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Sensors, Volume 20, Issue 8 (April-2 2020) – 278 articles

Cover Story (view full-size image): “Virtus Unita Fortior!” Synthetic sensing materials are some of the most attractive components of chemical/biosensors because of their long-term stability and low-cost of production. For the construction of artificial material-based sensors, the bottom-up assembly of these materials is one of the effective methods. This is because the driving forces of molecular recognition on the receptors could be enhanced by the integration of such kinds of materials at the ‘interfaces’. Thus, synthetic receptor membrane-based nanosensors can be applied to powerful tools for high-throughput analyses of the required targets. In this review, we summarize a comprehensive overview that includes the preparation techniques for molecular assemblies, the characterization methods of the interfaces, and a few examples of receptor assembly-based chemical/biosensing platforms on each transduction mechanism.View this paper.
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15 pages, 15725 KiB  
Article
Shedding Light on People Action Recognition in Social Robotics by Means of Common Spatial Patterns
by Itsaso Rodríguez-Moreno, José María Martínez-Otzeta, Izaro Goienetxea, Igor Rodriguez-Rodriguez and Basilio Sierra
Sensors 2020, 20(8), 2436; https://doi.org/10.3390/s20082436 - 24 Apr 2020
Cited by 13 | Viewed by 2922
Abstract
Action recognition in robotics is a research field that has gained momentum in recent years. In this work, a video activity recognition method is presented, which has the ultimate goal of endowing a robot with action recognition capabilities for a more natural social [...] Read more.
Action recognition in robotics is a research field that has gained momentum in recent years. In this work, a video activity recognition method is presented, which has the ultimate goal of endowing a robot with action recognition capabilities for a more natural social interaction. The application of Common Spatial Patterns (CSP), a signal processing approach widely used in electroencephalography (EEG), is presented in a novel manner to be used in activity recognition in videos taken by a humanoid robot. A sequence of skeleton data is considered as a multidimensional signal and filtered according to the CSP algorithm. Then, characteristics extracted from these filtered data are used as features for a classifier. A database with 46 individuals performing six different actions has been created to test the proposed method. The CSP-based method along with a Linear Discriminant Analysis (LDA) classifier has been compared to a Long Short-Term Memory (LSTM) neural network, showing that the former obtains similar or better results than the latter, while being simpler. Full article
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18 pages, 2821 KiB  
Article
Medication Adherence and Liquid Level Tracking System for Healthcare Provider Feedback
by Nolan Payne, Rahul Gangwani, Kira Barton, Alanson P. Sample, Stephen M. Cain, David T. Burke, Paula Anne Newman-Casey and K. Alex Shorter
Sensors 2020, 20(8), 2435; https://doi.org/10.3390/s20082435 - 24 Apr 2020
Cited by 7 | Viewed by 4078
Abstract
A common problem for healthcare providers is accurately tracking patients’ adherence to medication and providing real-time feedback on the management of their medication regimen. This is a particular problem for eye drop medications, as the current commercially available monitors focus on measuring adherence [...] Read more.
A common problem for healthcare providers is accurately tracking patients’ adherence to medication and providing real-time feedback on the management of their medication regimen. This is a particular problem for eye drop medications, as the current commercially available monitors focus on measuring adherence to pills, and not to eye drops. This work presents an intelligent bottle sleeve that slides onto a prescription eye drop medication bottle. The intelligent sleeve is capable of detecting eye drop use, measuring fluid level, and sending use information to a healthcare team to facilitate intervention. The electronics embedded into the sleeve measure fluid level, dropper orientation, the state of the dropper top (on/off), and rates of angular motion during an application. The sleeve was tested with ten patients (age ≥65) and successfully identified and timestamped 94% of use events. On-board processing enabled event detection and the measurement of fluid levels at a 0.4 mL resolution. These data were communicated to the healthcare team using Bluetooth and Wi-Fi in real-time, enabling rapid feedback to the subject. The healthcare team can therefore monitor a log of medication use behavior to make informed decisions on treatment or support for the patient. Full article
(This article belongs to the Special Issue Wearable Sensors and Systems in the IOT)
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21 pages, 2359 KiB  
Article
Data Offloading in UAV-Assisted Multi-Access Edge Computing Systems: A Resource-Based Pricing and User Risk-Awareness Approach
by Giorgos Mitsis, Eirini Eleni Tsiropoulou and Symeon Papavassiliou
Sensors 2020, 20(8), 2434; https://doi.org/10.3390/s20082434 - 24 Apr 2020
Cited by 34 | Viewed by 4220
Abstract
Unmanned Aerial Vehicle (UAV)-assisted Multi-access Edge Computing (MEC) systems have emerged recently as a flexible and dynamic computing environment, providing task offloading service to the users. In order for such a paradigm to be viable, the operator of a UAV-mounted MEC server should [...] Read more.
Unmanned Aerial Vehicle (UAV)-assisted Multi-access Edge Computing (MEC) systems have emerged recently as a flexible and dynamic computing environment, providing task offloading service to the users. In order for such a paradigm to be viable, the operator of a UAV-mounted MEC server should enjoy some form of profit by offering its computing capabilities to the end users. To deal with this issue in this paper, we apply a usage-based pricing policy for allowing the exploitation of the servers’ computing resources. The proposed pricing mechanism implicitly introduces a more social behavior to the users with respect to competing for the UAV-mounted MEC servers’ computation resources. In order to properly model the users’ risk-aware behavior within the overall data offloading decision-making process the principles of Prospect Theory are adopted, while the exploitation of the available computation resources is considered based on the theory of the Tragedy of the Commons. Initially, the user’s prospect-theoretic utility function is formulated by quantifying the user’s risk seeking and loss aversion behavior, while taking into account the pricing mechanism. Accordingly, the users’ pricing and risk-aware data offloading problem is formulated as a distributed maximization problem of each user’s expected prospect-theoretic utility function and addressed as a non-cooperative game among the users. The existence of a Pure Nash Equilibrium (PNE) for the formulated non-cooperative game is shown based on the theory of submodular games. An iterative and distributed algorithm is introduced which converges to the PNE, following the learning rule of the best response dynamics. The performance evaluation of the proposed approach is achieved via modeling and simulation, and detailed numerical results are presented highlighting its key operation features and benefits. Full article
(This article belongs to the Special Issue Optimization and Communication in UAV Networks)
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16 pages, 5926 KiB  
Article
Fault Diagnosis of Planetary Gearbox Based on Adaptive Order Bispectrum Slice and Fault Characteristics Energy Ratio Analysis
by Zhaoyang Shen, Zhanqun Shi, Dong Zhen, Hao Zhang and Fengshou Gu
Sensors 2020, 20(8), 2433; https://doi.org/10.3390/s20082433 - 24 Apr 2020
Cited by 6 | Viewed by 2536
Abstract
The vibration of a planetary gearbox (PG) is complex and mutually modulated, which makes the weak features of incipient fault difficult to detect. To target this problem, a novel method, based on an adaptive order bispectrum slice (AOBS) and the fault characteristics energy [...] Read more.
