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Sensors, Volume 16, Issue 12 (December 2016)

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Research

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Open AccessArticle Human Pose Estimation from Monocular Images: A Comprehensive Survey
Sensors 2016, 16(12), 1966; doi:10.3390/s16121966
Received: 4 July 2016 / Revised: 23 September 2016 / Accepted: 2 November 2016 / Published: 25 November 2016
Cited by 2 | PDF Full-text (2357 KB) | HTML Full-text | XML Full-text
Abstract
Human pose estimation refers to the estimation of the location of body parts and how they are connected in an image. Human pose estimation from monocular images has wide applications (e.g., image indexing). Several surveys on human pose estimation can be found in
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Human pose estimation refers to the estimation of the location of body parts and how they are connected in an image. Human pose estimation from monocular images has wide applications (e.g., image indexing). Several surveys on human pose estimation can be found in the literature, but they focus on a certain category; for example, model-based approaches or human motion analysis, etc. As far as we know, an overall review of this problem domain has yet to be provided. Furthermore, recent advancements based on deep learning have brought novel algorithms for this problem. In this paper, a comprehensive survey of human pose estimation from monocular images is carried out including milestone works and recent advancements. Based on one standard pipeline for the solution of computer vision problems, this survey splits the problem into several modules: feature extraction and description, human body models, and modeling methods. Problem modeling methods are approached based on two means of categorization in this survey. One way to categorize includes top-down and bottom-up methods, and another way includes generative and discriminative methods. Considering the fact that one direct application of human pose estimation is to provide initialization for automatic video surveillance, there are additional sections for motion-related methods in all modules: motion features, motion models, and motion-based methods. Finally, the paper also collects 26 publicly available data sets for validation and provides error measurement methods that are frequently used. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle Emotion-Bracelet: A Web Service for Expressing Emotions through an Electronic Interface
Sensors 2016, 16(12), 1980; doi:10.3390/s16121980
Received: 1 June 2016 / Revised: 23 October 2016 / Accepted: 9 November 2016 / Published: 24 November 2016
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Abstract
The mechanisms to communicate emotions have dramatically changed in the last 10 years with social networks, where users massively communicate their emotional states by using the Internet. However, people with socialization problems have difficulty expressing their emotions verbally or interpreting the environment and
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The mechanisms to communicate emotions have dramatically changed in the last 10 years with social networks, where users massively communicate their emotional states by using the Internet. However, people with socialization problems have difficulty expressing their emotions verbally or interpreting the environment and providing an appropriate emotional response. In this paper, a novel solution called the Emotion-Bracelet is presented that combines a hardware device and a software system. The proposed approach identifies the polarity and emotional intensity of texts published on a social network site by performing real-time processing using a web service. It also shows emotions with a LED matrix using five emoticons that represent positive, very positive, negative, very negative, and neutral states. The Emotion-Bracelet is designed to help people express their emotions in a non-intrusive way, thereby expanding the social aspect of human emotions. Full article
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Open AccessArticle Remote Blood Glucose Monitoring in mHealth Scenarios: A Review
Sensors 2016, 16(12), 1983; doi:10.3390/s16121983
Received: 27 September 2016 / Revised: 14 November 2016 / Accepted: 16 November 2016 / Published: 24 November 2016
Cited by 4 | PDF Full-text (3522 KB) | HTML Full-text | XML Full-text
Abstract
Glucose concentration in the blood stream is a critical vital parameter and an effective monitoring of this quantity is crucial for diabetes treatment and intensive care management. Effective bio-sensing technology and advanced signal processing are therefore of unquestioned importance for blood glucose monitoring.
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Glucose concentration in the blood stream is a critical vital parameter and an effective monitoring of this quantity is crucial for diabetes treatment and intensive care management. Effective bio-sensing technology and advanced signal processing are therefore of unquestioned importance for blood glucose monitoring. Nevertheless, collecting measurements only represents part of the process as another critical task involves delivering the collected measures to the treating specialists and caregivers. These include the clinical staff, the patient’s significant other, his/her family members, and many other actors helping with the patient treatment that may be located far away from him/her. In all of these cases, a remote monitoring system, in charge of delivering the relevant information to the right player, becomes an important part of the sensing architecture. In this paper, we review how the remote monitoring architectures have evolved over time, paralleling the progress in the Information and Communication Technologies, and describe our experiences with the design of telemedicine systems for blood glucose monitoring in three medical applications. The paper ends summarizing the lessons learned through the experiences of the authors and discussing the challenges arising from a large-scale integration of sensors and actuators. Full article
(This article belongs to the Special Issue Glucose Sensors: Revolution in Diabetes Management 2016)
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Open AccessArticle One-Pot Click Access to a Cyclodextrin Dimer-Based Novel Aggregation Induced Emission Sensor and Monomer-Based Chiral Stationary Phase
Sensors 2016, 16(12), 1985; doi:10.3390/s16121985
Received: 6 October 2016 / Revised: 7 November 2016 / Accepted: 14 November 2016 / Published: 24 November 2016
PDF Full-text (3076 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
A ‘two birds, one stone’ strategy was developed via a one-pot click reaction to simultaneously prepare a novel cyclodextrin (CD) dimer based aggregation induced emission (AIE) sensor (AIE-DCD) and a monomer based chiral stationary phase (CSP-MCD) for chiral high performance liquid chromatography (CHPLC).
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A ‘two birds, one stone’ strategy was developed via a one-pot click reaction to simultaneously prepare a novel cyclodextrin (CD) dimer based aggregation induced emission (AIE) sensor (AIE-DCD) and a monomer based chiral stationary phase (CSP-MCD) for chiral high performance liquid chromatography (CHPLC). AIE-DCD was found to afford satisfactory AIE response for specific detection of Zn2+ with a detection limit of 50 nM. CSP-MCD exhibits excellent enantioseparation ability toward dansyl amino acids, where the resolution of dansyl amino leucine reaches 5.43. Full article
(This article belongs to the Special Issue Colorimetric and Fluorescent Sensor)
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Open AccessArticle Toward Optimal Computation of Ultrasound Image Reconstruction Using CPU and GPU
Sensors 2016, 16(12), 1986; doi:10.3390/s16121986
Received: 13 September 2016 / Revised: 31 October 2016 / Accepted: 10 November 2016 / Published: 24 November 2016
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Abstract
An ultrasound image is reconstructed from echo signals received by array elements of a transducer. The time of flight of the echo depends on the distance between the focus to the array elements. The received echo signals have to be delayed to make
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An ultrasound image is reconstructed from echo signals received by array elements of a transducer. The time of flight of the echo depends on the distance between the focus to the array elements. The received echo signals have to be delayed to make their wave fronts and phase coherent before summing the signals. In digital beamforming, the delays are not always located at the sampled points. Generally, the values of the delayed signals are estimated by the values of the nearest samples. This method is fast and easy, however inaccurate. There are other methods available for increasing the accuracy of the delayed signals and, consequently, the quality of the beamformed signals; for example, the in-phase (I)/quadrature (Q) interpolation, which is more time consuming but provides more accurate values than the nearest samples. This paper compares the signals after dynamic receive beamforming, in which the echo signals are delayed using two methods, the nearest sample method and the I/Q interpolation method. The comparisons of the visual qualities of the reconstructed images and the qualities of the beamformed signals are reported. Moreover, the computational speeds of these methods are also optimized by reorganizing the data processing flow and by applying the graphics processing unit (GPU). The use of single and double precision floating-point formats of the intermediate data is also considered. The speeds with and without these optimizations are also compared. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle On Performance Analysis of Protective Jamming Schemes in Wireless Sensor Networks
Sensors 2016, 16(12), 1987; doi:10.3390/s16121987
Received: 31 October 2016 / Revised: 16 November 2016 / Accepted: 20 November 2016 / Published: 24 November 2016
Cited by 1 | PDF Full-text (571 KB) | HTML Full-text | XML Full-text
Abstract
Wireless sensor networks (WSNs) play an important role in Cyber Physical Social Sensing (CPSS) systems. An eavesdropping attack is one of the most serious threats to WSNs since it is a prerequisite for other malicious attacks. In this paper, we propose a novel
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Wireless sensor networks (WSNs) play an important role in Cyber Physical Social Sensing (CPSS) systems. An eavesdropping attack is one of the most serious threats to WSNs since it is a prerequisite for other malicious attacks. In this paper, we propose a novel anti-eavesdropping mechanism by introducing friendly jammers to wireless sensor networks (WSNs). In particular, we establish a theoretical framework to evaluate the eavesdropping risk of WSNs with friendly jammers and that of WSNs without jammers. Our theoretical model takes into account various channel conditions such as the path loss and Rayleigh fading, the placement schemes of jammers and the power controlling schemes of jammers. Extensive results show that using jammers in WSNs can effectively reduce the eavesdropping risk. Besides, our results also show that the appropriate placement of jammers and the proper assignment of emitting power of jammers can not only mitigate the eavesdropping risk but also may have no significant impairment to the legitimate communications. Full article
(This article belongs to the Special Issue New Paradigms in Cyber-Physical Social Sensing)
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Open AccessArticle A Dual Frequency Carrier Phase Error Difference Checking Algorithm for the GNSS Compass
Sensors 2016, 16(12), 1988; doi:10.3390/s16121988
Received: 1 September 2016 / Revised: 14 November 2016 / Accepted: 21 November 2016 / Published: 24 November 2016
Cited by 1 | PDF Full-text (6850 KB) | HTML Full-text | XML Full-text
Abstract
The performance of the Global Navigation Satellite System (GNSS) compass is related to the quality of carrier phase measurement. How to process the carrier phase error properly is important to improve the GNSS compass accuracy. In this work, we propose a dual frequency
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The performance of the Global Navigation Satellite System (GNSS) compass is related to the quality of carrier phase measurement. How to process the carrier phase error properly is important to improve the GNSS compass accuracy. In this work, we propose a dual frequency carrier phase error difference checking algorithm for the GNSS compass. The algorithm aims at eliminating large carrier phase error in dual frequency double differenced carrier phase measurement according to the error difference between two frequencies. The advantage of the proposed algorithm is that it does not need additional environment information and has a good performance on multiple large errors compared with previous research. The core of the proposed algorithm is removing the geographical distance from the dual frequency carrier phase measurement, then the carrier phase error is separated and detectable. We generate the Double Differenced Geometry-Free (DDGF) measurement according to the characteristic that the different frequency carrier phase measurements contain the same geometrical distance. Then, we propose the DDGF detection to detect the large carrier phase error difference between two frequencies. The theoretical performance of the proposed DDGF detection is analyzed. An open sky test, a manmade multipath test and an urban vehicle test were carried out to evaluate the performance of the proposed algorithm. The result shows that the proposed DDGF detection is able to detect large error in dual frequency carrier phase measurement by checking the error difference between two frequencies. After the DDGF detection, the accuracy of the baseline vector is improved in the GNSS compass. Full article
(This article belongs to the Section Remote Sensors)
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Open AccessArticle Utilizing a Wristband Sensor to Measure the Stress Level for People with Dementia
Sensors 2016, 16(12), 1989; doi:10.3390/s16121989
Received: 3 August 2016 / Revised: 4 November 2016 / Accepted: 18 November 2016 / Published: 24 November 2016
Cited by 1 | PDF Full-text (2871 KB) | HTML Full-text | XML Full-text
Abstract
Stress is a common problem that affects most people with dementia and their caregivers. Stress symptoms for people with dementia are often measured by answering a checklist of questions by the clinical staff who work closely with the person with the dementia. This
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Stress is a common problem that affects most people with dementia and their caregivers. Stress symptoms for people with dementia are often measured by answering a checklist of questions by the clinical staff who work closely with the person with the dementia. This process requires a lot of effort with continuous observation of the person with dementia over the long term. This article investigates the effectiveness of using a straightforward method, based on a single wristband sensor to classify events of “Stressed” and “Not stressed” for people with dementia. The presented system calculates the stress level as an integer value from zero to five, providing clinical information of behavioral patterns to the clinical staff. Thirty staff members participated in this experiment, together with six residents suffering from dementia, from two nursing homes. The residents were equipped with the wristband sensor during the day, and the staff were writing observation notes during the experiment to serve as ground truth. Experimental evaluation showed relationships between staff observations and sensor analysis, while stress level thresholds adjusted to each individual can serve different scenarios. Full article
(This article belongs to the Special Issue Sensing Technology for Healthcare System)
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Open AccessArticle Micro-Doppler Based Classification of Human Aquatic Activities via Transfer Learning of Convolutional Neural Networks
Sensors 2016, 16(12), 1990; doi:10.3390/s16121990
Received: 19 September 2016 / Revised: 7 November 2016 / Accepted: 18 November 2016 / Published: 24 November 2016
Cited by 2 | PDF Full-text (2193 KB) | HTML Full-text | XML Full-text
Abstract
Accurate classification of human aquatic activities using radar has a variety of potential applications such as rescue operations and border patrols. Nevertheless, the classification of activities on water using radar has not been extensively studied, unlike the case on dry ground, due to
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Accurate classification of human aquatic activities using radar has a variety of potential applications such as rescue operations and border patrols. Nevertheless, the classification of activities on water using radar has not been extensively studied, unlike the case on dry ground, due to its unique challenge. Namely, not only is the radar cross section of a human on water small, but the micro-Doppler signatures are much noisier due to water drops and waves. In this paper, we first investigate whether discriminative signatures could be obtained for activities on water through a simulation study. Then, we show how we can effectively achieve high classification accuracy by applying deep convolutional neural networks (DCNN) directly to the spectrogram of real measurement data. From the five-fold cross-validation on our dataset, which consists of five aquatic activities, we report that the conventional feature-based scheme only achieves an accuracy of 45.1%. In contrast, the DCNN trained using only the collected data attains 66.7%, and the transfer learned DCNN, which takes a DCNN pre-trained on a RGB image dataset and fine-tunes the parameters using the collected data, achieves a much higher 80.3%, which is a significant performance boost. Full article
(This article belongs to the Special Issue Non-Contact Sensing)
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Open AccessArticle Design and Fabrication of Micro Hemispheric Shell Resonator with Annular Electrodes
Sensors 2016, 16(12), 1991; doi:10.3390/s16121991
Received: 27 August 2016 / Revised: 11 November 2016 / Accepted: 21 November 2016 / Published: 25 November 2016
Cited by 1 | PDF Full-text (6477 KB) | HTML Full-text | XML Full-text
Abstract
Electrostatic driving and capacitive detection is widely used in micro hemispheric shell resonators (HSR). The capacitor gap distance is a dominant factor for the initial capacitance, and affects the driving voltage and sensitivity. In order to decrease the equivalent gap distance, a micro
