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State-of-the-Art Sensors Technology in Canada 2017

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "State-of-the-Art Sensors Technologies".

Deadline for manuscript submissions: closed (31 May 2017) | Viewed by 182637

Special Issue Editors

Department of Electrical and Computer Engineering, University of Alberta, Edmonton, AB T6G 2V4, Canada
Interests: nanomechanical and piezoelectric devices for biosensing applications; bacteriophage-based platforms for detection of bacteria
Special Issues, Collections and Topics in MDPI journals
Department of Mechanical Engineering, University of Waterloo, Waterloo, ON, Canada
Interests: sensor arrays; adaptive estimation; sensor fusion; mechatronic systems; vehicle systems; sensor networks; sensor localization
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The aim of this Special Issue is to provide a comprehensive overview on the state-of-the-art sensor technology of Canada. Research articles are invited, which will provide a consolidated, up-to-date perspective in this area. The Special Issue will publish full research, review, and other highly-rated manuscripts addressing the above aim. Potential topics include, but are not limited to:

  • Biosensors
  • Chemical sensors
  • Physical sensors
  • NEMS/MEMS sensors
  • Sensor arrays and networks
  • Automotive applications
  • Aerospace applications
  • Advanced manufacturing applications
  • Environmental applications
  • Biomedical and human assistive applications


Prof. Dr. Stephane Evoy
Prof. Dr. Baris Fidan
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • biosensors
  • chemical sensors
  • physical sensors
  • sensor networks
  • remote sensors

Published Papers (17 papers)