The vibration of a planetary gearbox (PG) is complex and mutually modulated, which makes the weak features of incipient fault difficult to detect. To target this problem, a novel method, based on an adaptive order bispectrum slice (AOBS) and the fault characteristics energy ratio (FCER), is proposed. The order bispectrum (OB) method has shown its effectiveness in the feature extraction of bearings and fixed-shaft gearboxes. However, the effectiveness of the PG still needs to be explored. The FCER is developed to sum up the fault information, which is scattered by mutual modulation. In this method, the raw vibration signal is firstly converted to that in the angle domain. Secondly, the characteristic slice of AOBS is extracted. Different from the conventional OB method, the AOBS is extracted by searching for a characteristic carrier frequency adaptively in the sensitive range of signal coupling. Finally, the FCER is summed up and calculated from the fault features that were dispersed in the characteristic slice. Experimental data was processed, using both the AOBS-FCER method, and the method that combines order spectrum analysis with sideband energy ratio (OSA-SER), respectively. Results indicated that the new method is effective in incipient fault feature extraction, compared with the methods of OB and OSA-SER. Full article
(This article belongs to the Special Issue Sensors for Fault Diagnosis and Prognostics)
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20 pages, 10972 KiB  
Article
SGC-VSLAM: A Semantic and Geometric Constraints VSLAM for Dynamic Indoor Environments
by Shiqiang Yang, Guohao Fan, Lele Bai, Cheng Zhao and Dexin Li
Sensors 2020, 20(8), 2432; https://doi.org/10.3390/s20082432 - 24 Apr 2020
Cited by 16 | Viewed by 3982
Abstract
As one of the core technologies for autonomous mobile robots, Visual Simultaneous Localization and Mapping (VSLAM) has been widely researched in recent years. However, most state-of-the-art VSLAM adopts a strong scene rigidity assumption for analytical convenience, which limits the utility of these algorithms [...] Read more.
As one of the core technologies for autonomous mobile robots, Visual Simultaneous Localization and Mapping (VSLAM) has been widely researched in recent years. However, most state-of-the-art VSLAM adopts a strong scene rigidity assumption for analytical convenience, which limits the utility of these algorithms for real-world environments with independent dynamic objects. Hence, this paper presents a semantic and geometric constraints VSLAM (SGC-VSLAM), which is built on the RGB-D mode of ORB-SLAM2 with the addition of dynamic detection and static point cloud map construction modules. In detail, a novel improved quadtree-based method was adopted for SGC-VSLAM to enhance the performance of the feature extractor in ORB-SLAM (Oriented FAST and Rotated BRIEF-SLAM). Moreover, a new dynamic feature detection method called semantic and geometric constraints was proposed, which provided a robust and fast way to filter dynamic features. The semantic bounding box generated by YOLO v3 (You Only Look Once, v3) was used to calculate a more accurate fundamental matrix between adjacent frames, which was then used to filter all of the truly dynamic features. Finally, a static point cloud was estimated by using a new drawing key frame selection strategy. Experiments on the public TUM RGB-D (Red-Green-Blue Depth) dataset were conducted to evaluate the proposed approach. This evaluation revealed that the proposed SGC-VSLAM can effectively improve the positioning accuracy of the ORB-SLAM2 system in high-dynamic scenarios and was also able to build a map with the static parts of the real environment, which has long-term application value for autonomous mobile robots. Full article
(This article belongs to the Special Issue Intelligent Systems and Sensors for Robotics)
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13 pages, 4293 KiB  
Article
Combined Long-Period Fiber Grating and Microcavity In-Line Mach–Zehnder Interferometer for Refractive Index Measurements with Limited Cross-Sensitivity
by Monika Janik, Marcin Koba, Krystian Król, Predrag Mikulic, Wojtek J. Bock and Mateusz Śmietana
Sensors 2020, 20(8), 2431; https://doi.org/10.3390/s20082431 - 24 Apr 2020
Cited by 15 | Viewed by 2737
Abstract
This work discusses sensing properties of a long-period grating (LPG) and microcavity in-line Mach–Zehnder interferometer (µIMZI) when both are induced in the same single-mode optical fiber. LPGs were either etched or nanocoated with aluminum oxide (Al2O3) to increase its [...] Read more.
This work discusses sensing properties of a long-period grating (LPG) and microcavity in-line Mach–Zehnder interferometer (µIMZI) when both are induced in the same single-mode optical fiber. LPGs were either etched or nanocoated with aluminum oxide (Al2O3) to increase its refractive index (RI) sensitivity up to ≈2000 and 9000 nm/RIU, respectively. The µIMZI was machined using a femtosecond laser as a cylindrical cavity (d = 60 μm) in the center of the LPG. In transmission measurements for various RI in the cavity and around the LPG we observed two effects coming from the two independently working sensors. This dual operation had no significant impact on either of the devices in terms of their functional properties, especially in a lower RI range. Moreover, due to the properties of combined sensors two major effects can be distinguished—sensitivity to the RI of the volume and sensitivity to the RI at the surface. Considering also the negligible temperature sensitivity of the µIMZI, it makes the combination of LPG and µIMZI sensors a promising approach to limit cross-sensitivity or tackle simultaneous measurements of multiple effects with high efficiency and reliability. Full article
(This article belongs to the Special Issue Optical Fiber Sensors for Biomedical Applications)
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17 pages, 7095 KiB  
Article
Time-Interleaved SAR ADC with Background Timing-Skew Calibration for UWB Wireless Communication in IoT Systems
by Kiho Seong, Dong-Kyu Jung, Dong-Hyun Yoon, Jae-Soub Han, Ju-Eon Kim, Tony Tae-Hyoung Kim, Woojoo Lee and Kwang-Hyun Baek
Sensors 2020, 20(8), 2430; https://doi.org/10.3390/s20082430 - 24 Apr 2020
Cited by 14 | Viewed by 5172
Abstract
Ultra-wideband (UWB) wireless communication is prospering as a powerful partner of the Internet-of-things (IoT). Due to the ongoing development of UWB wireless communications, the demand for high-speed and medium resolution analog-to-digital converters (ADCs) continues to grow. The successive approximation register (SAR) ADCs are [...] Read more.