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Electrostatic driving and capacitive detection is widely used in micro hemispheric shell resonators (HSR). The capacitor gap distance is a dominant factor for the initial capacitance, and affects the driving voltage and sensitivity. In order to decrease the equivalent gap distance, a micro HSR with annular electrodes fabricated by a glassblowing method was developed. Central and annular cavities are defined, and then the inside gas drives glass softening and deformation at 770 °C. While the same force is applied, the deformation of the hemispherical shell is about 200 times that of the annular electrodes, illustrating that the deformation of the electrodes will not affect the measurement accuracy. S-shaped patterns on the annular electrodes and internal-gear-like patterns on the hemispherical shell can improve metal malleability and avoid metal cracking during glass expansion. An arched annular electrode and a hemispheric shell are demonstrated. Compared with HSR with a spherical electrode, the applied voltage could be reduced by 29%, and the capacitance could be increased by 39%, according to theoretical and numerical calculation. The surface roughness of glass after glassblowing was favorable (Rq = 0.296 nm, Ra = 0.217 nm). In brief, micro HSR with an annular electrode was fabricated, and its superiority was preliminarily confirmed. Full article
(This article belongs to the Special Issue Resonator Sensors)
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Open AccessArticle Optical Microbubble Resonators with High Refractive Index Inner Coating for Bio-Sensing Applications: An Analytical Approach
Sensors 2016, 16(12), 1992; doi:10.3390/s16121992
Received: 30 September 2016 / Revised: 17 November 2016 / Accepted: 22 November 2016 / Published: 25 November 2016
Cited by 1 | PDF Full-text (38442 KB) | HTML Full-text | XML Full-text
Abstract
The design of Whispering Gallery Mode Resonators (WGMRs) used as an optical transducer for biosensing represents the first and crucial step towards the optimization of the final device performance in terms of sensitivity and Limit of Detection (LoD). Here, we propose an analytical
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The design of Whispering Gallery Mode Resonators (WGMRs) used as an optical transducer for biosensing represents the first and crucial step towards the optimization of the final device performance in terms of sensitivity and Limit of Detection (LoD). Here, we propose an analytical method for the design of an optical microbubble resonator (OMBR)-based biosensor. In order to enhance the OMBR sensing performance, we consider a polymeric layer of high refractive index as an inner coating for the OMBR. The effect of this layer and other optical/geometrical parameters on the mode field distribution, sensitivity and LoD of the OMBR is assessed and discussed, both for transverse electric (TE) and transverse magnetic (TM) polarization. The obtained results do provide physical insights for the development of OMBR-based biosensor. Full article
(This article belongs to the Special Issue Label-Free Optical Biosensors)
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Open AccessArticle Privacy-Preserving Location-Based Service Scheme for Mobile Sensing Data
Sensors 2016, 16(12), 1993; doi:10.3390/s16121993
Received: 9 August 2016 / Revised: 23 October 2016 / Accepted: 22 November 2016 / Published: 25 November 2016
Cited by 1 | PDF Full-text (556 KB) | HTML Full-text | XML Full-text
Abstract
With the wide use of mobile sensing application, more and more location-embedded data are collected and stored in mobile clouds, such as iCloud, Samsung cloud, etc. Using these data, the cloud service provider (CSP) can provide location-based service (LBS) for users. However, the
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With the wide use of mobile sensing application, more and more location-embedded data are collected and stored in mobile clouds, such as iCloud, Samsung cloud, etc. Using these data, the cloud service provider (CSP) can provide location-based service (LBS) for users. However, the mobile cloud is untrustworthy. The privacy concerns force the sensitive locations to be stored on the mobile cloud in an encrypted form. However, this brings a great challenge to utilize these data to provide efficient LBS. To solve this problem, we propose a privacy-preserving LBS scheme for mobile sensing data, based on the RSA (for Rivest, Shamir and Adleman) algorithm and ciphertext policy attribute-based encryption (CP-ABE) scheme. The mobile cloud can perform location distance computing and comparison efficiently for authorized users, without location privacy leakage. In the end, theoretical security analysis and experimental evaluation demonstrate that our scheme is secure against the chosen plaintext attack (CPA) and efficient enough for practical applications in terms of user side computation overhead. Full article
(This article belongs to the Special Issue Big Data and Cloud Computing for Sensor Networks)
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Open AccessArticle Test of the Practicality and Feasibility of EDoF-Empowered Image Sensors for Long-Range Biometrics
Sensors 2016, 16(12), 1994; doi:10.3390/s16121994
Received: 28 September 2016 / Revised: 17 November 2016 / Accepted: 18 November 2016 / Published: 25 November 2016
Cited by 1 | PDF Full-text (5099 KB) | HTML Full-text | XML Full-text
Abstract
For many practical applications of image sensors, how to extend the depth-of-field (DoF) is an important research topic; if successfully implemented, it could be beneficial in various applications, from photography to biometrics. In this work, we want to examine the feasibility and practicability
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For many practical applications of image sensors, how to extend the depth-of-field (DoF) is an important research topic; if successfully implemented, it could be beneficial in various applications, from photography to biometrics. In this work, we want to examine the feasibility and practicability of a well-known “extended DoF” (EDoF) technique, or “wavefront coding,” by building real-time long-range iris recognition and performing large-scale iris recognition. The key to the success of long-range iris recognition includes long DoF and image quality invariance toward various object distance, which is strict and harsh enough to test the practicality and feasibility of EDoF-empowered image sensors. Besides image sensor modification, we also explored the possibility of varying enrollment/testing pairs. With 512 iris images from 32 Asian people as the database, 400-mm focal length and F/6.3 optics over 3 m working distance, our results prove that a sophisticated coding design scheme plus homogeneous enrollment/testing setups can effectively overcome the blurring caused by phase modulation and omit Wiener-based restoration. In our experiments, which are based on 3328 iris images in total, the EDoF factor can achieve a result 3.71 times better than the original system without a loss of recognition accuracy. Full article
(This article belongs to the Special Issue Imaging: Sensors and Technologies) Printed Edition available
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Open AccessArticle Design of a Solar Tracking System Using the Brightest Region in the Sky Image Sensor
Sensors 2016, 16(12), 1995; doi:10.3390/s16121995
Received: 12 October 2016 / Revised: 18 November 2016 / Accepted: 18 November 2016 / Published: 25 November 2016
Cited by 2 | PDF Full-text (6097 KB) | HTML Full-text | XML Full-text
Abstract
Solar energy is certainly an energy source worth exploring and utilizing because of the environmental protection it offers. However, the conversion efficiency of solar energy is still low. If the photovoltaic panel perpendicularly tracks the sun, the solar energy conversion efficiency will be
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Solar energy is certainly an energy source worth exploring and utilizing because of the environmental protection it offers. However, the conversion efficiency of solar energy is still low. If the photovoltaic panel perpendicularly tracks the sun, the solar energy conversion efficiency will be improved. In this article, we propose an innovative method to track the sun using an image sensor. In our method, it is logical to assume the points of the brightest region in the sky image representing the location of the sun. Then, the center of the brightest region is assumed to be the solar-center, and is mathematically calculated using an embedded processor (Raspberry Pi). Finally, the location information on the sun center is sent to the embedded processor to control two servo motors that are capable of moving both horizontally and vertically to track the sun. In comparison with the existing sun tracking methods using image sensors, such as the Hough transform method, our method based on the brightest region in the sky image remains accurate under conditions such as a sunny day and building shelter. The practical sun tracking system using our method was implemented and tested. The results reveal that the system successfully captured the real sun center in most weather conditions, and the servo motor system was able to direct the photovoltaic panel perpendicularly to the sun center. In addition, our system can be easily and practically integrated, and can operate in real-time. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle Visualization of Venous Compliance of Superficial Veins Using Non-Contact Plethysmography Based on Digital Red-Green-Blue Images
Sensors 2016, 16(12), 1996; doi:10.3390/s16121996
Received: 4 September 2016 / Revised: 2 November 2016 / Accepted: 19 November 2016 / Published: 25 November 2016
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Abstract
We propose the visualization of venous compliance (VC) using a digital red-green-blue (RGB) camera. The new imaging method, which transforms RGB values into VC, combines VC evaluation with blood concentration estimation from the RGB values of each pixel. We evaluate a non-contact plethysmography
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We propose the visualization of venous compliance (VC) using a digital red-green-blue (RGB) camera. The new imaging method, which transforms RGB values into VC, combines VC evaluation with blood concentration estimation from the RGB values of each pixel. We evaluate a non-contact plethysmography (NCPG) system for VC based on comparisons with conventional strain gauge plethysmography (SPG). We conduct in vivo measurements using both systems and investigate their differences by evaluating the VC. The results show that the two methods measure different blood vessels and that errors caused by interstitial fluid accumulation are negligible for the NCPG system, whereas SPG is influenced by such errors. Additionally, we investigate the relationship between VC and physical activity using NCPG. Full article
(This article belongs to the Special Issue Non-Contact Sensing)
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Open AccessArticle Atmospheric Correction of Satellite GF-1/WFV Imagery and Quantitative Estimation of Suspended Particulate Matter in the Yangtze Estuary
Sensors 2016, 16(12), 1997; doi:10.3390/s16121997
Received: 29 September 2016 / Revised: 10 November 2016 / Accepted: 11 November 2016 / Published: 25 November 2016
PDF Full-text (8308 KB) | HTML Full-text | XML Full-text
Abstract
The Multispectral Wide Field of View (WFV) camera on the Chinese GF-1 satellite, launched in 2013, has advantages of high spatial resolution (16 m), short revisit period (4 days) and wide scene swath (800 km) compared to the Landsat-8/OLI, which make it an
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The Multispectral Wide Field of View (WFV) camera on the Chinese GF-1 satellite, launched in 2013, has advantages of high spatial resolution (16 m), short revisit period (4 days) and wide scene swath (800 km) compared to the Landsat-8/OLI, which make it an ideal means of monitoring spatial-temporal changes of Suspended Particulate Matter (SPM) in large estuaries like the Yangtze Estuary. However, a lack of proper atmospheric correction methods has limited its application in water quality assessment. We propose an atmospheric correction method based on a look up table coupled by the atmosphere radiative transfer model (6S) and the water semi-empirical radiative transfer (SERT) model for inversion of water-leaving reflectance from GF-1 top-of-atmosphere radiance, and then retrieving SPM concentration from water-leaving radiance reflectance of the Yangtze Estuary and its adjacent sea. Results are validated by the Landsat-8/OLI imagery together with autonomous fixed station data, and influences of human activities (e.g., waterway construction and shipping) on SPM distribution are analyzed. Full article
(This article belongs to the Special Issue Sensors and Sensing in Water Quality Assessment and Monitoring)
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Open AccessArticle Reciprocally-Benefited Secure Transmission for Spectrum Sensing-Based Cognitive Radio Sensor Networks
Sensors 2016, 16(12), 1998; doi:10.3390/s16121998
Received: 20 September 2016 / Revised: 10 November 2016 / Accepted: 18 November 2016 / Published: 25 November 2016
Cited by 2 | PDF Full-text (626 KB) | HTML Full-text | XML Full-text
Abstract
The rapid proliferation of independently-designed and -deployed wireless sensor networks extremely crowds the wireless spectrum and promotes the emergence of cognitive radio sensor networks (CRSN). In CRSN, the sensor node (SN) can make full use of the unutilized licensed spectrum, and the spectrum
[...] Read more.
The rapid proliferation of independently-designed and -deployed wireless sensor networks extremely crowds the wireless spectrum and promotes the emergence of cognitive radio sensor networks (CRSN). In CRSN, the sensor node (SN) can make full use of the unutilized licensed spectrum, and the spectrum efficiency is greatly improved. However, inevitable spectrum sensing errors will adversely interfere with the primary transmission, which may result in primary transmission outage. To compensate the adverse effect of spectrum sensing errors, we propose a reciprocally-benefited secure transmission strategy, in which SN’s interference to the eavesdropper is employed to protect the primary confidential messages while the CRSN is also rewarded with a loose spectrum sensing error probability constraint. Specifically, according to the spectrum sensing results and primary users’ activities, there are four system states in this strategy. For each state, we analyze the primary secrecy rate and the SN’s transmission rate by taking into account the spectrum sensing errors. Then, the SN’s transmit power is optimally allocated for each state so that the average transmission rate of CRSN is maximized under the constraint of the primary maximum permitted secrecy outage probability. In addition, the performance tradeoff between the transmission rate of CRSN and the primary secrecy outage probability is investigated. Moreover, we analyze the primary secrecy rate for the asymptotic scenarios and derive the closed-form expression of the SN’s transmission outage probability. Simulation results show that: (1) the performance of the SN’s average throughput in the proposed strategy outperforms the conventional overlay strategy; (2) both the primary network and CRSN benefit from the proposed strategy. Full article
(This article belongs to the Special Issue Trusted and Secure Wireless Sensor Network Designs and Deployments)
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Open AccessArticle Mitigating RF Front-End Nonlinearity of Sensor Nodes to Enhance Spectrum Sensing
Sensors 2016, 16(12), 1999; doi:10.3390/s16121999
Received: 1 August 2016 / Revised: 7 November 2016 / Accepted: 10 November 2016 / Published: 25 November 2016
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Abstract
The cognitive radio wireless sensor network (CR-WSN) has gained worldwide attention in recent years for its potential applications. Reliable spectrum sensing is the premise for opportunistic access to sensor nodes. However, as a result of the radio frequency (RF) front-end nonlinearity of sensor
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The cognitive radio wireless sensor network (CR-WSN) has gained worldwide attention in recent years for its potential applications. Reliable spectrum sensing is the premise for opportunistic access to sensor nodes. However, as a result of the radio frequency (RF) front-end nonlinearity of sensor nodes, distortion products can easily degrade the spectrum sensing performance by causing false alarms and degrading the detection probability. Given the limitations of the widely-used adaptive interference cancellation (AIC) algorithm, this paper develops several details to avoid these limitations and form a new mitigation architecture to alleviate nonlinear distortions. To demonstrate the efficiency of the proposed algorithm, verification tests for both simulations and actual RF front-end measurements are presented and discussed. The obtained results show that distortions can be suppressed significantly, thus improving the reliability of spectrum sensing. Moreover, compared to AIC, the proposed algorithm clearly shows better performance, especially at the band edges of the interferer signal. Full article
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Open AccessArticle Validation and Parameter Sensitivity Tests for Reconstructing Swell Field Based on an Ensemble Kalman Filter
Sensors 2016, 16(12), 2000; doi:10.3390/s16122000
Received: 21 May 2016 / Revised: 19 October 2016 / Accepted: 11 November 2016 / Published: 25 November 2016
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Abstract
The swell propagation model built on geometric optics is known to work well when simulating radiated swells from a far located storm. Based on this simple approximation, satellites have acquired plenty of large samples on basin-traversing swells induced by fierce storms situated in
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The swell propagation model built on geometric optics is known to work well when simulating radiated swells from a far located storm. Based on this simple approximation, satellites have acquired plenty of large samples on basin-traversing swells induced by fierce storms situated in mid-latitudes. How to routinely reconstruct swell fields with these irregularly sampled observations from space via known swell propagation principle requires more examination. In this study, we apply 3-h interval pseudo SAR observations in the ensemble Kalman filter (EnKF) to reconstruct a swell field in ocean basin, and compare it with buoy swell partitions and polynomial regression results. As validated against in situ measurements, EnKF works well in terms of spatial–temporal consistency in far-field swell propagation scenarios. Using this framework, we further address the influence of EnKF parameters, and perform a sensitivity analysis to evaluate estimations made under different sets of parameters. Such analysis is of key interest with respect to future multiple-source routinely recorded swell field data. Satellite-derived swell data can serve as a valuable complementary dataset to in situ or wave re-analysis datasets. Full article
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Open AccessArticle The Design and Characterization of a Flexible Tactile Sensing Array for Robot Skin
Sensors 2016, 16(12), 2001; doi:10.3390/s16122001
Received: 12 September 2016 / Revised: 10 November 2016 / Accepted: 22 November 2016 / Published: 25 November 2016
Cited by 4 | PDF Full-text (4352 KB) | HTML Full-text | XML Full-text
Abstract
In this study, a flexible tactile sensing array based on a capacitive mechanism was designed, fabricated, and characterized for sensitive robot skin. A device with 8 × 8 sensing units was composed of top and bottom flexible polyethyleneterephthalate (PET) substrates with copper (Cu)
[...] Read more.
In this study, a flexible tactile sensing array based on a capacitive mechanism was designed, fabricated, and characterized for sensitive robot skin. A device with 8 × 8 sensing units was composed of top and bottom flexible polyethyleneterephthalate (PET) substrates with copper (Cu) electrodes, a polydimethylsiloxane (PDMS) dielectric layer, and a bump contact layer. Four types of microstructures (i.e., pyramids and V-shape grooves) atop a PDMS dielectric layer were well-designed and fabricated to enhance tactile sensitivity. The optimal sensing unit achieved a high sensitivity of 35.9%/N in a force range of 0–1 N. By incorporating a tactile feedback control system, the flexible sensing array as the sensitive skin of a robotic manipulator demonstrated a potential capability of robotic obstacle avoidance. Full article
(This article belongs to the Special Issue Flexible Electronics and Sensors)
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Open AccessArticle Reconfigurable Multiparameter Biosignal Acquisition SoC for Low Power Wearable Platform
Sensors 2016, 16(12), 2002; doi:10.3390/s16122002
Received: 30 September 2016 / Revised: 17 November 2016 / Accepted: 24 November 2016 / Published: 25 November 2016
Cited by 1 | PDF Full-text (6457 KB) | HTML Full-text | XML Full-text
Abstract
A low power and low noise reconfigurable analog front-end (AFE) system on a chip (SoC) for biosignal acquisition is presented. The presented AFE can be reconfigured for use in electropotential, bioimpedance, electrochemical, and photoelectrical modes. The advanced healthcare services based on multiparameter physiological
[...] Read more.
A low power and low noise reconfigurable analog front-end (AFE) system on a chip (SoC) for biosignal acquisition is presented. The presented AFE can be reconfigured for use in electropotential, bioimpedance, electrochemical, and photoelectrical modes. The advanced healthcare services based on multiparameter physiological biosignals can be easily implemented with these multimodal and highly reconfigurable features of the proposed system. The reconfigurable gain and input referred noise of the core instrumentation amplifier block are 25 dB to 52 dB, and 1 μVRMS, respectively. The power consumption of the analog blocks in one readout channel is less than 52 μW. The reconfigurable capability among various modes of applications including electrocardiogram, blood glucose concentration, respiration, and photoplethysmography are shown experimentally. Full article
(This article belongs to the Section Biosensors)
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Open AccessArticle Data-Driven Multiresolution Camera Using the Foveal Adaptive Pyramid
Sensors 2016, 16(12), 2003; doi:10.3390/s16122003
Received: 23 August 2016 / Revised: 16 November 2016 / Accepted: 18 November 2016 / Published: 26 November 2016
Cited by 2 | PDF Full-text (2526 KB) | HTML Full-text | XML Full-text
Abstract
There exist image processing applications, such as tracking or pattern recognition, that are not necessarily precise enough to maintain the same resolution across the whole image sensor. In fact, they must only keep it as high as possible in a relatively small region,
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There exist image processing applications, such as tracking or pattern recognition, that are not necessarily precise enough to maintain the same resolution across the whole image sensor. In fact, they must only keep it as high as possible in a relatively small region, but covering a wide field of view. This is the aim of foveal vision systems. Briefly, they propose to sense a large field of view at a spatially-variant resolution: one relatively small region, the fovea, is mapped at a high resolution, while the rest of the image is captured at a lower resolution. In these systems, this fovea must be moved, from one region of interest to another one, to scan a visual scene. It is interesting that the part of the scene that is covered by the fovea should not be merely spatial, but closely related to perceptual objects. Segmentation and attention are then intimately tied together: while the segmentation process is responsible for extracting perceptively-coherent entities from the scene (proto-objects), attention can guide segmentation. From this loop, the concept of foveal attention arises. This work proposes a hardware system for mapping a uniformly-sampled sensor to a space-variant one. Furthermore, this mapping is tied with a software-based, foveal attention mechanism that takes as input the stream of generated foveal images. The whole hardware/software architecture has been designed to be embedded within an all programmable system on chip (AP SoC). Our results show the flexibility of the data port for exchanging information between the mapping and attention parts of the architecture and the good performance rates of the mapping procedure. Experimental evaluation also demonstrates that the segmentation method and the attention model provide results comparable to other more computationally-expensive algorithms. Full article
(This article belongs to the Special Issue State-of-the-Art Sensors Technology in Spain 2016)
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Open AccessArticle Estimating Leaf Area Index (LAI) in Vineyards Using the PocketLAI Smart-App
Sensors 2016, 16(12), 2004; doi:10.3390/s16122004
Received: 13 September 2016 / Revised: 17 November 2016 / Accepted: 18 November 2016 / Published: 26 November 2016
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Abstract
Estimating leaf area index (LAI) of Vitis vinifera using indirect methods involves some critical issues, related to its discontinuous and non-homogeneous canopy. This study evaluates the smart app PocketLAI and hemispherical photography in vineyards against destructive LAI measurements. Data were collected during six
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Estimating leaf area index (LAI) of Vitis vinifera using indirect methods involves some critical issues, related to its discontinuous and non-homogeneous canopy. This study evaluates the smart app PocketLAI and hemispherical photography in vineyards against destructive LAI measurements. Data were collected during six surveys in an experimental site characterized by a high level of heterogeneity among plants, allowing us to explore a wide range of LAI values. During the last survey, the possibility to combine remote sensing data and in-situ PocketLAI estimates (smart scouting) was evaluated. Results showed a good agreement between PocketLAI data and direct measurements, especially for LAI ranging from 0.13 to 1.41 (R2 = 0.94, RRMSE = 17.27%), whereas the accuracy decreased when an outlying value (vineyard LAI = 2.84) was included (R2 = 0.77, RRMSE = 43.00%), due to the saturation effect in case of very dense canopies arising from lack of green pruning. The hemispherical photography showed very high values of R2, even in presence of the outlying value (R2 = 0.94), although it showed a marked and quite constant overestimation error (RRMSE = 99.46%), suggesting the need to introduce a correction factor specific for vineyards. During the smart scouting, PocketLAI showed its reliability to monitor the spatial-temporal variability of vine vigor in cordon-trained systems, and showed a potential for a wide range of applications, also in combination with remote sensing. Full article
(This article belongs to the Special Issue Precision Agriculture and Remote Sensing Data Fusion)
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Open AccessArticle Identification of Object Dynamics Using Hand Worn Motion and Force Sensors
Sensors 2016, 16(12), 2005; doi:10.3390/s16122005
Received: 29 May 2016 / Revised: 16 November 2016 / Accepted: 21 November 2016 / Published: 26 November 2016
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Abstract
Emerging microelectromechanical system (MEMS)-based sensors become much more applicable for on-body measurement purposes lately. Especially, the development of a finger tip-sized tri-axial force sensor gives the opportunity to measure interaction forces between the human hand and environmental objects. We have developed a new
[...] Read more.
Emerging microelectromechanical system (MEMS)-based sensors become much more applicable for on-body measurement purposes lately. Especially, the development of a finger tip-sized tri-axial force sensor gives the opportunity to measure interaction forces between the human hand and environmental objects. We have developed a new prototype device that allows simultaneous 3D force and movement measurements at the finger and thumb tips. The combination of interaction forces and movements makes it possible to identify the dynamical characteristics of the object being handled by the hand. With this device attached to the hand, a subject manipulated mass and spring objects under varying conditions. We were able to identify and estimate the weight of two physical mass objects (0.44 kg: 29 . 3 % ± 18 . 9 % and 0.28 kg: 19 . 7 % ± 10 . 6 % ) and the spring constant of a physical spring object ( 16 . 3 % ± 12 . 6 % ). The system is a first attempt to quantify the interactions of the hand with the environment and has many potential applications in rehabilitation, ergonomics and sports. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle Gap Measurement of Point Machine Using Adaptive Wavelet Threshold and Mathematical Morphology
Sensors 2016, 16(12), 2006; doi:10.3390/s16122006
Received: 1 October 2016 / Revised: 15 November 2016 / Accepted: 23 November 2016 / Published: 26 November 2016
Cited by 3 | PDF Full-text (593 KB) | HTML Full-text | XML Full-text
Abstract
A point machine’s gap is an important indication of its healthy status. An edge detection algorithm is proposed to measure and calculate a point machine’s gap from the gap image captured by CCD plane arrays. This algorithm integrates adaptive wavelet-based image denoising, locally
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A point machine’s gap is an important indication of its healthy status. An edge detection algorithm is proposed to measure and calculate a point machine’s gap from the gap image captured by CCD plane arrays. This algorithm integrates adaptive wavelet-based image denoising, locally adaptive image binarization, and mathematical morphology technologies. The adaptive wavelet-based image denoising obtains not only an optimal denoising threshold, but also unblurred edges. Locally adaptive image binarization has the advantage of overcoming the local intensity variation in gap images. Mathematical morphology may suppress speckle spots caused by reflective metal surfaces in point machines. The subjective and objective evaluations of the proposed method are presented by using point machine gap images from a railway corporation in China. The performance between the proposed method and conventional edge detection methods has also been compared, and the result shows that the former outperforms the latter. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle Fast Interrogation of Fiber Bragg Gratings with Electro-Optical Dual Optical Frequency Combs
Sensors 2016, 16(12), 2007; doi:10.3390/s16122007
Received: 30 September 2016 / Revised: 21 November 2016 / Accepted: 23 November 2016 / Published: 26 November 2016
Cited by 3 | PDF Full-text (3831 KB) | HTML Full-text | XML Full-text
Abstract
Optical frequency combs (OFC) generated by electro-optic modulation of continuous-wave lasers provide broadband coherent sources with high power per line and independent control of line spacing and the number of lines. In addition to their application in spectroscopy, they offer flexible and optimized
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Optical frequency combs (OFC) generated by electro-optic modulation of continuous-wave lasers provide broadband coherent sources with high power per line and independent control of line spacing and the number of lines. In addition to their application in spectroscopy, they offer flexible and optimized sources for the interrogation of other sensors based on wavelength change or wavelength filtering, such as fiber Bragg grating (FBG) sensors. In this paper, a dual-OFC FBG interrogation system based on a single laser and two optical-phase modulators is presented. This architecture allows for the configuration of multimode optical source parameters such as the number of modes and their position within the reflected spectrum of the FBG. A direct read-out is obtained by mapping the optical spectrum onto the radio-frequency spectrum output of the dual-comb. This interrogation scheme is proposed for measuring fast phenomena such as vibrations and ultrasounds. Results are presented for dual-comb operation under optimized control. The optical modes are mapped onto detectable tones that are multiples of 0.5 MHz around a center radiofrequency tone (40 MHz). Measurements of ultrasounds (40 kHz and 120 kHz) are demonstrated with this sensing system. Ultrasounds induce dynamic strain onto the fiber, which generates changes in the reflected Bragg wavelength and, hence, modulates the amplitude of the OFC modes within the reflected spectrum. The amplitude modulation of two counterphase tones is detected to obtain a differential measurement proportional to the ultrasound signal. Full article
(This article belongs to the Special Issue Optical Fiber Sensors 2016)
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Open AccessArticle An Alternative Approach for Registration of
High-Resolution Satellite Optical Imagery and ICESat Laser Altimetry Data
Sensors 2016, 16(12), 2008; doi:10.3390/s16122008
Received: 25 September 2016 / Revised: 22 November 2016 / Accepted: 24 November 2016 / Published: 27 November 2016
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Abstract
Satellite optical images and altimetry data are two major data sources used in Antarctic research. The integration use of these two datasets is expected to provide more accurate and higher quality products, during which data registration is the first issue that needs to
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Satellite optical images and altimetry data are two major data sources used in Antarctic research. The integration use of these two datasets is expected to provide more accurate and higher quality products, during which data registration is the first issue that needs to be solved. This paper presents an alternative approach for the registration of high-resolution satellite optical images and ICESat (Ice, Cloud, and land Elevation Satellite) laser altimetry data. Due to the sparse distribution characteristic of the ICESat laser point data, it is difficult and even impossible to find same-type conjugate features between ICESat data and satellite optical images. The method is implemented in a direct way to correct the point-to-line inconsistency in image space through 2D transformation between the projected terrain feature points and the corresponding 2D image lines, which is simpler than discrepancy correction in object space that requires stereo images for 3D model construction, and easier than the indirect way of image orientation correction via photogrammetric bundle adjustment. The correction parameters are further incorporated into imaging model through RPCs (Rational Polynomial Coefficients) generation/regeneration for the convenience of photogrammetric applications. The experimental results by using the ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) images and ZY-3 (Ziyuan-3 satellite) images for registration with ICESat data showed that sub-pixel level registration accuracies were achieved after registration, which have validated the feasibility and effectiveness of the presented approach. Full article
(This article belongs to the Section Remote Sensors)
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Open AccessArticle MECS-VINE®: A New Proximal Sensor for Segmented Mapping of Vigor and Yield Parameters on Vineyard Rows
Sensors 2016, 16(12), 2009; doi:10.3390/s16122009
Received: 24 September 2016 / Revised: 23 November 2016 / Accepted: 24 November 2016 / Published: 27 November 2016
PDF Full-text (4433 KB) | HTML Full-text | XML Full-text
Abstract
Ground-based proximal sensing of vineyard features is gaining interest due to its ability to serve in even quite small plots with the advantage of being conducted concurrently with normal vineyard practices (i.e., spraying, pruning or soil tilling) with no dependence upon weather conditions,
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Ground-based proximal sensing of vineyard features is gaining interest due to its ability to serve in even quite small plots with the advantage of being conducted concurrently with normal vineyard practices (i.e., spraying, pruning or soil tilling) with no dependence upon weather conditions, external services or law-imposed limitations. The purpose of the present work was to test performance of the new terrestrial multi-sensor MECS-VINE® in terms of reliability and degree of correlation with several canopy growth and yield parameters in the grapevine. MECS-VINE®, once conveniently positioned in front of the tractor, can provide simultaneous assessment of growth features and microclimate of specific canopy sections of the two adjacent row sides. MECS-VINE® integrates a series of microclimate sensors (air relative humidity, air and surface temperature) with two (left and right) matrix-based optical RGB imaging sensors and a related algorithm, termed Canoyct). MECS-VINE® was run five times along the season in a mature cv. Barbera vineyard and a Canopy Index (CI, pure number varying from 0 to 1000), calculated through its built-in algorithm, validated vs. canopy structure parameters (i.e., leaf layer number, fractions of canopy gaps and interior leaves) derived from point quadrat analysis. Results showed that CI was highly correlated vs. any canopy parameter at any date, although the closest relationships were found for CI vs. fraction of canopy gaps (R2 = 0.97) and leaf layer number (R2 = 0.97) for data pooled over 24 test vines. While correlations against canopy light interception and total lateral leaf area were still unsatisfactory, a good correlation was found vs. cluster and berry weight (R2 = 0.76 and 0.71, respectively) suggesting a good potential also for yield estimates. Besides the quite satisfactory calibration provided, main improvements of MECS-VINE® usage versus other current equipment are: (i) MECS-VINE® delivers a segmented evaluation of the canopy up to 15 different sectors, therefore allowing to differentiate canopy structure and density at specific and crucial canopy segments (i.e., basal part where clusters are located) and (ii) the sensor is optimized to work at any time of the day with any weather condition without the need of any supplemental lighting system. Full article
(This article belongs to the Section Remote Sensors)
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Open AccessArticle Is the Geographic Range of Mangrove Forests in the Conterminous United States Really Expanding?