Ultra-wideband (UWB) wireless communication is prospering as a powerful partner of the Internet-of-things (IoT). Due to the ongoing development of UWB wireless communications, the demand for high-speed and medium resolution analog-to-digital converters (ADCs) continues to grow. The successive approximation register (SAR) ADCs are the most powerful candidate to meet these demands, attracting both industries and academia. In particular, recent time-interleaved SAR ADCs show that multi-giga sample per second (GS/s) can be achieved by overcoming the challenges of high-speed implementation of existing SAR ADCs. However, there are still critical issues that need to be addressed before the time-interleaved SAR ADCs can be applied in real commercial applications. The most well-known problem is that the time-interleaved SAR ADC architecture requires multiple sub-ADCs, and the mismatches between these sub-ADCs can significantly degrade overall ADC performance. And one of the most difficult mismatches to solve is the sampling timing skew. Recently, research to solve this timing-skew problem has been intensively studied. In this paper, we focus on the cutting-edge timing-skew calibration technique using a window detector. Based on the pros and cons analysis of the existing techniques, we come up with an idea that increases the benefits of the window detector-based timing-skew calibration techniques and minimizes the power and area overheads. Finally, through the continuous development of this idea, we propose a timing-skew calibration technique using a comparator offset-based window detector. To demonstrate the effectiveness of the proposed technique, intensive works were performed, including the design of a 7-bit, 2.5 GS/s 5-channel time-interleaved SAR ADC and various simulations, and the results prove excellent efficacy of signal-to-noise and distortion ratio (SNDR) and spurious-free dynamic range (SFDR) of 40.79 dB and 48.97 dB at Nyquist frequency, respectively, while the proposed window detector occupies only 6.5% of the total active area, and consumes 11% of the total power. Full article
(This article belongs to the Section Communications)
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26 pages, 9492 KiB  
Article
Implementation of System Operation Modes for Health Management and Failure Prognosis in Cyber-Physical Systems
by Santiago Ruiz-Arenas, Zoltán Rusák, Ricardo Mejía-Gutiérrez and Imre Horváth
Sensors 2020, 20(8), 2429; https://doi.org/10.3390/s20082429 - 24 Apr 2020
Cited by 5 | Viewed by 2066
Abstract
Cyber-physical systems (CPSs) have sophisticated control mechanisms that help achieve optimal system operations and services. These mechanisms, imply considering multiple signal inputs in parallel, to timely respond to varying working conditions. Despite the advantages that control mechanisms convey, they bring new challenges in [...] Read more.
Cyber-physical systems (CPSs) have sophisticated control mechanisms that help achieve optimal system operations and services. These mechanisms, imply considering multiple signal inputs in parallel, to timely respond to varying working conditions. Despite the advantages that control mechanisms convey, they bring new challenges in terms of failure prevention. The compensatory action the control exerts cause a fault masking effect, hampering fault diagnosis. Likewise, the multiple information inputs CPSs have to process can affect the timely system response to faults. This article proposes a failure prognosis method, which combines time series-based forecasting methods with statistically based classification techniques in order to investigate system degradation and failure forming on system levels. This method utilizes a new approach based on the concept of the system operation mode (SOM) that offers a novel perspective for health management that allows monitoring the system behavior, through the frequency and duration of SOMs. Validation of this method was conducted by systematically injecting faults in a cyber-physical greenhouse testbed. The obtained results demonstrate that the degradation and fault forming process can be monitored by analyzing the changes of the frequency and duration of SOMs. These indicators made possible to estimate the time to failure caused by various failures in the conducted experiments. Full article
(This article belongs to the Section Fault Diagnosis & Sensors)
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16 pages, 7342 KiB  
Article
Research on Visualization and Error Compensation of Demolition Robot Attachment Changing
by Qian Deng, Shuliang Zou, Hongbin Chen and Weixiong Duan
Sensors 2020, 20(8), 2428; https://doi.org/10.3390/s20082428 - 24 Apr 2020
Cited by 3 | Viewed by 2834
Abstract
Attachment changing in demolition robots has a high docking accuracy requirement, so it is hard for operators to control this process remotely through the perspective of a camera. To solve this problem, this study investigated positioning error and proposed a method of error [...] Read more.
Attachment changing in demolition robots has a high docking accuracy requirement, so it is hard for operators to control this process remotely through the perspective of a camera. To solve this problem, this study investigated positioning error and proposed a method of error compensation to achieve a highly precise attachment changing process. This study established a link parameter model for the demolition robot, measured the error in the attachment changing, introduced a reference coordinate system to solve the coordinate transformation from the dock spot of the robot’s quick-hitch equipment to the dock spot of the attachment, and realized error compensation. Through calculation and experimentation, it was shown that the error compensation method proposed in this study reduced the level of error in attachment changing from the centimeter to millimeter scale, thereby meeting the accuracy requirements for attachment changing. This method can be applied to the remote-controlled attachment changing process of demolition robots, which provides the basis for the subsequent automatic changing of attachments. This has the potential to be applied in nuclear facility decommissioning and dismantling, as well as other radioactive environments. Full article
(This article belongs to the Section Intelligent Sensors)
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16 pages, 2401 KiB  
Article
Intra- and Inter-Rater Reliability of Manual Feature Extraction Methods in Movement Related Cortical Potential Analysis
by Gemma Alder, Nada Signal, Usman Rashid, Sharon Olsen, Imran Khan Niazi and Denise Taylor
Sensors 2020, 20(8), 2427; https://doi.org/10.3390/s20082427 - 24 Apr 2020
Viewed by 3376
Abstract
Event related potentials (ERPs) provide insight into the neural activity generated in response to motor, sensory and cognitive processes. Despite the increasing use of ERP data in clinical research little is known about the reliability of human manual ERP labelling methods. Intra-rater and [...] Read more.
Event related potentials (ERPs) provide insight into the neural activity generated in response to motor, sensory and cognitive processes. Despite the increasing use of ERP data in clinical research little is known about the reliability of human manual ERP labelling methods. Intra-rater and inter-rater reliability were evaluated in five electroencephalography (EEG) experts who labelled the peak negativity of averaged movement related cortical potentials (MRCPs) derived from thirty datasets. Each dataset contained 50 MRCP epochs from healthy people performing cued voluntary or imagined movement, or people with stroke performing cued voluntary movement. Reliability was assessed using the intraclass correlation coefficient and standard error of measurement. Excellent intra- and inter-rater reliability was demonstrated in the voluntary movement conditions in healthy people and people with stroke. In comparison reliability in the imagined condition was low to moderate. Post-hoc secondary epoch analysis revealed that the morphology of the signal contributed to the consistency of epoch inclusion; potentially explaining the differences in reliability seen across conditions. Findings from this study may inform future research focused on developing automated labelling methods for ERP feature extraction and call to the wider community of researchers interested in utilizing ERPs as a measure of neurophysiological change or in the delivery of EEG-driven interventions. Full article
(This article belongs to the Special Issue Biomedical Signal Processing)
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17 pages, 2066 KiB  
Article
Adversarial Networks for Scale Feature-Attention Spectral Image Reconstruction from a Single RGB
by Pengfei Liu and Huaici Zhao
Sensors 2020, 20(8), 2426; https://doi.org/10.3390/s20082426 - 24 Apr 2020
Cited by 11 | Viewed by 2842
Abstract
Hyperspectral images reconstruction focuses on recovering the spectral information from a single RGBimage. In this paper, we propose two advanced Generative Adversarial Networks (GAN) for the heavily underconstrained inverse problem. We first propose scale attention pyramid UNet (SAPUNet), which uses U-Net with dilated [...] Read more.