Sensors 2016, 16(12), 2010; doi:10.3390/s16122010
Received: 21 August 2016 / Revised: 16 October 2016 / Accepted: 21 October 2016 / Published: 28 November 2016
Cited by 5 | PDF Full-text (8874 KB) | HTML Full-text | XML Full-text
Abstract
Changes in the distribution and abundance of mangrove species within and outside of their historic geographic range can have profound consequences in the provision of ecosystem goods and services they provide. Mangroves in the conterminous United States (CONUS) are believed to be expanding
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Changes in the distribution and abundance of mangrove species within and outside of their historic geographic range can have profound consequences in the provision of ecosystem goods and services they provide. Mangroves in the conterminous United States (CONUS) are believed to be expanding poleward (north) due to decreases in the frequency and severity of extreme cold events, while sea level rise is a factor often implicated in the landward expansion of mangroves locally. We used ~35 years of satellite imagery and in situ observations for CONUS and report that: (i) poleward expansion of mangrove forest is inconclusive, and may have stalled for now, and (ii) landward expansion is actively occurring within the historical northernmost limit. We revealed that the northernmost latitudinal limit of mangrove forests along the east and west coasts of Florida, in addition to Louisiana and Texas has not systematically expanded toward the pole. Mangrove area, however, expanded by 4.3% from 1980 to 2015 within the historic northernmost boundary, with the highest percentage of change in Texas and southern Florida. Several confounding factors such as sea level rise, absence or presence of sub-freezing temperatures, land use change, impoundment/dredging, changing hydrology, fire, storm, sedimentation and erosion, and mangrove planting are responsible for the change. Besides, sea level rise, relatively milder winters and the absence of sub-freezing temperatures in recent decades may be enabling the expansion locally. The results highlight the complex set of forcings acting on the northerly extent of mangroves and emphasize the need for long-term monitoring as this system increases in importance as a means to adapt to rising oceans and mitigate the effects of increased atmospheric CO2. Full article
(This article belongs to the Section Remote Sensors)
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Open AccessArticle Anatomical Calibration through Post-Processing of Standard Motion Tests Data
Sensors 2016, 16(12), 2011; doi:10.3390/s16122011
Received: 3 October 2016 / Revised: 21 November 2016 / Accepted: 23 November 2016 / Published: 28 November 2016
PDF Full-text (6536 KB) | HTML Full-text | XML Full-text
Abstract
The inertial measurement unit is popularly used as a wearable and flexible tool for human motion tracking. Sensor-to-body alignment, or anatomical calibration (AC), is fundamental to improve accuracy and reliability. Current AC methods either require extra movements or are limited to specific joints.
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The inertial measurement unit is popularly used as a wearable and flexible tool for human motion tracking. Sensor-to-body alignment, or anatomical calibration (AC), is fundamental to improve accuracy and reliability. Current AC methods either require extra movements or are limited to specific joints. In this research, the authors propose a novel method to achieve AC from standard motion tests (such as walking, or sit-to-stand), and compare the results with the AC obtained from specially designed movements. The proposed method uses the limited acceleration range on medial-lateral direction, and applies principal component analysis to estimate the sagittal plane, while the vertical direction is estimated from acceleration during quiet stance. The results show a good correlation between the two sets of IMUs placed on frontal/back and lateral sides of head, trunk and lower limbs. Moreover, repeatability and convergence were verified. The AC obtained from sit-to-stand and walking achieved similar results as the movements specifically designed for upper and lower body AC, respectively, except for the feet. Therefore, the experiments without AC performed can be recovered through post-processing on the walking and sit-to-stand data. Moreover, extra movements for AC can be avoided during the experiment and instead achieved through the proposed method. Full article
(This article belongs to the Special Issue Inertial Sensors and Systems 2016)
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Open AccessArticle Potential of Wake-Up Radio-Based MAC Protocols for Implantable Body Sensor Networks (IBSN)—A Survey
Sensors 2016, 16(12), 2012; doi:10.3390/s16122012
Received: 19 October 2016 / Revised: 18 November 2016 / Accepted: 21 November 2016 / Published: 29 November 2016
PDF Full-text (673 KB) | HTML Full-text | XML Full-text
Abstract
With the advent of nano-technology, medical sensors and devices are becoming highly miniaturized. Consequently, the number of sensors and medical devices being implanted to accurately monitor and diagnose a disease is increasing. By measuring the symptoms and controlling a medical device as close
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With the advent of nano-technology, medical sensors and devices are becoming highly miniaturized. Consequently, the number of sensors and medical devices being implanted to accurately monitor and diagnose a disease is increasing. By measuring the symptoms and controlling a medical device as close as possible to the source, these implantable devices are able to save lives. A wireless link between medical sensors and implantable medical devices is essential in the case of closed-loop medical devices, in which symptoms of the diseases are monitored by sensors that are not placed in close proximity of the therapeutic device. Medium Access Control (MAC) is crucial to make it possible for several medical devices to communicate using a shared wireless medium in such a way that minimum delay, maximum throughput, and increased network life-time are guaranteed. To guarantee this Quality of Service (QoS), the MAC protocols control the main sources of limited resource wastage, namely the idle-listening, packet collisions, over-hearing, and packet loss. Traditional MAC protocols designed for body sensor networks are not directly applicable to Implantable Body Sensor Networks (IBSN) because of the dynamic nature of the radio channel within the human body and the strict QoS requirements of IBSN applications. Although numerous MAC protocols are available in the literature, the majority of them are designed for Body Sensor Network (BSN) and Wireless Sensor Network (WSN). To the best of our knowledge, there is so far no research paper that explores the impact of these MAC protocols specifically for IBSN. MAC protocols designed for implantable devices are still in their infancy and one of their most challenging objectives is to be ultra-low-power. One of the technological solutions to achieve this objective so is to integrate the concept of Wake-up radio (WuR) into the MAC design. In this survey, we present a taxonomy of MAC protocols based on their use of WuR technology and identify their bottlenecks to be used in IBSN applications. Furthermore, we present a number of open research challenges and requirements for designing an energy-efficient and reliable wireless communication protocol for IBSN. Full article
(This article belongs to the Special Issue Advances in Body Sensor Networks: Sensors, Systems, and Applications)
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Open AccessArticle Task and Participant Scheduling of Trading Platforms in Vehicular Participatory Sensing Networks
Sensors 2016, 16(12), 2013; doi:10.3390/s16122013
Received: 30 October 2016 / Revised: 23 November 2016 / Accepted: 23 November 2016 / Published: 28 November 2016
Cited by 1 | PDF Full-text (1323 KB) | HTML Full-text | XML Full-text
Abstract
The vehicular participatory sensing network (VPSN) is now becoming more and more prevalent, and additionally has shown its great potential in various applications. A general VPSN consists of many tasks from task, publishers, trading platforms and a crowd of participants. Some literature treats
[...] Read more.
The vehicular participatory sensing network (VPSN) is now becoming more and more prevalent, and additionally has shown its great potential in various applications. A general VPSN consists of many tasks from task, publishers, trading platforms and a crowd of participants. Some literature treats publishers and the trading platform as a whole, which is impractical since they are two independent economic entities with respective purposes. For a trading platform in markets, its purpose is to maximize the profit by selecting tasks and recruiting participants who satisfy the requirements of accepted tasks, rather than to improve the quality of each task. This scheduling problem for a trading platform consists of two parts: which tasks should be selected and which participants to be recruited? In this paper, we investigate the scheduling problem in vehicular participatory sensing with the predictable mobility of each vehicle. A genetic-based trading scheduling algorithm (GTSA) is proposed to solve the scheduling problem. Experiments with a realistic dataset of taxi trajectories demonstrate that GTSA algorithm is efficient for trading platforms to gain considerable profit in VPSN. Full article
(This article belongs to the Special Issue New Paradigms in Cyber-Physical Social Sensing)
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Open AccessArticle Measurement of M2-Curve for Asymmetric Beams by Self-Referencing Interferometer Wavefront Sensor
Sensors 2016, 16(12), 2014; doi:10.3390/s16122014
Received: 17 October 2016 / Revised: 15 November 2016 / Accepted: 23 November 2016 / Published: 29 November 2016
Cited by 1 | PDF Full-text (4706 KB) | HTML Full-text | XML Full-text
Abstract
For asymmetric laser beams, the values of beam quality factor Mx2 and My2 are inconsistent if one selects a different coordinate system or measures beam quality with different experimental conditionals, even when analyzing the same beam. To overcome this
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For asymmetric laser beams, the values of beam quality factor M x 2 and M y 2 are inconsistent if one selects a different coordinate system or measures beam quality with different experimental conditionals, even when analyzing the same beam. To overcome this non-uniqueness, a new beam quality characterization method named as M2-curve is developed. The M2-curve not only contains the beam quality factor M x 2 and M y 2 in the x-direction and y-direction, respectively; but also introduces a curve of M x α 2 versus rotation angle α of coordinate axis. Moreover, we also present a real-time measurement method to demonstrate beam propagation factor M2-curve with a modified self-referencing Mach-Zehnder interferometer based-wavefront sensor (henceforth SRI-WFS). The feasibility of the proposed method is demonstrated with the theoretical analysis and experiment in multimode beams. The experimental results showed that the proposed measurement method is simple, fast, and a single-shot measurement procedure without movable parts. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle Localization Based on Magnetic Markers for an All-Wheel Steering Vehicle
Sensors 2016, 16(12), 2015; doi:10.3390/s16122015
Received: 11 October 2016 / Revised: 23 November 2016 / Accepted: 24 November 2016 / Published: 29 November 2016
PDF Full-text (5989 KB) | HTML Full-text | XML Full-text
Abstract
Real-time continuous localization is a key technology in the development of intelligent transportation systems. In these systems, it is very important to have accurate information about the position and heading angle of the vehicle at all times. The most widely implemented methods for
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Real-time continuous localization is a key technology in the development of intelligent transportation systems. In these systems, it is very important to have accurate information about the position and heading angle of the vehicle at all times. The most widely implemented methods for positioning are the global positioning system (GPS), vision-based system, and magnetic marker system. Among these methods, the magnetic marker system is less vulnerable to indoor and outdoor environment conditions; moreover, it requires minimal maintenance expenses. In this paper, we present a position estimation scheme based on magnetic markers and odometry sensors for an all-wheel-steering vehicle. The heading angle of the vehicle is determined by using the position coordinates of the last two detected magnetic markers and odometer data. The instant position and heading angle of the vehicle are integrated with an extended Kalman filter to estimate the continuous position. GPS data with the real-time kinematics mode was obtained to evaluate the performance of the proposed position estimation system. The test results show that the performance of the proposed localization algorithm is accurate (mean error: 3 cm; max error: 9 cm) and reliable under unexpected missing markers or incorrect markers. Full article
(This article belongs to the Special Issue Sensors for Autonomous Road Vehicles)
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Open AccessArticle Optimal Resource Allocation Policies for Multi-User Backscatter Communication Systems
Sensors 2016, 16(12), 2016; doi:10.3390/s16122016
Received: 26 October 2016 / Revised: 23 November 2016 / Accepted: 24 November 2016 / Published: 29 November 2016
Cited by 5 | PDF Full-text (386 KB) | HTML Full-text | XML Full-text
Abstract
This paper considers a backscatter communication (BackCom) system including a reader and N tags, where each tag receives excitation signals transmitted by the reader and concurrently backscatters information to the reader in time-division-multiple-access (TDMA) mode. In this system, we aim to maximize the
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This paper considers a backscatter communication (BackCom) system including a reader and N tags, where each tag receives excitation signals transmitted by the reader and concurrently backscatters information to the reader in time-division-multiple-access (TDMA) mode. In this system, we aim to maximize the total system goodput by jointly optimizing reader transmission power, time allocation, and reflection ratio for the cases of passive and semi-passive tags. For each case, an optimization problem is formulated, which is non-convex and can be solved by being decomposed into at most N feasible sub-problems based on the priority of allocated reader transmission power. First, for the passive tags case, by solving the convex sub-problems sequentially and comparing their maximum total goodput, we derive the optimal resource allocation policy. Then, for the semi-passive tags case, we find a close-to-optimal solution, since each sub-problem can be reformulated as a biconvex problem, which is solved by a proposed block coordinate descent (BCD)-based optimization algorithm. Finally, simulation results demonstrate the superiority of the proposed resource allocation policies. Full article
(This article belongs to the Special Issue New Paradigms in Cyber-Physical Social Sensing)
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Open AccessArticle MEMS IMU Error Mitigation Using Rotation Modulation Technique
Sensors 2016, 16(12), 2017; doi:10.3390/s16122017
Received: 6 August 2016 / Revised: 26 October 2016 / Accepted: 28 October 2016 / Published: 29 November 2016
Cited by 2 | PDF Full-text (2249 KB) | HTML Full-text | XML Full-text
Abstract
Micro-electro-mechanical-systems (MEMS) inertial measurement unit (IMU) outputs are corrupted by significant sensor errors. The navigation errors of a MEMS-based inertial navigation system will therefore accumulate very quickly over time. This requires aiding from other sensors such as Global Navigation Satellite Systems (GNSS). However,