Hyperspectral images reconstruction focuses on recovering the spectral information from a single RGBimage. In this paper, we propose two advanced Generative Adversarial Networks (GAN) for the heavily underconstrained inverse problem. We first propose scale attention pyramid UNet (SAPUNet), which uses U-Net with dilated convolution to extract features. We establish the feature pyramid inside the network and use the attention mechanism for feature selection. The superior performance of this model is due to the modern architecture and capturing of spatial semantics. To provide a more accurate solution, we propose another distinct architecture, named W-Net, that builds one more branch compared to U-Net to conduct boundary supervision. SAPUNet and scale attention pyramid WNet (SAPWNet) provide improvements on the Interdisciplinary Computational Vision Lab at Ben Gurion University (ICVL) datasetby 42% and 46.6%, and 45% and 50% in terms of root mean square error (RMSE) and relative RMSE, respectively. The experimental results demonstrate that our proposed models are more accurate than the state-of-the-art hyperspectral recovery methods Full article
(This article belongs to the Section Remote Sensors)
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24 pages, 471 KiB  
Review
Predictive Maintenance for Pump Systems and Thermal Power Plants: State-of-the-Art Review, Trends and Challenges
by Jonas Fausing Olesen and Hamid Reza Shaker
Sensors 2020, 20(8), 2425; https://doi.org/10.3390/s20082425 - 24 Apr 2020
Cited by 50 | Viewed by 10328
Abstract
Thermal power plants are an important asset in the current energy infrastructure, delivering ancillary services, power, and heat to their respective consumers. Faults on critical components, such as large pumping systems, can lead to material damage and opportunity losses. Pumps plays an essential [...] Read more.
Thermal power plants are an important asset in the current energy infrastructure, delivering ancillary services, power, and heat to their respective consumers. Faults on critical components, such as large pumping systems, can lead to material damage and opportunity losses. Pumps plays an essential role in various industries and as such clever maintenance can ensure cost reductions and high availability. Prognostics and Health Management, PHM, is the study utilizing data to estimate the current and future conditions of a system. Within the field of PHM, Predictive Maintenance, PdM, has been gaining increased attention. Data-driven models can be built to estimate the remaining-useful-lifetime of complex systems that would be difficult to identify by man. With the increased attention that the Predictive Maintenance field is receiving, review papers become increasingly important to understand what research has been conducted and what challenges need to be addressed. This paper does so by initially conceptualising the PdM field. A structured overview of literature in regard to application within PdM is presented, before delving into the domain of thermal power plants and pump systems. Finally, related challenges and trends will be outlined. This paper finds that a large number of experimental data-driven models have been successfully deployed, but the PdM field would benefit from more industrial case studies. Furthermore, investigations into the scale-ability of models would benefit industries that are looking into large-scale implementations. Here, examining a method for automatic maintenance of the developed model will be of interest. This paper can be used to understand the PdM field as a broad concept but does also provide a niche understanding of the domain in focus. Full article
(This article belongs to the Section Intelligent Sensors)
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24 pages, 3132 KiB  
Article
Wearable Sensor-Based Gait Analysis for Age and Gender Estimation
by Md Atiqur Rahman Ahad, Thanh Trung Ngo, Anindya Das Antar, Masud Ahmed, Tahera Hossain, Daigo Muramatsu, Yasushi Makihara, Sozo Inoue and Yasushi Yagi
Sensors 2020, 20(8), 2424; https://doi.org/10.3390/s20082424 - 24 Apr 2020
Cited by 35 | Viewed by 6211
Abstract
Wearable sensor-based systems and devices have been expanded in different application domains, especially in the healthcare arena. Automatic age and gender estimation has several important applications. Gait has been demonstrated as a profound motion cue for various applications. A gait-based age and gender [...] Read more.
Wearable sensor-based systems and devices have been expanded in different application domains, especially in the healthcare arena. Automatic age and gender estimation has several important applications. Gait has been demonstrated as a profound motion cue for various applications. A gait-based age and gender estimation challenge was launched in the 12th IAPR International Conference on Biometrics (ICB), 2019. In this competition, 18 teams initially registered from 14 countries. The goal of this challenge was to find some smart approaches to deal with age and gender estimation from sensor-based gait data. For this purpose, we employed a large wearable sensor-based gait dataset, which has 745 subjects (357 females and 388 males), from 2 to 78 years old in the training dataset; and 58 subjects (19 females and 39 males) in the test dataset. It has several walking patterns. The gait data sequences were collected from three IMUZ sensors, which were placed on waist-belt or at the top of a backpack. There were 67 solutions from ten teams—for age and gender estimation. This paper extensively analyzes the methods and achieved-results from various approaches. Based on analysis, we found that deep learning-based solutions lead the competitions compared with conventional handcrafted methods. We found that the best result achieved 24.23% prediction error for gender estimation, and 5.39 mean absolute error for age estimation by employing angle embedded gait dynamic image and temporal convolution network. Full article
(This article belongs to the Special Issue Inertial Sensors for Activity Recognition and Classification)
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13 pages, 4995 KiB  
Article
PM2.5 Concentration Estimation Based on Image Processing Schemes and Simple Linear Regression
by Jiun-Jian Liaw, Yung-Fa Huang, Cheng-Hsiung Hsieh, Dung-Ching Lin and Chin-Hsiang Luo
Sensors 2020, 20(8), 2423; https://doi.org/10.3390/s20082423 - 24 Apr 2020
Cited by 12 | Viewed by 3240
Abstract
Fine aerosols with a diameter of less than 2.5 microns (PM2.5) have a significant negative impact on human health. However, their measurement devices or instruments are usually expensive and complicated operations are required, so a simple and effective way for measuring [...] Read more.