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Micro-electro-mechanical-systems (MEMS) inertial measurement unit (IMU) outputs are corrupted by significant sensor errors. The navigation errors of a MEMS-based inertial navigation system will therefore accumulate very quickly over time. This requires aiding from other sensors such as Global Navigation Satellite Systems (GNSS). However, it will still remain a significant challenge in the presence of GNSS outages, which are typically in urban canopies. This paper proposed a rotary inertial navigation system (INS) to mitigate navigation errors caused by MEMS inertial sensor errors when external aiding information is not available. A rotary INS is an inertial navigator in which the IMU is installed on a rotation platform. Application of proper rotation schemes can effectively cancel and reduce sensor errors. A rotary INS has the potential to significantly increase the time period that INS can bridge GNSS outages and make MEMS IMU possible to maintain longer autonomous navigation performance when there is no external aiding. In this research, several IMU rotation schemes (rotation about X-, Y- and Z-axes) are analyzed to mitigate the navigation errors caused by MEMS IMU sensor errors. As the IMU rotation induces additional sensor errors, a calibration process is proposed to remove the induced errors. Tests are further conducted with two MEMS IMUs installed on a tri-axial rotation table to verify the error mitigation by IMU rotations. Full article
(This article belongs to the Special Issue Inertial Sensors and Systems 2016)
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Open AccessArticle A Pilot Study of Individual Muscle Force Prediction during Elbow Flexion and Extension in the Neurorehabilitation Field
Sensors 2016, 16(12), 2018; doi:10.3390/s16122018
Received: 11 October 2016 / Revised: 17 November 2016 / Accepted: 25 November 2016 / Published: 29 November 2016
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Abstract
This paper proposes a neuromusculoskeletal (NMS) model to predict individual muscle force during elbow flexion and extension. Four male subjects were asked to do voluntary elbow flexion and extension. An inertial sensor and surface electromyography (sEMG) sensors were attached to subject's forearm. Joint
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This paper proposes a neuromusculoskeletal (NMS) model to predict individual muscle force during elbow flexion and extension. Four male subjects were asked to do voluntary elbow flexion and extension. An inertial sensor and surface electromyography (sEMG) sensors were attached to subject's forearm. Joint angle calculated by fusion of acceleration and angular rate using an extended Kalman filter (EKF) and muscle activations obtained from the sEMG signals were taken as the inputs of the proposed NMS model to determine individual muscle force. The result shows that our NMS model can predict individual muscle force accurately, with the ability to reflect subject-specific joint dynamics and neural control solutions. Our method incorporates sEMG and motion data, making it possible to get a deeper understanding of neurological, physiological, and anatomical characteristics of human dynamic movement. We demonstrate the potential of the proposed NMS model for evaluating the function of upper limb movements in the field of neurorehabilitation. Full article
(This article belongs to the Special Issue Sensors and Analytics for Precision Medicine)
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Open AccessArticle A Novel Gravity Compensation Method for High Precision Free-INS Based on “Extreme Learning Machine”
Sensors 2016, 16(12), 2019; doi:10.3390/s16122019
Received: 18 June 2016 / Revised: 18 November 2016 / Accepted: 22 November 2016 / Published: 29 November 2016
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Abstract
In recent years, with the emergency of high precision inertial sensors (accelerometers and gyros), gravity compensation has become a major source influencing the navigation accuracy in inertial navigation systems (INS), especially for high-precision INS. This paper presents preliminary results concerning the effect of
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In recent years, with the emergency of high precision inertial sensors (accelerometers and gyros), gravity compensation has become a major source influencing the navigation accuracy in inertial navigation systems (INS), especially for high-precision INS. This paper presents preliminary results concerning the effect of gravity disturbance on INS. Meanwhile, this paper proposes a novel gravity compensation method for high-precision INS, which estimates the gravity disturbance on the track using the extreme learning machine (ELM) method based on measured gravity data on the geoid and processes the gravity disturbance to the height where INS has an upward continuation, then compensates the obtained gravity disturbance into the error equations of INS to restrain the INS error propagation. The estimation accuracy of the gravity disturbance data is verified by numerical tests. The root mean square error (RMSE) of the ELM estimation method can be improved by 23% and 44% compared with the bilinear interpolation method in plain and mountain areas, respectively. To further validate the proposed gravity compensation method, field experiments with an experimental vehicle were carried out in two regions. Test 1 was carried out in a plain area and Test 2 in a mountain area. The field experiment results also prove that the proposed gravity compensation method can significantly improve the positioning accuracy. During the 2-h field experiments, the positioning accuracy can be improved by 13% and 29% respectively, in Tests 1 and 2, when the navigation scheme is compensated by the proposed gravity compensation method. Full article
(This article belongs to the Special Issue Inertial Sensors and Systems 2016)
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Open AccessArticle Three-Dimensional Continuous Displacement Measurement with Temporal Speckle Pattern Interferometry
Sensors 2016, 16(12), 2020; doi:10.3390/s16122020
Received: 18 September 2016 / Revised: 24 November 2016 / Accepted: 24 November 2016 / Published: 29 November 2016
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Abstract
A speckle interferometer which can measure whole field three-dimensional displacements continuously and dynamically has been built. Three different wavelength lasers are used to produce the speckle interferograms of the two in-plane displacements (displacements in the x- and y-direction) and one out-of-plane
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A speckle interferometer which can measure whole field three-dimensional displacements continuously and dynamically has been built. Three different wavelength lasers are used to produce the speckle interferograms of the two in-plane displacements (displacements in the x- and y-direction) and one out-of-plane displacement (displacement in the z-direction), respectively. One color CCD camera is employed to collect these mixed speckle interferograms simultaneously. The mixed interferograms are separated by the Red, Green and Blue channels of the color CCD camera, and then are processed by the wavelet transform technique to extract the phase information of the measured object. The preliminary experiment is carried out to demonstrate the performance of this new device. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle Market Model for Resource Allocation in Emerging Sensor Networks with Reinforcement Learning
Sensors 2016, 16(12), 2021; doi:10.3390/s16122021
Received: 29 September 2016 / Revised: 16 November 2016 / Accepted: 24 November 2016 / Published: 29 November 2016
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Abstract
Emerging sensor networks (ESNs) are an inevitable trend with the development of the Internet of Things (IoT), and intend to connect almost every intelligent device. Therefore, it is critical to study resource allocation in such an environment, due to the concern of efficiency,
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Emerging sensor networks (ESNs) are an inevitable trend with the development of the Internet of Things (IoT), and intend to connect almost every intelligent device. Therefore, it is critical to study resource allocation in such an environment, due to the concern of efficiency, especially when resources are limited. By viewing ESNs as multi-agent environments, we model them with an agent-based modelling (ABM) method and deal with resource allocation problems with market models, after describing users’ patterns. Reinforcement learning methods are introduced to estimate users’ patterns and verify the outcomes in our market models. Experimental results show the efficiency of our methods, which are also capable of guiding topology management. Full article
(This article belongs to the Special Issue Topology Control in Emerging Sensor Networks)
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Open AccessArticle Error Analysis and Experimental Study of a Bi-Planar Parallel Mechanism in a Pedicle Screw Robot System
Sensors 2016, 16(12), 2022; doi:10.3390/s16122022
Received: 30 June 2016 / Revised: 21 November 2016 / Accepted: 21 November 2016 / Published: 30 November 2016
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Abstract
Due to the urgent need for high precision surgical equipment for minimally invasive spinal surgery, a novel robot-assistant system was developed for the accurate placement of pedicle screws in lumbar spinal surgeries. The structure of the robot was based on a macro-micro mechanism,
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Due to the urgent need for high precision surgical equipment for minimally invasive spinal surgery, a novel robot-assistant system was developed for the accurate placement of pedicle screws in lumbar spinal surgeries. The structure of the robot was based on a macro-micro mechanism, which includes a serial mechanism (macro part) and a bi-planar 5R parallel mechanism (micro part). The macro part was used to achieve a large workspace, while the micro part was used to obtain high stiffness and accuracy. Based on the transfer function of dimension errors, the factors affecting the accuracy of the end effectors were analyzed. Then the manufacturing errors and joint angle error on the position-stance of the end effectors were investigated. Eventually, the mechanism of the strain energy produced by the deformation of linkage via forced assembly and displacements of the output point were calculated. The amount of the transfer errors was quantitatively analyzed by the simulation. Experimental tests show that the error of the bi-planar 5R mechanism can be controlled no more than 1 mm for translation and 1° for rotation, which satisfies the required absolute position accuracy of the robot. Full article
(This article belongs to the Special Issue Advanced Robotics and Mechatronics Devices)
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Open AccessArticle One-Step Fabrication of Microchannels with Integrated Three Dimensional Features by Hot Intrusion Embossing
Sensors 2016, 16(12), 2023; doi:10.3390/s16122023
Received: 23 September 2016 / Revised: 15 November 2016 / Accepted: 22 November 2016 / Published: 29 November 2016
Cited by 2 | PDF Full-text (3471 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
We build on the concept of hot intrusion embossing to develop a one-step fabrication method for thermoplastic microfluidic channels containing integrated three-dimensional features. This was accomplished with simple, rapid-to-fabricate imprint templates containing microcavities that locally control the intrusion of heated thermoplastic based on
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We build on the concept of hot intrusion embossing to develop a one-step fabrication method for thermoplastic microfluidic channels containing integrated three-dimensional features. This was accomplished with simple, rapid-to-fabricate imprint templates containing microcavities that locally control the intrusion of heated thermoplastic based on their cross-sectional geometries. The use of circular, rectangular and triangular cavity geometries was demonstrated for the purposes of forming posts, multi-focal length microlense arrays, walls, steps, tapered features and three-dimensional serpentine microchannels. Process variables, such as temperature and pressure, controlled feature dimensions without affecting the overall microchannel geometry. The approach was demonstrated for polycarbonate, cycloolefin copolymer and polystyrene, but in principle is applicable to any thermoplastic. The approach is a step forward towards rapid fabrication of complex, robust, microfluidic platforms with integrated multi-functional elements. Full article
(This article belongs to the Special Issue Microfluidics-Based Microsystem Integration Research)
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Open AccessArticle SAW Humidity Sensor Sensitivity Enhancement via Electrospraying of Silver Nanowires
Sensors 2016, 16(12), 2024; doi:10.3390/s16122024
Received: 9 September 2016 / Revised: 23 November 2016 / Accepted: 25 November 2016 / Published: 30 November 2016
Cited by 4 | PDF Full-text (3845 KB) | HTML Full-text | XML Full-text
Abstract
In this research, we investigated the influence of the surface coatings of silver nanowires on the sensitivity of surface acoustic wave (SAW) humidity sensors. Silver nanowires, with poly(vinylpyrrolidone) (PVP), which is a hydrophilic capping agent, were chemically synthesized, with an average length of
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In this research, we investigated the influence of the surface coatings of silver nanowires on the sensitivity of surface acoustic wave (SAW) humidity sensors. Silver nanowires, with poly(vinylpyrrolidone) (PVP), which is a hydrophilic capping agent, were chemically synthesized, with an average length of 15 µm and an average diameter of 60 nm. Humidity sensors, with 433 MHz frequency dual-port resonator Rayleigh-SAW devices, were coated by silver nanowires (AgNWs) using the electrospray coating method. It was demonstrated that increasing thickness of coated AgNW on the surfaces of SAW devices results in increased sensitivity. The highest frequency shift (262 kHz) in these SAW devices was obtained with an injection of 0.5 mL of the AgNW solution with a concentration of 0.5 mg/mL at an injection rate of 1 mL/h. It also showed the highest humidity sensitivity among the other prepared SAW devices. Full article
(This article belongs to the Special Issue Gas Nanosensors)
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Open AccessArticle Short-Range Vital Signs Sensing Based on EEMD and CWT Using IR-UWB Radar
Sensors 2016, 16(12), 2025; doi:10.3390/s16122025
Received: 9 August 2016 / Revised: 10 November 2016 / Accepted: 24 November 2016 / Published: 30 November 2016
Cited by 4 | PDF Full-text (6081 KB) | HTML Full-text | XML Full-text
Abstract
The radar sensor described realizes healthcare monitoring capable of detecting subject chest-wall movement caused by cardiopulmonary activities and wirelessly estimating the respiration and heartbeat rates of the subject without attaching any devices to the body. Conventional single-tone Doppler radar can only capture Doppler
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The radar sensor described realizes healthcare monitoring capable of detecting subject chest-wall movement caused by cardiopulmonary activities and wirelessly estimating the respiration and heartbeat rates of the subject without attaching any devices to the body. Conventional single-tone Doppler radar can only capture Doppler signatures because of a lack of bandwidth information with noncontact sensors. In contrast, we take full advantage of impulse radio ultra-wideband (IR-UWB) radar to achieve low power consumption and convenient portability, with a flexible detection range and desirable accuracy. A noise reduction method based on improved ensemble empirical mode decomposition (EEMD) and a vital sign separation method based on the continuous-wavelet transform (CWT) are proposed jointly to improve the signal-to-noise ratio (SNR) in order to acquire accurate respiration and heartbeat rates. Experimental results illustrate that respiration and heartbeat signals can be extracted accurately under different conditions. This noncontact healthcare sensor system proves the commercial feasibility and considerable accessibility of using compact IR-UWB radar for emerging biomedical applications. Full article
(This article belongs to the Special Issue Sensing Technology for Healthcare System)
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Open AccessArticle A Fiber-Optic Sensor for Acoustic Emission Detection in a High Voltage Cable System
Sensors 2016, 16(12), 2026; doi:10.3390/s16122026
Received: 23 September 2016 / Revised: 20 November 2016 / Accepted: 25 November 2016 / Published: 30 November 2016
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Abstract
We have proposed and demonstrated a Michelson interferometer-based fiber sensor for detecting acoustic emission generated from the partial discharge (PD) of the accessories of a high-voltage cable system. The developed sensor head is integrated with a compact and relatively high sensitivity cylindrical elastomer.