Fine aerosols with a diameter of less than 2.5 microns (PM2.5) have a significant negative impact on human health. However, their measurement devices or instruments are usually expensive and complicated operations are required, so a simple and effective way for measuring the PM2.5 concentration is needed. To relieve this problem, this paper attempts to provide an easy alternative approach to PM2.5 concentration estimation. The proposed approach is based on image processing schemes and a simple linear regression model. It uses images with a high and low PM2.5 concentration to obtain the difference between these images. The difference is applied to find the region with the greatest impact. The approach is described in two stages. First, a series of image processing schemes are employed to automatically select the region of interest (RoI) for PM2.5 concentration estimation. Through the selected RoI, a single feature is obtained. Second, by employing the single feature, a simple linear regression model is used and applied to PM2.5 concentration estimation. The proposed approach is verified by the real-world open data released by Taiwan’s government. The proposed scheme is not expected to replace component analysis using physical or chemical techniques. We have tried to provide a cheaper and easier way to conduct PM2.5 estimation with an acceptable performance more efficiently. To achieve this, further work will be conducted and is summarized at the end of this paper. Full article
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11 pages, 11711 KiB  
Letter
Safe Helicopter Landing on Unprepared Terrain Using Onboard Interferometric Radar
by Pavel E. Shimkin, Alexander I. Baskakov, Aleksey A. Komarov and Min-Ho Ka
Sensors 2020, 20(8), 2422; https://doi.org/10.3390/s20082422 - 24 Apr 2020
Cited by 3 | Viewed by 2681
Abstract
This letter proposes a radar interferometric survey system for the ground surface of helicopter landing sites. This system generates high-quality three-dimensional terrain surface topography data and estimates the slope of the site with the required accuracy. This study presents the processing algorithms of [...] Read more.
This letter proposes a radar interferometric survey system for the ground surface of helicopter landing sites. This system generates high-quality three-dimensional terrain surface topography data and estimates the slope of the site with the required accuracy. This study presents the processing algorithms of the radar system for safe helicopter landing using an interferometric method and also demonstrates the efficiency of the proposed approach based on computer simulation results. The results of the calculated potential accuracy characteristics of such a system are presented, as well as one of the variants of the algorithmic implementation of a simulation computer model implemented on MATLAB. Visual results of modeling using an example of a helicopter landing on a non-uniform surface relief similar to a real case are shown. The study focuses on the simulation of a unique on-board radar system, which allows helicopters to land on an unprepared site with a high degree of safety, having previously determined the presence of dangerous irregularities, inclines, foreign objects, and mechanisms on the site. Full article
(This article belongs to the Special Issue InSAR Signal and Data Processing)
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12 pages, 1103 KiB  
Article
Perception of a Haptic Stimulus Presented Under the Foot Under Workload
by Landry Delphin Chapwouo Tchakoute and Bob-Antoine J. Menelas
Sensors 2020, 20(8), 2421; https://doi.org/10.3390/s20082421 - 24 Apr 2020
Cited by 3 | Viewed by 2265
Abstract
It is clear that the haptic channel can be exploited as a communication medium for several tasks of everyday life. Here we investigated whether such communication can be altered in a cognitive load situation. We studied the perception of a vibrotactile stimulus presented [...] Read more.
It is clear that the haptic channel can be exploited as a communication medium for several tasks of everyday life. Here we investigated whether such communication can be altered in a cognitive load situation. We studied the perception of a vibrotactile stimulus presented under the foot when the attention is loaded by another task (cognitive load). The results demonstrated a significant influence of workload on the perception of the vibrotactile stimulus. Overall, we observed that the average score in the single-task (at rest) condition was greater than the overall mean score in the dual-task conditions (counting forwards, counting backwards, and walking). The walking task was the task that most influenced the perception of the vibrotactile stimulus presented under the foot. Full article
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12 pages, 2083 KiB  
Article
Fast Screening of Whole Blood and Tumor Tissue for Bladder Cancer Biomarkers Using Stochastic Needle Sensors
by Raluca-Ioana Stefan-van Staden, Damaris-Cristina Gheorghe, Viorel Jinga, Cristian Sorin Sima and Marius Geanta
Sensors 2020, 20(8), 2420; https://doi.org/10.3390/s20082420 - 24 Apr 2020
Cited by 12 | Viewed by 2595
Abstract
Bladder cancer is one of the most common urologic malignancies, which is more frequent in men than in women. The early diagnosis for this type of cancer still remains a challenge, therefore, the development of a fast screening test for whole blood and [...] Read more.
Bladder cancer is one of the most common urologic malignancies, which is more frequent in men than in women. The early diagnosis for this type of cancer still remains a challenge, therefore, the development of a fast screening test for whole blood and tumor tissue samples may save lives. Four biomarkers, p53, E-cadherin, bladder tumor antigen (BTA), and hyaluronic acid were considered for the screening tests using stochastic needle sensors. Three stochastic needle sensors, based on graphite powder and modified with three types of chitosan, were designed and characterized for the screening test. The proposed sensors showed low limits of quantification, and high sensitivity and selectivity levels. The recoveries of p53, E-cadherin, BTA, and hyaluronic acid in whole blood samples and tissue samples were higher than 95.00% with a relative standard deviation lower than 1.00%. Full article
(This article belongs to the Special Issue Graphene-Based Sensors for Pharmaceutical and Biomedical Analysis)
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10 pages, 2944 KiB  
Article
Enhancement of Photoemission on p-Type GaAs Using Surface Acoustic Waves
by Boqun Dong, Andrei Afanasev, Rolland Johnson and Mona Zaghloul
Sensors 2020, 20(8), 2419; https://doi.org/10.3390/s20082419 - 24 Apr 2020
Cited by 6 | Viewed by 2544
Abstract
We demonstrate that photoemission properties of p-type GaAs can be altered by surface acoustic waves (SAWs) generated on the GaAs surface due to dynamical piezoelectric fields of SAWs. Multiphysics simulations indicate that charge-carrier recombination is greatly reduced, and electron effective lifetime in p-doped [...] Read more.
We demonstrate that photoemission properties of p-type GaAs can be altered by surface acoustic waves (SAWs) generated on the GaAs surface due to dynamical piezoelectric fields of SAWs. Multiphysics simulations indicate that charge-carrier recombination is greatly reduced, and electron effective lifetime in p-doped GaAs may increase by a factor of 10× to 20×. It implies a significant increase, by a factor of 2× to 3×, of quantum efficiency (QE) for GaAs photoemission applications, like GaAs photocathodes. Conditions of different SAW wavelengths, swept SAW intensities, and varied incident photon energies were investigated. Essential steps in SAW device fabrication on a GaAs substrate are demonstrated, including deposition of an additional layer of ZnO for piezoelectric effect enhancement, measurements of current–voltage (I–V) characteristics of the SAW device, and ability to survive high-temperature annealing. Results obtained and reported in this study provide the potential and basis for future studies on building SAW-enhanced photocathodes, as well as other GaAs photoelectric applications. Full article
(This article belongs to the Special Issue Surface Acoustic Wave and Bulk Acoustic Wave Sensors 2019)
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26 pages, 18576 KiB  
Article
An IoT Platform Based on Microservices and Serverless Paradigms for Smart Farming Purposes
by Sergio Trilles, Alberto González-Pérez and Joaquín Huerta
Sensors 2020, 20(8), 2418; https://doi.org/10.3390/s20082418 - 24 Apr 2020
Cited by 55 | Viewed by 8693
Abstract
Nowadays, the concept of “Everything is connected to Everything” has spread to reach increasingly diverse scenarios, due to the benefits of constantly being able to know, in real-time, the status of your factory, your city, your health or your smallholding. This wide variety [...] Read more.
Nowadays, the concept of “Everything is connected to Everything” has spread to reach increasingly diverse scenarios, due to the benefits of constantly being able to know, in real-time, the status of your factory, your city, your health or your smallholding. This wide variety of scenarios creates different challenges such as the heterogeneity of IoT devices, support for large numbers of connected devices, reliable and safe systems, energy efficiency and the possibility of using this system by third-parties in other scenarios. A transversal middleware in all IoT solutions is called an IoT platform. the IoT platform is a piece of software that works like a kind of “glue” to combine platforms and orchestrate capabilities that connect devices, users and applications/services in a “cyber-physical” world. In this way, the IoT platform can help solve the challenges listed above. This paper proposes an IoT agnostic architecture, highlighting the role of the IoT platform, within a broader ecosystem of interconnected tools, aiming at increasing scalability, stability, interoperability and reusability. For that purpose, different paradigms of computing will be used, such as microservices architecture and serverless computing. Additionally, a technological proposal of the architecture, called SEnviro Connect, is presented. This proposal is validated in the IoT scenario of smart farming, where five IoT devices (SEnviro nodes) have been deployed to improve wine production. A comprehensive performance evaluation is carried out to guarantee a scalable and stable platform. Full article
(This article belongs to the Special Issue Smart Agricultural Applications with Internet of Things)
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15 pages, 499 KiB  
Article
Covert Timing Channel Analysis Either as Cyber Attacks or Confidential Applications
by Shorouq Al-Eidi, Omar Darwish and Yuanzhu Chen
Sensors 2020, 20(8), 2417; https://doi.org/10.3390/s20082417 - 24 Apr 2020
Cited by 11 | Viewed by 4244
Abstract
Covert timing channels are an important alternative for transmitting information in the world of the Internet of Things (IoT). In covert timing channels data are encoded in inter-arrival times between consecutive packets based on modifying the transmission time of legitimate traffic. Typically, the [...] Read more.
Covert timing channels are an important alternative for transmitting information in the world of the Internet of Things (IoT). In covert timing channels data are encoded in inter-arrival times between consecutive packets based on modifying the transmission time of legitimate traffic. Typically, the modification of time takes place by delaying the transmitted packets on the sender side. A key aspect in covert timing channels is to find the threshold of packet delay that can accurately distinguish covert traffic from legitimate traffic. Based on that we can assess the level of dangerous of security threats or the quality of transferred sensitive information secretly. In this paper, we study the inter-arrival time behavior of covert timing channels in two different network configurations based on statistical metrics, in addition we investigate the packet delaying threshold value. Our experiments show that the threshold is approximately equal to or greater than double the mean of legitimate inter-arrival times. In this case covert timing channels become detectable as strong anomalies. Full article
(This article belongs to the Special Issue Machine Learning for IoT Applications and Digital Twins)
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24 pages, 11694 KiB  
Article
A Game-Based Rehabilitation System for Upper-Limb Cerebral Palsy: A Feasibility Study
by Mohammad I. Daoud, Abdullah Alhusseini, Mostafa Z. Ali and Rami Alazrai
Sensors 2020, 20(8), 2416; https://doi.org/10.3390/s20082416 - 24 Apr 2020
Cited by 13 | Viewed by 3678
Abstract
Game-based rehabilitation systems provide an effective tool to engage cerebral palsy patients in physical exercises within an exciting and entertaining environment. A crucial factor to ensure the effectiveness of game-based rehabilitation systems is to assess the correctness of the movements performed by the [...] Read more.
Game-based rehabilitation systems provide an effective tool to engage cerebral palsy patients in physical exercises within an exciting and entertaining environment. A crucial factor to ensure the effectiveness of game-based rehabilitation systems is to assess the correctness of the movements performed by the patient during the game-playing sessions. In this study, we propose a game-based rehabilitation system for upper-limb cerebral palsy that includes three game-based exercises and a computerized assessment method. The game-based exercises aim to engage the participant in shoulder flexion, shoulder horizontal abduction/adduction, and shoulder adduction physical exercises that target the right arm. Human interaction with the game-based rehabilitation system is achieved using a Kinect sensor that tracks the skeleton joints of the participant. The computerized assessment method aims to assess the correctness of the right arm movements during each game-playing session by analyzing the tracking data acquired by the Kinect sensor. To evaluate the performance of the computerized assessment method, two groups of participants volunteered to participate in the game-based exercises. The first group included six cerebral palsy children and the second group included twenty typically developing subjects. For every participant, the computerized assessment method was employed to assess the correctness of the right arm movements in each game-playing session and these computer-based assessments were compared with matching gold standard evaluations provided by an experienced physiotherapist. The results reported in this study suggest the feasibility of employing the computerized assessment method to evaluate the correctness of the right arm movements during the game-playing sessions. Full article
(This article belongs to the Special Issue Smart Sensors for Healthcare and Medical Applications)
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5 pages, 158 KiB  
Editorial
Special Issue “Fibre Optic Sensors for Structural and Geotechnical Monitoring”
by Michele Arturo Caponero
Sensors 2020, 20(8), 2415; https://doi.org/10.3390/s20082415 - 24 Apr 2020
Cited by 5 | Viewed by 2141
Abstract
In this editorial on the special issue “Fibre Optic Sensors for Structural and Geotechnical Monitoring” a review of the contribution papers selected for publication is given. Each paper is briefly summarized, presenting its objective and methods, then a comment is given about the [...] Read more.