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We have proposed and demonstrated a Michelson interferometer-based fiber sensor for detecting acoustic emission generated from the partial discharge (PD) of the accessories of a high-voltage cable system. The developed sensor head is integrated with a compact and relatively high sensitivity cylindrical elastomer. Such a sensor has a broadband frequency response and a relatively high sensitivity in a harsh environment under a high-voltage electric field. The design and fabrication of the sensor head integrated with the cylindrical elastomer is described, and a series of experiments was conducted to evaluate the sensing performance. The experimental results demonstrate that the sensitivity of our developed sensor for acoustic detection of partial discharges is 1.7 rad / ( m Pa ) . A high frequency response up to 150 kHz is achieved. Moreover, the relatively high sensitivity for the detection of PD is verified in both the laboratory environment and gas insulated switchgear. The obtained results show the great potential application of a Michelson interferometer-based fiber sensor integrated with a cylindrical elastomer for in-situ monitoring high-voltage cable accessories for safety work. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle A Multi-Pumping Flow System for In Situ Measurements of Dissolved Manganese in Aquatic Systems
Sensors 2016, 16(12), 2027; doi:10.3390/s16122027
Received: 22 September 2016 / Revised: 21 November 2016 / Accepted: 23 November 2016 / Published: 30 November 2016
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Abstract
A METals In Situ analyzer (METIS) has been used to determine dissolved manganese (II) concentrations in the subhalocline waters of the Gotland Deep (central Baltic Sea). High-resolution in situ measurements of total dissolved Mn were obtained in near real-time by spectrophotometry using 1-(2-pyridylazo)-2-naphthol
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A METals In Situ analyzer (METIS) has been used to determine dissolved manganese (II) concentrations in the subhalocline waters of the Gotland Deep (central Baltic Sea). High-resolution in situ measurements of total dissolved Mn were obtained in near real-time by spectrophotometry using 1-(2-pyridylazo)-2-naphthol (PAN). PAN is a complexing agent of dissolved Mn and forms a wine-red complex with a maximum absorbance at a wavelength of 562 nm. Results are presented together with ancillary temperature, salinity, and dissolved O 2 data. Lab calibration of the analyzer was performed in a pressure testing tank. A detection limit of 77 nM was obtained. For validation purposes, discrete water samples were taken by using a pump-CTD system. Dissolved Mn in these samples was determined by an independent laboratory based method (inductively coupled plasma–optical emission spectrometry, ICP-OES). Mn measurements from both METIS and ICP-OES analysis were in good agreement. The results showed that the in situ analysis of dissolved Mn is a powerful technique reducing dependencies on heavy and expensive equipment (pump-CTD system, ICP-OES) and is also cost and time effective. Full article
(This article belongs to the Special Issue Colorimetric and Fluorescent Sensor)
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Open AccessArticle Uniformly Porous Nanocrystalline CaMgFe1.33Ti3O12 Ceramic Derived Electro-Ceramic Nanocomposite for Impedance Type Humidity Sensor
Sensors 2016, 16(12), 2029; doi:10.3390/s16122029
Received: 23 August 2016 / Revised: 5 October 2016 / Accepted: 10 October 2016 / Published: 30 November 2016
Cited by 2 | PDF Full-text (4857 KB) | HTML Full-text | XML Full-text
Abstract
Since humidity sensors have been widely used in many sectors, a suitable humidity sensing material with improved sensitivity, faster response and recovery times, better stability and low hysteresis is necessary to be developed. Here, we fabricate a uniformly porous humidity sensor using Ca,
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Since humidity sensors have been widely used in many sectors, a suitable humidity sensing material with improved sensitivity, faster response and recovery times, better stability and low hysteresis is necessary to be developed. Here, we fabricate a uniformly porous humidity sensor using Ca, Ti substituted Mg ferrites with chemical formula of CaMgFe1.33Ti3O12 as humidity sensing materials by solid-sate step-sintering technique. This synthesis technique is useful to control the grain size with increased porosity to enhance the hydrophilic characteristics of the CaMgFe1.33Ti3O12 nanoceramic based sintered electro-ceramic nanocomposites. The highest porosity, lowest density and excellent surface-hydrophilicity properties were obtained at 1050 °C sintered ceramic. The performance of this impedance type humidity sensor was evaluated by electrical characterizations using alternating current (AC) in the 33%–95% relative humidity (RH) range at 25 °C. Compared with existing conventional resistive humidity sensors, the present sintered electro-ceramic nanocomposite based humidity sensor showed faster response time (20 s) and recovery time (40 s). This newly developed sensor showed extremely high sensitivity (%S) and small hysteresis of <3.4%. Long-term stability of the sensor had been determined by testing for 30 consecutive days. Therefore, the high performance sensing behavior of the present electro-ceramic nanocomposites would be suitable for a potential use in advanced humidity sensors. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle A Context-Recognition-Aided PDR Localization Method Based on the Hidden Markov Model
Sensors 2016, 16(12), 2030; doi:10.3390/s16122030
Received: 17 August 2016 / Revised: 18 November 2016 / Accepted: 22 November 2016 / Published: 30 November 2016
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Abstract
Indoor positioning has recently become an important field of interest because global navigation satellite systems (GNSS) are usually unavailable in indoor environments. Pedestrian dead reckoning (PDR) is a promising localization technique for indoor environments since it can be implemented on widely used smartphones
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Indoor positioning has recently become an important field of interest because global navigation satellite systems (GNSS) are usually unavailable in indoor environments. Pedestrian dead reckoning (PDR) is a promising localization technique for indoor environments since it can be implemented on widely used smartphones equipped with low cost inertial sensors. However, the PDR localization severely suffers from the accumulation of positioning errors, and other external calibration sources should be used. In this paper, a context-recognition-aided PDR localization model is proposed to calibrate PDR. The context is detected by employing particular human actions or characteristic objects and it is matched to the context pre-stored offline in the database to get the pedestrian’s location. The Hidden Markov Model (HMM) and Recursive Viterbi Algorithm are used to do the matching, which reduces the time complexity and saves the storage. In addition, the authors design the turn detection algorithm and take the context of corner as an example to illustrate and verify the proposed model. The experimental results show that the proposed localization method can fix the pedestrian’s starting point quickly and improves the positioning accuracy of PDR by 40.56% at most with perfect stability and robustness at the same time. Full article
(This article belongs to the Special Issue Scalable Localization in Wireless Sensor Networks)
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Open AccessArticle Evaluation of a Tracking System for Patients and Mixed Intravenous Medication Based on RFID Technology
Sensors 2016, 16(12), 2031; doi:10.3390/s16122031
Received: 7 September 2016 / Revised: 31 October 2016 / Accepted: 28 November 2016 / Published: 30 November 2016
Cited by 4 | PDF Full-text (1202 KB) | HTML Full-text | XML Full-text
Abstract
At present, one of the primary concerns of healthcare professionals is how to increase the safety and quality of the care that patients receive during their stay in hospital. This is particularly important in the administration of expensive and high-risk medicines with which
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At present, one of the primary concerns of healthcare professionals is how to increase the safety and quality of the care that patients receive during their stay in hospital. This is particularly important in the administration of expensive and high-risk medicines with which it is fundamental to minimize the possibility of adverse events in the process of prescription-validation-preparation/dosage-dispensation-administration of intravenous mixes. This work is a detailed analysis of the evaluation, carried out by the health personnel involved in the Radiofrequency Identification (RFID) system developed in the Day Hospital and Pharmacy services of the Complejo Hospitalario Universitario A Coruña (CHUAC). The RFID system is evaluated by analyzing surveys completed by said health personnel, since their questions represent the key indicators of the patient care process (safety, cost, adequacy with the clinical practice). This work allows us to conclude, among other things, that the system tracks the patients satisfactorily and that its cost, though high, is justified in the context of the project context (use of dangerous and costly medication). Full article
(This article belongs to the Special Issue Selected Papers from UCAmI, IWAAL and AmIHEALTH 2015)
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Open AccessArticle A Routing Protocol for Multisink Wireless Sensor Networks in Underground Coalmine Tunnels
Sensors 2016, 16(12), 2032; doi:10.3390/s16122032
Received: 23 August 2016 / Revised: 12 November 2016 / Accepted: 24 November 2016 / Published: 30 November 2016
Cited by 2 | PDF Full-text (3048 KB) | HTML Full-text | XML Full-text
Abstract
Traditional underground coalmine monitoring systems are mainly based on the use of wired transmission. However, when cables are damaged during an accident, it is difficult to obtain relevant data on environmental parameters and the emergency situation underground. To address this problem, the use
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Traditional underground coalmine monitoring systems are mainly based on the use of wired transmission. However, when cables are damaged during an accident, it is difficult to obtain relevant data on environmental parameters and the emergency situation underground. To address this problem, the use of wireless sensor networks (WSNs) has been proposed. However, the shape of coalmine tunnels is not conducive to the deployment of WSNs as they are long and narrow. Therefore, issues with the network arise, such as extremely large energy consumption, very weak connectivity, long time delays, and a short lifetime. To solve these problems, in this study, a new routing protocol algorithm for multisink WSNs based on transmission power control is proposed. First, a transmission power control algorithm is used to negotiate the optimal communication radius and transmission power of each sink. Second, the non-uniform clustering idea is adopted to optimize the cluster head selection. Simulation results are subsequently compared to the Centroid of the Nodes in a Partition (CNP) strategy and show that the new algorithm delivers a good performance: power efficiency is increased by approximately 70%, connectivity is increased by approximately 15%, the cluster interference is diminished by approximately 50%, the network lifetime is increased by approximately 6%, and the delay is reduced with an increase in the number of sinks. Full article
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Open AccessCommunication Label-Free Detection of Human Glycoprotein (CgA) Using an Extended-Gated Organic Transistor-Based Immunosensor
Sensors 2016, 16(12), 2033; doi:10.3390/s16122033
Received: 30 September 2016 / Revised: 26 November 2016 / Accepted: 28 November 2016 / Published: 30 November 2016
Cited by 3 | PDF Full-text (1481 KB) | HTML Full-text | XML Full-text
Abstract
Herein, we report on the fabrication of an extended-gated organic field-effect transistor (OFET)-based immunosensor and its application in the detection of human chromogranin A (hCgA). The fabricated OFET device possesses an extended-gate electrode immobilized with an anti-CgA antibody. The titration results of hCgA
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Herein, we report on the fabrication of an extended-gated organic field-effect transistor (OFET)-based immunosensor and its application in the detection of human chromogranin A (hCgA). The fabricated OFET device possesses an extended-gate electrode immobilized with an anti-CgA antibody. The titration results of hCgA showed that the electrical changes in the OFET characteristics corresponded to the glycoprotein recognition ability of the monoclonal antibody (anti-CgA). The observed sensitivity (detection limit: 0.11 µg/mL) and selectivity indicate that the OFET-based immunosensor can be potentially applied to the rapid detection of the glycoprotein concentration without any labeling. Full article
(This article belongs to the Special Issue Sensors for Glycoproteins and Glycated Proteins)
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Open AccessArticle A Multipurpose CMOS Platform for Nanosensing
Sensors 2016, 16(12), 2034; doi:10.3390/s16122034
Received: 23 September 2016 / Revised: 17 November 2016 / Accepted: 23 November 2016 / Published: 30 November 2016
PDF Full-text (12026 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
This paper presents a customizable sensing system based on functionalized nanowires (NWs) assembled onto complementary metal oxide semiconductor (CMOS) technology. The Micro-for-Nano (M4N) chip integrates on top of the electronics an array of aluminum microelectrodes covered with gold by means of a customized
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This paper presents a customizable sensing system based on functionalized nanowires (NWs) assembled onto complementary metal oxide semiconductor (CMOS) technology. The Micro-for-Nano (M4N) chip integrates on top of the electronics an array of aluminum microelectrodes covered with gold by means of a customized electroless plating process. The NW assembly process is driven by an array of on-chip dielectrophoresis (DEP) generators, enabling a custom layout of different nanosensors on the same microelectrode array. The electrical properties of each assembled NW are singularly sensed through an in situ CMOS read-out circuit (ROC) that guarantees a low noise and reliable measurement. The M4N chip is directly connected to an external microcontroller for configuration and data processing. The processed data are then redirected to a workstation for real-time data visualization and storage during sensing experiments. As proof of concept, ZnO nanowires have been integrated onto the M4N chip to validate the approach that enables different kind of sensing experiments. The device has been then irradiated by an external UV source with adjustable power to measure the ZnO sensitivity to UV-light exposure. A maximum variation of about 80% of the ZnO-NW resistance has been detected by the M4N system when the assembled 5 μ m × 500 nm single ZnO-NW is exposed to an estimated incident radiant UV-light flux in the range of 1 nW–229 nW. The performed experiments prove the efficiency of the platform conceived for exploiting any kind of material that can change its capacitance and/or resistance due to an external stimulus. Full article
(This article belongs to the Special Issue System-Integrated Intelligence and Intelligent Systems)
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Open AccessArticle Neuron Stimulation Device Integrated with Silicon Nanowire-Based Photodetection Circuit on a Flexible Substrate
Sensors 2016, 16(12), 2035; doi:10.3390/s16122035
Received: 7 September 2016 / Revised: 7 November 2016 / Accepted: 25 November 2016 / Published: 1 December 2016
Cited by 1 | PDF Full-text (9434 KB) | HTML Full-text | XML Full-text
Abstract
This paper proposes a neural stimulation device integrated with a silicon nanowire (SiNW)-based photodetection circuit for the activation of neurons with light. The proposed device is comprised of a voltage divider and a current driver in which SiNWs are used as photodetector and
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This paper proposes a neural stimulation device integrated with a silicon nanowire (SiNW)-based photodetection circuit for the activation of neurons with light. The proposed device is comprised of a voltage divider and a current driver in which SiNWs are used as photodetector and field-effect transistors; it has the functions of detecting light, generating a stimulation signal in proportion to the light intensity, and transmitting the signal to a micro electrode. To show the applicability of the proposed neural stimulation device as a high-resolution retinal prosthesis system, a high-density neural stimulation device with a unit cell size of 110 × 110 μ m and a resolution of 32 × 32 was fabricated on a flexible film with a thickness of approximately 50 μm. Its effectiveness as a retinal stimulation device was then evaluated using a unit cell in an in vitro animal experiment involving the retinal tissue of retinal Degeneration 1 (rd1) mice. Experiments wherein stimulation pulses were applied to the retinal tissues successfully demonstrate that the number of spikes in neural response signals increases in proportion to light intensity. Full article
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Open AccessArticle Trend-Residual Dual Modeling for Detection of Outliers in Low-Cost GPS Trajectories
Sensors 2016, 16(12), 2036; doi:10.3390/s16122036
Received: 19 September 2016 / Revised: 14 November 2016 / Accepted: 24 November 2016 / Published: 1 December 2016
PDF Full-text (5286 KB) | HTML Full-text | XML Full-text
Abstract
Low-cost GPS (receiver) has become a ubiquitous and integral part of our daily life. Despite noticeable advantages such as being cheap, small, light, and easy to use, its limited positioning accuracy devalues and hampers its wide applications for reliable mapping and analysis. Two
[...] Read more.