In this editorial on the special issue “Fibre Optic Sensors for Structural and Geotechnical Monitoring” a review of the contribution papers selected for publication is given. Each paper is briefly summarized, presenting its objective and methods, then a comment is given about the relevance of the work with respect to the advance and the spreading of the fibre optic technology for monitoring applications. Full article
(This article belongs to the Special Issue Fiber Optic Sensors for Structural and Geotechnical Monitoring)
12 pages, 2237 KiB  
Article
Software Sensor for Airflow Modulation and Noise Detection by Cyclostationary Tools
by Mohamad Alkoussa Dit Albacha, Laurent Rambault, Anas Sakout, Kamel Abed Meraim, Erik Etien, Thierry Doget and Sebastien Cauet
Sensors 2020, 20(8), 2414; https://doi.org/10.3390/s20082414 - 23 Apr 2020
Cited by 1 | Viewed by 2582
Abstract
The paper presents tools to model low speed airflow coming from a turbulent machine. This low speed flow have instabilities who generate noise disturbances in the environment. The aim of the study proposed in this paper, is the using of cyclostationary tools with [...] Read more.
The paper presents tools to model low speed airflow coming from a turbulent machine. This low speed flow have instabilities who generate noise disturbances in the environment. The aim of the study proposed in this paper, is the using of cyclostationary tools with audio signals to model this airflow and detect the noisy frequencies to eliminate this noise. This paper also deals with the extraction in real time of the frequency corresponding to the noise nuisance. This extraction makes it possible to build a software sensor. This software sensor can be used to estimate the air flow rate and also to control a future actuator which will reduce the intensity of the noise nuisance. This paper focuses on the characteristic of the sound signal (property of cyclostationarity) and on the development of a software sensor. The results are established using an experimental setup representative of the physical phenomenon to be characterised. Full article
(This article belongs to the Section Intelligent Sensors)
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13 pages, 3555 KiB  
Article
Performance Evaluation and Compensation Method of Trigger Probes in Measurement Based on the Abbé Principle
by Guoying Ren, Xinghua Qu and Xiangjun Chen
Sensors 2020, 20(8), 2413; https://doi.org/10.3390/s20082413 - 23 Apr 2020
Cited by 4 | Viewed by 3748
Abstract
Trigger probes are widely used in precision manufacturing industries such as coordinate measuring machines (CMM) and high-end computer numerical control(CNC) machine tools for quality control. Their performance and accuracy often determine the measurement results and the quality of the product manufacturing. However, because [...] Read more.
Trigger probes are widely used in precision manufacturing industries such as coordinate measuring machines (CMM) and high-end computer numerical control(CNC) machine tools for quality control. Their performance and accuracy often determine the measurement results and the quality of the product manufacturing. However, because there is no accurate measurement of the trigger force in different directions of the probe, and no special measuring device to calibrate the characteristic parameters of the probe in traditional measurement methods, it is impossible to exactly compensate for the measurement error caused by the trigger force of the probe in the measurement process. The accuracy of the measurement of the equipment can be improved by abiding by the Abbé principle. Thus, in order to better evaluate the performance parameters of the probe and realize the accurate compensation for its errors, this paper presents a method which can directly measure the performance parameters of the trigger probe based on the Abbé measurement principle, expounds the measurement principle, the establishment of the mathematical model, and the calibration system, and finishes with an experimental verification and measurement uncertainty analysis. The experimental results show that this method can obtain the exact calibration errors of the performance parameters of the trigger probe intuitively, realize the compensation for the errors of the probe in the measurement process, and effectively improve the measurement accuracy. Full article
(This article belongs to the Special Issue Sensors for Manufacturing Process Monitoring)
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18 pages, 6959 KiB  
Article
Acoustic Emission Analysis of Corroded Reinforced Concrete Columns under Compressive Loading
by Qiang Li, Xianyu Jin, Dan Wu and Hailong Ye
Sensors 2020, 20(8), 2412; https://doi.org/10.3390/s20082412 - 23 Apr 2020
Cited by 5 | Viewed by 2745
Abstract
In this work, the failure process of non-corroded and corroded reinforced concrete (RC) columns under eccentric compressive loading is studied using the acoustic emission (AE) technique. The results show that reinforcement corrosion considerably affects the mechanical failure process of RC columns. The corrosion [...] Read more.
In this work, the failure process of non-corroded and corroded reinforced concrete (RC) columns under eccentric compressive loading is studied using the acoustic emission (AE) technique. The results show that reinforcement corrosion considerably affects the mechanical failure process of RC columns. The corrosion of reinforcement in RC columns leads to highly active AE signals at the initial stage of loading, in comparison to the non-corroded counterparts. Also, a continuous AE hit pattern with a higher number of cumulative hits is observed for corroded RC columns. The spatial distribution and evolution of AE events indicate that the reinforcement corrosion noticeably accelerates the initiation and propagation of cracking in the RC columns during compressive loading. The AE characteristics of corroded RC columns are in agreement with the macroscopic failure behaviors observed during the damage and failure process. A damage evolution model of corroded RC columns based on the AE parameters is proposed. Full article
(This article belongs to the Section Physical Sensors)
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12 pages, 5032 KiB  
Article
3-D Terrain Node Coverage of Wireless Sensor Network Using Enhanced Black Hole Algorithm
by Jeng-Shyang Pan, Qing-Wei Chai, Shu-Chuan Chu and Ning Wu
Sensors 2020, 20(8), 2411; https://doi.org/10.3390/s20082411 - 23 Apr 2020
Cited by 28 | Viewed by 3174
Abstract
In this paper, a new intelligent computing algorithm named Enhanced Black Hole (EBH) is proposed to which the mutation operation and weight factor are applied. In EBH, several elites are taken as role models instead of only one in the original Black Hole [...] Read more.
In this paper, a new intelligent computing algorithm named Enhanced Black Hole (EBH) is proposed to which the mutation operation and weight factor are applied. In EBH, several elites are taken as role models instead of only one in the original Black Hole (BH) algorithm. The performance of the EBH algorithm is verified by the CEC 2013 test suit, and shows better results than the original BH. In addition, the EBH and other celebrated algorithms can be used to solve node coverage problems of Wireless Sensor Network (WSN) in 3-D terrain with satisfactory performance. Full article
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17 pages, 2170 KiB  
Article
Use of Spectroscopic Techniques for a Rapid and Non-Destructive Monitoring of Thermal Treatments and Storage Time of Sous-Vide Cooked Cod Fillets
by Abdo Hassoun, Janna Cropotova, Turid Rustad, Karsten Heia, Stein-Kato Lindberg and Heidi Nilsen
Sensors 2020, 20(8), 2410; https://doi.org/10.3390/s20082410 - 23 Apr 2020
Cited by 12 | Viewed by 3840
Abstract
In this work, the potential of spectroscopic techniques was studied to investigate heat-induced changes occurring during the application of thermal treatments on cod (Gadus morhua L.) fillets. Vacuum-packed samples were thermally treated in a water bath at 50, 60, 70 and 80 [...] Read more.
In this work, the potential of spectroscopic techniques was studied to investigate heat-induced changes occurring during the application of thermal treatments on cod (Gadus morhua L.) fillets. Vacuum-packed samples were thermally treated in a water bath at 50, 60, 70 and 80 °C for 5 and 10 min, and further stored for one, four, and eight days at 4 ± 1 °C before analysis. Several traditional (including cooking loss, drip loss, texture, protein solubility, protein oxidation, and color) and spectroscopic (fluorescence and diffuse reflectance hyperspectral imaging) measurements were conducted on the same samples. The results showed a decrease in fluorescence intensity with increasing cooking temperature and storage time, while the impact of cooking time was only noticeable at low temperatures. Diffuse reflectance data exhibited a decrease in absorbance, possibly as a result of protein denaturation and increased scattering at higher cooking temperatures. Both fluorescence and diffuse reflectance data were highly correlated with color parameters, whereas moderate correlations were observed with most other traditional parameters. Support vector machine models performed better than partial least square ones for both classification of cod samples cooked at different temperatures and in prediction of the cooking temperature. The best classification result was obtained on fluorescence data, achieving an accuracy of 92.5%, while the prediction models resulted in a root mean square error of prediction of cooking temperature lower than 5 °C. Overall, the classification and prediction models showed good results, indicating that spectroscopic techniques, especially fluorescence hyperspectral imaging, have a high potential for monitoring thermal treatments in cod fillets. Full article
(This article belongs to the Special Issue Fluorescence-Based Sensors)
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11 pages, 5441 KiB  
Article
Measurement for the Thickness of Water Droplets/Film on a Curved Surface with Digital Image Projection (DIP) Technique
by Lingwei Zeng, Hanfeng Wang, Ying Li and Xuhui He
Sensors 2020, 20(8), 2409; https://doi.org/10.3390/s20082409 - 23 Apr 2020
Viewed by 3088
Abstract
Digital image projection (DIP) with traditional vertical calibration cannot be used for measuring the water droplets/film on a curved surface, because significant systematic error will be introduced. An improved DIP technique with normal calibration is proposed in the present paper, including the principles, [...] Read more.
Digital image projection (DIP) with traditional vertical calibration cannot be used for measuring the water droplets/film on a curved surface, because significant systematic error will be introduced. An improved DIP technique with normal calibration is proposed in the present paper, including the principles, operation procedures and analysis of systematic errors, which was successfully applied to measuring the water droplets/film on a curved surface. By comparing the results of laser profiler, traditional DIP, improved DIP and theoretical analysis, advantages of the present improved DIP technique are highlighted. Full article
(This article belongs to the Special Issue Camera as a Smart-Sensor (CaaSS))
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10 pages, 3404 KiB  
Article
The Design of a Frame-Like ZnO FBAR Sensor for Achieving Uniform Mass Sensitivity Distributions
by Xueli Zhao, Zinan Zhao, Bin Wang, Zhenghua Qian and Tingfeng Ma
Sensors 2020, 20(8), 2408; https://doi.org/10.3390/s20082408 - 23 Apr 2020
Cited by 5 | Viewed by 2491
Abstract
In this paper, an infinite circular ZnO thin film bulk acoustic resonator (FBAR) with a frame-like electrode operating at the thickness-extensional (TE) mode is studied. Two-dimensional scalar differential equations established for the problem in the Cartesian coordinate system are successfully solved by transforming [...] Read more.
In this paper, an infinite circular ZnO thin film bulk acoustic resonator (FBAR) with a frame-like electrode operating at the thickness-extensional (TE) mode is studied. Two-dimensional scalar differential equations established for the problem in the Cartesian coordinate system are successfully solved by transforming them into normal Bessel equations and modified Bessel equations in the cylindrical coordinate system. Resonant frequencies and vibration distributions are obtained for this frame-like FBAR sensor. A nearly uniform mass sensitivity distribution in the active area is achieved by designing proper electrode size and mass ratio of the driving electrode to the ZnO film. Numerical results show that compared with the reported ring electrode FBAR sensor, the novel frame-like electrode FBAR can achieve a maximum optimization ratio (up to 97.90%) on the uniformity of the mass sensitivity distribution in the active area under the same structural parameters, which is also higher than the optimization ratio 77.63% obtained by the reported double-ring electrode design. Moreover, the mechanism to achieve a very uniform mass sensitivity distribution in the active area by the frame-like electrode is explained in detail according to dispersion curves. Namely, when the resonant frequency of the FBAR sensor is close to the cut-off frequency of the active region in the dispersion curve, the mass sensitivity distribution is nearly uniform. These conclusions provide a theoretical guidance for the design and optimization of ZnO FBAR mass sensors with high performance. Full article
(This article belongs to the Special Issue Surface Acoustic Wave and Bulk Acoustic Wave Sensors 2019)
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12 pages, 1574 KiB  
Article
KickStat: A Coin-Sized Potentiostat for High-Resolution Electrochemical Analysis
by Orlando S. Hoilett, Jenna F. Walker, Bethany M. Balash, Nicholas J. Jaras, Sriram Boppana and Jacqueline C. Linnes
Sensors 2020, 20(8), 2407; https://doi.org/10.3390/s20082407 - 23 Apr 2020
Cited by 48 | Viewed by 11949
Abstract
The demand for wearable and point-of-care devices has led to an increase in electrochemical sensor development to measure an ever-increasing array of biological molecules. In order to move from the benchtop to truly portable devices, the development of new biosensors requires miniaturized instrumentation [...] Read more.
The demand for wearable and point-of-care devices has led to an increase in electrochemical sensor development to measure an ever-increasing array of biological molecules. In order to move from the benchtop to truly portable devices, the development of new biosensors requires miniaturized instrumentation capable of making highly sensitive amperometric measurements. To meet this demand, we have developed KickStat, a miniaturized potentiostat that combines the small size of the integrated Texas Instruments LMP91000 potentiostat chip (Texas Instruments, Dallas, TX, USA) with the processing power of the ARM Cortex-M0+ SAMD21 microcontroller (Microchip Technology, Chandler, AZ, USA) on a custom-designed 21.6 mm by 20.3 mm circuit board. By incorporating onboard signal processing via the SAMD21, we achieve 1 mV voltage increment resolution and an instrumental limit of detection of 4.5 nA in a coin-sized form factor. This elegant engineering solution allows for high-resolution electrochemical analysis without requiring extensive circuitry. We measured the faradaic current of an anti-cocaine aptamer using cyclic voltammetry and square wave voltammetry and demonstrated that KickStat’s response was within 0.6% of a high-end benchtop potentiostat. To further support others in electrochemical biosensors development, we have made KickStat’s design and firmware available in an online GitHub repository. Full article
(This article belongs to the Special Issue Amperometric Sensing)
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