Low-cost GPS (receiver) has become a ubiquitous and integral part of our daily life. Despite noticeable advantages such as being cheap, small, light, and easy to use, its limited positioning accuracy devalues and hampers its wide applications for reliable mapping and analysis. Two conventional techniques to remove outliers in a GPS trajectory are thresholding and Kalman-based methods, which are difficult in selecting appropriate thresholds and modeling the trajectories. Moreover, they are insensitive to medium and small outliers, especially for low-sample-rate trajectories. This paper proposes a model-based GPS trajectory cleaner. Rather than examining speed and acceleration or assuming a pre-determined trajectory model, we first use cubic smooth spline to adaptively model the trend of the trajectory. The residuals, i.e., the differences between the trend and GPS measurements, are then further modeled by time series method. Outliers are detected by scoring the residuals at every GPS trajectory point. Comparing to the conventional procedures, the trend-residual dual modeling approach has the following features: (a) it is able to model trajectories and detect outliers adaptively; (b) only one critical value for outlier scores needs to be set; (c) it is able to robustly detect unapparent outliers; and (d) it is effective in cleaning outliers for GPS trajectories with low sample rates. Tests are carried out on three real-world GPS trajectories datasets. The evaluation demonstrates an average of 9.27 times better performance in outlier detection for GPS trajectories than thresholding and Kalman-based techniques. Full article
(This article belongs to the Section Remote Sensors)
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Open AccessArticle Dielectrically-Loaded Cylindrical Resonator-Based Wireless Passive High-Temperature Sensor
Sensors 2016, 16(12), 2037; doi:10.3390/s16122037
Received: 14 August 2016 / Revised: 18 November 2016 / Accepted: 24 November 2016 / Published: 1 December 2016
Cited by 2 | PDF Full-text (4337 KB) | HTML Full-text | XML Full-text
Abstract
The temperature sensor presented in this paper is based on a microwave dielectric resonator, which uses alumina ceramic as a substrate to survive in harsh environments. The resonant frequency of the resonator is determined by the relative permittivity of the alumina ceramic, which
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The temperature sensor presented in this paper is based on a microwave dielectric resonator, which uses alumina ceramic as a substrate to survive in harsh environments. The resonant frequency of the resonator is determined by the relative permittivity of the alumina ceramic, which monotonically changes with temperature. A rectangular aperture etched on the surface of the resonator works as both an incentive and a coupling device. A broadband slot antenna fed by a coplanar waveguide is utilized as an interrogation antenna to wirelessly detect the sensor signal using a radio-frequency backscattering technique. Theoretical analysis, software simulation, and experiments verified the feasibility of this temperature-sensing system. The sensor was tested in a metal-enclosed environment, which severely interferes with the extraction of the sensor signal. Therefore, frequency-domain compensation was introduced to filter the background noise and improve the signal-to-noise ratio of the sensor signal. The extracted peak frequency was found to monotonically shift from 2.441 to 2.291 GHz when the temperature was varied from 27 to 800 °C, leading to an average absolute sensitivity of 0.19 MHz/°C. Full article
(This article belongs to the Special Issue Resonator Sensors)
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Open AccessArticle A Framework to Implement IoT Network Performance Modelling Techniques for Network Solution Selection
Sensors 2016, 16(12), 2038; doi:10.3390/s16122038
Received: 29 July 2016 / Revised: 14 November 2016 / Accepted: 18 November 2016 / Published: 1 December 2016
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Abstract
No single network solution for Internet of Things (IoT) networks can provide the required level of Quality of Service (QoS) for all applications in all environments. This leads to an increasing number of solutions created to fit particular scenarios. Given the increasing number
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No single network solution for Internet of Things (IoT) networks can provide the required level of Quality of Service (QoS) for all applications in all environments. This leads to an increasing number of solutions created to fit particular scenarios. Given the increasing number and complexity of solutions available, it becomes difficult for an application developer to choose the solution which is best suited for an application. This article introduces a framework which autonomously chooses the best solution for the application given the current deployed environment. The framework utilises a performance model to predict the expected performance of a particular solution in a given environment. The framework can then choose an apt solution for the application from a set of available solutions. This article presents the framework with a set of models built using data collected from simulation. The modelling technique can determine with up to 85% accuracy the solution which performs the best for a particular performance metric given a set of solutions. The article highlights the fractured and disjointed practice currently in place for examining and comparing communication solutions and aims to open a discussion on harmonising testing procedures so that different solutions can be directly compared and offers a framework to achieve this within IoT networks. Full article
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Open AccessArticle Tunable Multiple-Step Plasmonic Bragg Reflectors with Graphene-Based Modulated Grating
Sensors 2016, 16(12), 2039; doi:10.3390/s16122039
Received: 17 October 2016 / Revised: 25 November 2016 / Accepted: 25 November 2016 / Published: 1 December 2016
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Abstract
We propose a novel plasmonic Bragg reflector (PBR) based on graphene with multiple-step silicon structure. The monolayer graphene bears locally variable optical properties by modulation of electric fields, and the periodical change of effective refractive index on graphene can be obtained by external
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We propose a novel plasmonic Bragg reflector (PBR) based on graphene with multiple-step silicon structure. The monolayer graphene bears locally variable optical properties by modulation of electric fields, and the periodical change of effective refractive index on graphene can be obtained by external bias voltage in the mid-infrared region. Through patterning the PBR units into multiple-step structures, we can decrease the insertion loss and suppress the rippling in transmission spectra. By introducing the defect into the multiple-step PBRs, the multiple resonance modes are formed inside the stopband by increasing the step number. This work may pave the ways for the further development of ultra-compact low-cost hyperspectral sensors in the mid-infrared region. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle Femtosecond Laser Ablated FBG with Composite Microstructure for Hydrogen Sensor Application
Sensors 2016, 16(12), 2040; doi:10.3390/s16122040
Received: 27 October 2016 / Revised: 25 November 2016 / Accepted: 29 November 2016 / Published: 1 December 2016
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Abstract
A composite microstructure in fiber Bragg grating (FBG) with film deposition for hydrogen detection is presented. Through ablated to FBG cladding by a femtosecond laser, straight-trenches and spiral micro-pits are formed. A Pd–Ag film is sputtered on the surface of the laser processed
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A composite microstructure in fiber Bragg grating (FBG) with film deposition for hydrogen detection is presented. Through ablated to FBG cladding by a femtosecond laser, straight-trenches and spiral micro-pits are formed. A Pd–Ag film is sputtered on the surface of the laser processed FBG single mode fiber, and acts as hydrogen sensing transducer. The demonstrated experimental outcomes show that a composite structure produced the highest sensitivity of 26.3 pm/%H, nearly sevenfold more sensitive compared with original standard FBG. It offers great potential in engineering applications for its good structure stability and sensitivity. Full article
(This article belongs to the Section Chemical Sensors)
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Open AccessArticle Manipulation and Immobilization of a Single Fluorescence Nanosensor for Selective Injection into Cells
Sensors 2016, 16(12), 2041; doi:10.3390/s16122041
Received: 9 October 2016 / Revised: 21 November 2016 / Accepted: 29 November 2016 / Published: 1 December 2016
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Abstract
Manipulation and injection of single nanosensors with high cell viability is an emerging field in cell analysis. We propose a new method using fluorescence nanosensors with a glass nanoprobe and optical control of the zeta potential. The nanosensor is fabricated by encapsulating a
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Manipulation and injection of single nanosensors with high cell viability is an emerging field in cell analysis. We propose a new method using fluorescence nanosensors with a glass nanoprobe and optical control of the zeta potential. The nanosensor is fabricated by encapsulating a fluorescence polystyrene nanobead into a lipid layer with 1,3,3-trimethylindolino-6′-nitrobenzopyrylospiran (SP), which is a photochromic material. The nanobead contains iron oxide nanoparticles and a temperature-sensitive fluorescent dye, Rhodamine B. The zeta potential of the nanosensor switches between negative and positive by photo-isomerization of SP with ultraviolet irradiation. The positively-charged nanosensor easily adheres to a negatively-charged glass nanoprobe, is transported to a target cell, and then adheres to the negatively-charged cell membrane. The nanosensor is then injected into the cytoplasm by heating with a near-infrared (NIR) laser. As a demonstration, a single 750 nm nanosensor was picked-up using a glass nanoprobe with optical control of the zeta potential. Then, the nanosensor was transported and immobilized onto a target cell membrane. Finally, it was injected into the cytoplasm using a NIR laser. The success rates of pick-up and cell immobilization of the nanosensor were 75% and 64%, respectively. Cell injection and cell survival rates were 80% and 100%, respectively. Full article
(This article belongs to the Section Chemical Sensors)
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Open AccessArticle Comparing ∆Tmax Determination Approaches for Granier-Based Sapflow Estimations
Sensors 2016, 16(12), 2042; doi:10.3390/s16122042
Received: 19 October 2016 / Revised: 22 November 2016 / Accepted: 28 November 2016 / Published: 1 December 2016
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Abstract
Granier-type thermal dissipation probes are common instruments for quantifying tree water use in forest hydrological studies. Estimating sapflow using Granier-type sapflow sensors requires determining the maximum temperature gradient (∆Tmax) between the heated probe and the reference probe below. ∆Tmax represents
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Granier-type thermal dissipation probes are common instruments for quantifying tree water use in forest hydrological studies. Estimating sapflow using Granier-type sapflow sensors requires determining the maximum temperature gradient (∆Tmax) between the heated probe and the reference probe below. ∆Tmax represents a state of zero sap flux, which was originally assumed to occur each night leading to a ∆Tmax determination on a daily basis. However, researchers have proven that, under certain conditions, sapflow may continue throughout the night. Therefore alternative approaches to determining ∆Tmax have been developed. Multiple ∆Tmax approaches are now in use; however, sapflow estimates remain imprecise because the empirical equation that transfers the raw temperature signal (∆T) to sap flux density (Fd) is strongly sensitive to ∆Tmax. In this study, we analyze the effects of different ∆Tmax determination approaches on sub-daily, daily and (intra-)seasonal Fd estimations. On this basis, we quantify the uncertainty of sapflow calculations, which is related to the raw signal processing. We show that the ∆Tmax determination procedure has a major influence on absolute ∆Tmax values and the respective sap flux density computations. Consequently, the choice of the ∆Tmax determination approach may be a significant source of uncertainty in sapflow estimations. Full article
(This article belongs to the Special Issue Sensors for Environmental Monitoring 2016)
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Open AccessArticle A Robust and Device-Free System for the Recognition and Classification of Elderly Activities
Sensors 2016, 16(12), 2043; doi:10.3390/s16122043
Received: 25 October 2016 / Revised: 25 November 2016 / Accepted: 29 November 2016 / Published: 1 December 2016
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Abstract
Human activity recognition, tracking and classification is an essential trend in assisted living systems that can help support elderly people with their daily activities. Traditional activity recognition approaches depend on vision-based or sensor-based techniques. Nowadays, a novel promising technique has obtained more attention,
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Human activity recognition, tracking and classification is an essential trend in assisted living systems that can help support elderly people with their daily activities. Traditional activity recognition approaches depend on vision-based or sensor-based techniques. Nowadays, a novel promising technique has obtained more attention, namely device-free human activity recognition that neither requires the target object to wear or carry a device nor install cameras in a perceived area. The device-free technique for activity recognition uses only the signals of common wireless local area network (WLAN) devices available everywhere. In this paper, we present a novel elderly activities recognition system by leveraging the fluctuation of the wireless signals caused by human motion. We present an efficient method to select the correct data from the Channel State Information (CSI) streams that were neglected in previous approaches. We apply a Principle Component Analysis method that exposes the useful information from raw CSI. Thereafter, Forest Decision (FD) is adopted to classify the proposed activities and has gained a high accuracy rate. Extensive experiments have been conducted in an indoor environment to test the feasibility of the proposed system with a total of five volunteer users. The evaluation shows that the proposed system is applicable and robust to electromagnetic noise. Full article
(This article belongs to the Special Issue New Paradigms in Cyber-Physical Social Sensing)
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Open AccessArticle Lightweight Sensor Authentication Scheme for Energy Efficiency in Ubiquitous Computing Environments
Sensors 2016, 16(12), 2044; doi:10.3390/s16122044
Received: 26 September 2016 / Revised: 27 November 2016 / Accepted: 28 November 2016 / Published: 1 December 2016
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Abstract
The Internet of Things (IoT) is the intelligent technologies and services that mutually communicate information between humans and devices or between Internet-based devices. In IoT environments, various device information is collected from the user for intelligent technologies and services that control the devices.
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The Internet of Things (IoT) is the intelligent technologies and services that mutually communicate information between humans and devices or between Internet-based devices. In IoT environments, various device information is collected from the user for intelligent technologies and services that control the devices. Recently, wireless sensor networks based on IoT environments are being used in sectors as diverse as medicine, the military, and commerce. Specifically, sensor techniques that collect relevant area data via mini-sensors after distributing smart dust in inaccessible areas like forests or military zones have been embraced as the future of information technology. IoT environments that utilize smart dust are composed of the sensor nodes that detect data using wireless sensors and transmit the detected data to middle nodes. Currently, since the sensors used in these environments are composed of mini-hardware, they have limited memory, processing power, and energy, and a variety of research that aims to make the best use of these limited resources is progressing. This paper proposes a method to utilize these resources while considering energy efficiency, and suggests lightweight mutual verification and key exchange methods based on a hash function that has no restrictions on operation quantity, velocity, and storage space. This study verifies the security and energy efficiency of this method through security analysis and function evaluation, comparing with existing approaches. The proposed method has great value in its applicability as a lightweight security technology for IoT environments. Full article
(This article belongs to the Special Issue Topology Control in Emerging Sensor Networks)
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Open AccessArticle Optimized Energy Harvesting, Cluster-Head Selection and Channel Allocation for IoTs in Smart Cities
Sensors 2016, 16(12), 2046; doi:10.3390/s16122046
Received: 18 August 2016 / Revised: 24 November 2016 / Accepted: 28 November 2016 / Published: 2 December 2016
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Abstract
This paper highlights three critical aspects of the internet of things (IoTs), namely (1) energy efficiency, (2) energy balancing and (3) quality of service (QoS) and presents three novel schemes for addressing these aspects. For energy efficiency, a novel radio frequency (RF) energy-harvesting
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This paper highlights three critical aspects of the internet of things (IoTs), namely (1) energy efficiency, (2) energy balancing and (3) quality of service (QoS) and presents three novel schemes for addressing these aspects. For energy efficiency, a novel radio frequency (RF) energy-harvesting scheme is presented in which each IoT device is associated with the best possible RF source in order to maximize the overall energy that the IoT devices harvest. For energy balancing, the IoT devices in close proximity are clustered together and then an IoT device with the highest residual energy is selected as a cluster head (CH) on a rotational basis. Once the CH is selected, it assigns channels to the IoT devices to report their data using a novel integer linear program (ILP)-based channel allocation scheme by satisfying their desired QoS. To evaluate the presented schemes, exhaustive simulations are carried out by varying different parameters, including the number of IoT devices, the number of harvesting sources, the distance between RF sources and IoT devices and the primary user (PU) activity of different channels. The simulation results demonstrate that our proposed schemes perform better than the existing ones. Full article
(This article belongs to the Special Issue Smart City: Vision and Reality)
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Open AccessArticle A Hyperspectral Survey of New York City Lighting Technology
Sensors 2016, 16(12), 2047; doi:10.3390/s16122047
Received: 26 September 2016 / Revised: 16 November 2016 / Accepted: 17 November 2016 / Published: 5 December 2016
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Abstract
Using side-facing observations of the New York City (NYC) skyline, we identify lighting technologies via spectral signatures measured with Visible and Near Infrared (VNIR) hyperspectral imaging. The instrument is a scanning, single slit spectrograph with 872 spectral channels from 0.4–1.0 μm. With
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Using side-facing observations of the New York City (NYC) skyline, we identify lighting technologies via spectral signatures measured with Visible and Near Infrared (VNIR) hyperspectral imaging. The instrument is a scanning, single slit spectrograph with 872 spectral channels from 0.4–1.0 μ m. With a single scan, we are able to clearly match the detected spectral signatures of 13 templates of known lighting types. However, many of the observed lighting spectra do not match those that have been measured in the laboratory. We identify unknown spectra by segmenting our observations and using Template-Activated Partition (TAP) clustering with a variety of underlying unsupervised clustering methods to generate the first empirically-determined spectral catalog of roughly 40 urban lighting types. We show that, given our vantage point, we are able to determine lighting technology use for both interior and exterior lighting. Finally, we find that the total brightness of our scene shows strong peaks at the 570 nm Na - II , 595 nm Na - II and 818 nm Na - I lines that are common in high pressure sodium lamps, which dominate our observations. Full article
(This article belongs to the Section Remote Sensors)
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Open AccessArticle Wearable Sensor-Based Human Activity Recognition Method with Multi-Features Extracted from Hilbert-Huang Transform
Sensors 2016, 16(12), 2048; doi:10.3390/s16122048
Received: 7 September 2016 / Revised: 17 November 2016 / Accepted: 21 November 2016 / Published: 2 December 2016
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Abstract
Wearable sensors-based human activity recognition introduces many useful applications and services in health care, rehabilitation training, elderly monitoring and many other areas of human interaction. Existing works in this field mainly focus on recognizing activities by using traditional features extracted from Fourier transform
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Wearable sensors-based human activity recognition introduces many useful applications and services in health care, rehabilitation training, elderly monitoring and many other areas of human interaction. Existing works in this field mainly focus on recognizing activities by using traditional features extracted from Fourier transform (FT) or wavelet transform (WT). However, these signal processing approaches are suitable for a linear signal but not for a nonlinear signal. In this paper, we investigate the characteristics of the Hilbert-Huang transform (HHT) for dealing with activity data with properties such as nonlinearity and non-stationarity. A multi-features extraction method based on HHT is then proposed to improve the effect of activity recognition. The extracted multi-features include instantaneous amplitude (IA) and instantaneous frequency (IF) by means of empirical mode decomposition (EMD), as well as instantaneous energy density (IE) and marginal spectrum (MS) derived from Hilbert spectral analysis. Experimental studies are performed to verify the proposed approach by using the PAMAP2 dataset from the University of California, Irvine for wearable sensors-based activity recognition. Moreover, the effect of combining multi-features vs. a single-feature are investigated and discussed in the scenario of a dependent subject. The experimental results show that multi-features combination can further improve the performance measures. Finally, we test the effect of multi-features combination in the scenario of an independent subject. Our experimental results show that we achieve four performance indexes: recall, precision, F-measure, and accuracy to 0.9337, 0.9417, 0.9353, and 0.9377 respectively, which are all better than the achievements of related works. Full article
(This article belongs to the Special Issue Body Worn Behavior Sensing)
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Open AccessCommunication A Touch Sensing Technique Using the Effects of Extremely Low Frequency Fields on the Human Body
Sensors 2016, 16(12), 2049; doi:10.3390/s16122049
Received: 17 August 2016 / Revised: 31 October 2016 / Accepted: 21 November 2016 / Published: 2 December 2016
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Abstract
Touch sensing is a fundamental approach in human-to-machine interfaces, and is currently under widespread use. Many current applications use active touch sensing technologies. Passive touch sensing technologies are, however, more adequate to implement low power or energy harvesting touch sensing interfaces. This paper
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Touch sensing is a fundamental approach in human-to-machine interfaces, and is currently under widespread use. Many current applications use active touch sensing technologies. Passive touch sensing technologies are, however, more adequate to implement low power or energy harvesting touch sensing interfaces. This paper presents a passive touch sensing technique based on the fact that the human body is affected by the surrounding extremely low frequency (ELF) electromagnetic fields, such as those of AC power lines. These external ELF fields induce electric potentials on the human body—because human tissues exhibit some conductivity at these frequencies—resulting in what is called AC hum. We therefore propose a passive touch sensing system that detects this hum noise when a human touch occurs, thus distinguishing between touch and non-touch events. The effectiveness of the proposed technique is validated by designing and implementing a flexible touch sensing keyboard. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle A Brain-Machine Interface Based on ERD/ERS for an Upper-Limb Exoskeleton Control
Sensors 2016, 16(12), 2050; doi:10.3390/s16122050
Received: 29 August 2016 / Revised: 22 October 2016 / Accepted: 8 November 2016 / Published: 2 December 2016
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Abstract
To recognize the user’s motion intention, brain-machine interfaces (BMI) usually decode movements from cortical activity to control exoskeletons and neuroprostheses for daily activities. The aim of this paper is to investigate whether self-induced variations of the electroencephalogram (EEG) can be useful as control
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To recognize the user’s motion intention, brain-machine interfaces (BMI) usually decode movements from cortical activity to control exoskeletons and neuroprostheses for daily activities. The aim of this paper is to investigate whether self-induced variations of the electroencephalogram (EEG) can be useful as control signals for an upper-limb exoskeleton developed by us. A BMI based on event-related desynchronization/synchronization (ERD/ERS) is proposed. In the decoder-training phase, we investigate the offline classification performance of left versus right hand and left hand versus both feet by using motor execution (ME) or motor imagery (MI). The results indicate that the accuracies of ME sessions are higher than those of MI sessions, and left hand versus both feet paradigm achieves a better classification performance, which would be used in the online-control phase. In the online-control phase, the trained decoder is tested in two scenarios (wearing or without wearing the exoskeleton). The MI and ME sessions wearing the exoskeleton achieve mean classification accuracy of 84.29% ± 2.11% and 87.37% ± 3.06%, respectively. The present study demonstrates that the proposed BMI is effective to control the upper-limb exoskeleton, and provides a practical method by non-invasive EEG signal associated with human natural behavior for clinical applications. Full article
(This article belongs to the Special Issue Wearable Biomedical Sensors)
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Open AccessArticle On the Use of a Feedback Tracking Architecture for Satellite Navigation Spoofing Detection
Sensors 2016, 16(12), 2051; doi:10.3390/s16122051
Received: 19 July 2016 / Revised: 26 November 2016 / Accepted: 29 November 2016 / Published: 2 December 2016
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Abstract
In this paper, the Extended Coupled Amplitude Delay Lock Loop (ECADLL) architecture, previously introduced as a solution able to deal with a multipath environment, is revisited and improved to tailor it to spoofing detection purposes. Exploiting a properly-defined decision algorithm, the architecture is
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In this paper, the Extended Coupled Amplitude Delay Lock Loop (ECADLL) architecture, previously introduced as a solution able to deal with a multipath environment, is revisited and improved to tailor it to spoofing detection purposes. Exploiting a properly-defined decision algorithm, the architecture is able to effectively detect a spoofer attack, as well as distinguish it from other kinds of interference events. The new algorithm is used to classify them according to their characteristics. We also introduce the use of a ratio metric detector in order to reduce the detection latency and the computational load of the architecture. Full article
(This article belongs to the Section Remote Sensors)
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Open AccessArticle Potentiometric Aptasensing of Vibrio alginolyticus Based on DNA Nanostructure-Modified Magnetic Beads
Sensors 2016, 16(12), 2052; doi:10.3390/s16122052
Received: 23 September 2016 / Revised: 25 November 2016 / Accepted: 28 November 2016 / Published: 2 December 2016
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Abstract
A potentiometric aptasensing assay that couples the DNA nanostructure-modified magnetic beads with a solid-contact polycation-sensitive membrane electrode for the detection of Vibrio alginolyticus is herein described. The DNA nanostructure-modified magnetic beads are used for amplification of the potential response and elimination of the
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A potentiometric aptasensing assay that couples the DNA nanostructure-modified magnetic beads with a solid-contact polycation-sensitive membrane electrode for the detection of Vibrio alginolyticus is herein described. The DNA nanostructure-modified magnetic beads are used for amplification of the potential response and elimination of the interfering effect from a complex sample matrix. The solid-contact polycation-sensitive membrane electrode using protamine as an indicator is employed to chronopotentiometrically detect the change in the charge or DNA concentration on the magnetic beads, which is induced by the interaction between Vibrio alginolyticus and the aptamer on the DNA nanostructures. The present potentiometric aptasensing method shows a linear range of 10–100 CFU mL−1 with a detection limit of 10 CFU mL−1, and a good specificity for the detection of Vibrio alginolyticus. This proposed strategy can be used for the detection of other microorganisms by changing the aptamers in the DNA nanostructures. Full article
(This article belongs to the Special Issue Nanobiosensing for Sensors)
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Open AccessArticle Fuzzy Computing Model of Activity Recognition on WSN Movement Data for Ubiquitous Healthcare Measurement
Sensors 2016, 16(12), 2053; doi:10.3390/s16122053
Received: 4 October 2016 / Revised: 22 November 2016 / Accepted: 23 November 2016 / Published: 3 December 2016
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Abstract
Ubiquitous health care (UHC) is beneficial for patients to ensure they complete therapeutic exercises by self-management at home. We designed a fuzzy computing model that enables recognizing assigned movements in UHC with privacy. The movements are measured by the self-developed body motion sensor,
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Ubiquitous health care (UHC) is beneficial for patients to ensure they complete therapeutic exercises by self-management at home. We designed a fuzzy computing model that enables recognizing assigned movements in UHC with privacy. The movements are measured by the self-developed body motion sensor, which combines both accelerometer and gyroscope chips to make an inertial sensing node compliant with a wireless sensor network (WSN). The fuzzy logic process was studied to calculate the sensor signals that would entail necessary features of static postures and dynamic motions. Combinations of the features were studied and the proper feature sets were chosen with compatible fuzzy rules. Then, a fuzzy inference system (FIS) can be generated to recognize the assigned movements based on the rules. We thus implemented both fuzzy and adaptive neuro-fuzzy inference systems in the model to distinguish static and dynamic movements. The proposed model can effectively reach the recognition scope of the assigned activity. Furthermore, two exercises of upper-limb flexion in physical therapy were applied for the model in which the recognition rate can stand for the passing rate of the assigned motions. Finally, a web-based interface was developed to help remotely measure movement in physical therapy for UHC. Full article
(This article belongs to the Special Issue Advances in Body Sensor Networks: Sensors, Systems, and Applications)
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Open AccessArticle A Novel Method for Vertical Acceleration Noise Suppression of a Thrust-Vectored VTOL UAV
Sensors 2016, 16(12), 2054; doi:10.3390/s16122054
Received: 7 September 2016 / Revised: 24 November 2016 / Accepted: 29 November 2016 / Published: 2 December 2016
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Abstract
Acceleration is of great importance in motion control for unmanned aerial vehicles (UAVs), especially during the takeoff and landing stages. However, the measured acceleration is inevitably polluted by severe noise. Therefore, a proper noise suppression procedure is required. This paper presents a novel
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Acceleration is of great importance in motion control for unmanned aerial vehicles (UAVs), especially during the takeoff and landing stages. However, the measured acceleration is inevitably polluted by severe noise. Therefore, a proper noise suppression procedure is required. This paper presents a novel method to reduce the noise in the measured vertical acceleration for a thrust-vectored tail-sitter vertical takeoff and landing (VTOL) UAV. In the new procedure, a Kalman filter is first applied to estimate the UAV mass by using the information in the vertical thrust and measured acceleration. The UAV mass is then used to compute an estimate of UAV vertical acceleration. The estimated acceleration is finally fused with the measured acceleration to obtain the minimum variance estimate of vertical acceleration. By doing this, the new approach incorporates the thrust information into the acceleration estimate. The method is applied to the data measured in a VTOL UAV takeoff experiment. Two other denoising approaches developed by former researchers are also tested for comparison. The results demonstrate that the new method is able to suppress the acceleration noise substantially. It also maintains the real-time performance in the final estimated acceleration, which is not seen in the former denoising approaches. The acceleration treated with the new method can be readily used in the motion control applications for UAVs to achieve improved accuracy. Full article
(This article belongs to the Special Issue UAV-Based Remote Sensing)
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Open AccessArticle Coordinate-Based Clustering Method for Indoor Fingerprinting Localization in Dense Cluttered Environments
Sensors 2016, 16(12), 2055; doi:10.3390/s16122055
Received: 27 September 2016 / Revised: 17 November 2016 / Accepted: 29 November 2016 / Published: 2 December 2016
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Abstract
Indoor positioning technologies has boomed recently because of the growing commercial interest in indoor location-based service (ILBS). Due to the absence of satellite signal in Global Navigation Satellite System (GNSS), various technologies have been proposed for indoor applications. Among them, Wi-Fi fingerprinting has
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Indoor positioning technologies has boomed recently because of the growing commercial interest in indoor location-based service (ILBS). Due to the absence of satellite signal in Global Navigation Satellite System (GNSS), various technologies have been proposed for indoor applications. Among them, Wi-Fi fingerprinting has been attracting much interest from researchers because of its pervasive deployment, flexibility and robustness to dense cluttered indoor environments. One challenge, however, is the deployment of Access Points (AP), which would bring a significant influence on the system positioning accuracy. This paper concentrates on WLAN based fingerprinting indoor location by analyzing the AP deployment influence, and studying the advantages of coordinate-based clustering compared to traditional RSS-based clustering. A coordinate-based clustering method for indoor fingerprinting location, named Smallest-Enclosing-Circle-based (SEC), is then proposed aiming at reducing the positioning error lying in the AP deployment and improving robustness to dense cluttered environments. All measurements are conducted in indoor public areas, such as the National Center For the Performing Arts (as Test-bed 1) and the XiDan Joy City (Floors 1 and 2, as Test-bed 2), and results show that SEC clustering algorithm can improve system positioning accuracy by about 32.7% for Test-bed 1, 71.7% for Test-bed 2 Floor 1 and 73.7% for Test-bed 2 Floor 2 compared with traditional RSS-based clustering algorithms such as K-means. Full article
(This article belongs to the Special Issue Scalable Localization in Wireless Sensor Networks)
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Open AccessArticle Minimum Interference Channel Assignment Algorithm for Multicast in a Wireless Mesh Network
Sensors 2016, 16(12), 2056; doi:10.3390/s16122056
Received: 10 August 2016 / Revised: 18 November 2016 / Accepted: 28 November 2016 / Published: 2 December 2016
Cited by 1 | PDF Full-text (1358 KB) | HTML Full-text | XML Full-text