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Research

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3091 KiB  
Article
Augmented Reality as a Telemedicine Platform for Remote Procedural Training
by Shiyao Wang, Michael Parsons, Jordan Stone-McLean, Peter Rogers, Sarah Boyd, Kristopher Hoover, Oscar Meruvia-Pastor, Minglun Gong and Andrew Smith
Sensors 2017, 17(10), 2294; https://doi.org/10.3390/s17102294 - 10 Oct 2017
Cited by 147 | Viewed by 12376
Abstract
Traditionally, rural areas in many countries are limited by a lack of access to health care due to the inherent challenges associated with recruitment and retention of healthcare professionals. Telemedicine, which uses communication technology to deliver medical services over distance, is an economical [...] Read more.
Traditionally, rural areas in many countries are limited by a lack of access to health care due to the inherent challenges associated with recruitment and retention of healthcare professionals. Telemedicine, which uses communication technology to deliver medical services over distance, is an economical and potentially effective way to address this problem. In this research, we develop a new telepresence application using an Augmented Reality (AR) system. We explore the use of the Microsoft HoloLens to facilitate and enhance remote medical training. Intrinsic advantages of AR systems enable remote learners to perform complex medical procedures such as Point of Care Ultrasound (PoCUS) without visual interference. This research uses the HoloLens to capture the first-person view of a simulated rural emergency room (ER) through mixed reality capture (MRC) and serves as a novel telemedicine platform with remote pointing capabilities. The mentor’s hand gestures are captured using a Leap Motion and virtually displayed in the AR space of the HoloLens. To explore the feasibility of the developed platform, twelve novice medical trainees were guided by a mentor through a simulated ultrasound exploration in a trauma scenario, as part of a pilot user study. The study explores the utility of the system from the trainees, mentor, and objective observers’ perspectives and compares the findings to that of a more traditional multi-camera telemedicine solution. The results obtained provide valuable insight and guidance for the development of an AR-supported telemedicine platform. Full article
(This article belongs to the Special Issue State-of-the-Art Sensors Technology in Canada 2017)
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Article
Using Impedance Measurements to Characterize Surface Modified with Gold Nanoparticles
by Scott MacKay, Gaser N. Abdelrasoul, Marcus Tamura, Donghai Lin, Zhimin Yan and Jie Chen
Sensors 2017, 17(9), 2141; https://doi.org/10.3390/s17092141 - 18 Sep 2017
Cited by 12 | Viewed by 8056
Abstract
With the increased practice of preventative healthcare to help reduce costs worldwide, sensor technology improvement is vital to patient care. Point-of-care (POC) diagnostics can reduce time and lower labor in testing, and can effectively avoid transporting costs because of portable designs. Label-free detection [...] Read more.
With the increased practice of preventative healthcare to help reduce costs worldwide, sensor technology improvement is vital to patient care. Point-of-care (POC) diagnostics can reduce time and lower labor in testing, and can effectively avoid transporting costs because of portable designs. Label-free detection allows for greater versatility in the detection of biological molecules. Here, we describe the use of an impedance-based POC biosensor that can detect changes in the surface modification of a micro-fabricated chip using impedance spectroscopy. Gold nanoparticles (GNPs) have been employed to evaluate the sensing ability of our new chip using impedance measurements. Furthermore, we used impedance measurements to monitor surface functionalization progress on the sensor’s interdigitated electrodes (IDEs). Electrodes made from aluminum and gold were employed and the results were analyzed to compare the impact of electrode material. GNPs coated with mercaptoundecanoic acid were also used as a model of biomolecules to greatly enhance chemical affinity to the silicon substrate. The portable sensor can be used as an alternative technology to ELISA (enzyme-linked immunosorbent assays) and polymerase chain reaction (PCR)-based techniques. This system has advantages over PCR and ELISA both in the amount of time required for testing and the ease of use of our sensor. With other techniques, larger, expensive equipment must be utilized in a lab environment, and procedures have to be carried out by trained professionals. The simplicity of our sensor system can lead to an automated and portable sensing system. Full article
(This article belongs to the Special Issue State-of-the-Art Sensors Technology in Canada 2017)
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17812 KiB  
Article
Automated Water Quality Survey and Evaluation Using an IoT Platform with Mobile Sensor Nodes
by Teng Li, Min Xia, Jiahong Chen, Yuanjie Zhao and Clarence De Silva
Sensors 2017, 17(8), 1735; https://doi.org/10.3390/s17081735 - 28 Jul 2017
Cited by 34 | Viewed by 8803
Abstract
An Internet of Things (IoT) platform with capabilities of sensing, data processing, and wireless communication has been deployed to support remote aquatic environmental monitoring. In this paper, the design and development of an IoT platform with multiple Mobile Sensor Nodes (MSN) for the [...] Read more.
An Internet of Things (IoT) platform with capabilities of sensing, data processing, and wireless communication has been deployed to support remote aquatic environmental monitoring. In this paper, the design and development of an IoT platform with multiple Mobile Sensor Nodes (MSN) for the spatiotemporal quality evaluation of surface water is presented. A survey planner is proposed to distribute the Sampling Locations of Interest (SLoIs) over the study area and generate paths for MSNs to visit the SLoIs, given the limited energy and time budgets. The SLoIs are chosen based on a cellular decomposition that is composed of uniform hexagonal cells. They are visited by the MSNs along a path ring generated by a planning approach that uses a spanning tree. For quality evaluation, an Online Water Quality Index (OLWQI) is developed to interpret the large quantities of online measurements. The index formulations are modified by a state-of-the-art index, the CCME WQI, which has been developed by the Canadian Council of Ministers of Environment (CCME) for off-line indexing. The proposed index has demonstrated effective and reliable performance in online indexing a large volume of measurements of water quality parameters. The IoT platform is deployed in the field, and its performance is demonstrated and discussed in this paper. Full article
(This article belongs to the Special Issue State-of-the-Art Sensors Technology in Canada 2017)
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Article
Surface Estimation for Microwave Imaging
by Douglas Kurrant, Jeremie Bourqui and Elise Fear
Sensors 2017, 17(7), 1658; https://doi.org/10.3390/s17071658 - 19 Jul 2017
Cited by 27 | Viewed by 4647
Abstract
Biomedical imaging and sensing applications in many scenarios demand accurate surface estimation from a sparse set of noisy measurements. These measurements may arise from a variety of sensing modalities, including laser or electromagnetic samples of an object’s surface. We describe a state-of-the-art microwave [...] Read more.
Biomedical imaging and sensing applications in many scenarios demand accurate surface estimation from a sparse set of noisy measurements. These measurements may arise from a variety of sensing modalities, including laser or electromagnetic samples of an object’s surface. We describe a state-of-the-art microwave imaging prototype that has sensors to acquire both microwave and laser measurements. The approach developed to translate sparse samples of the breast surface into an accurate estimate of the region of interest is detailed. To evaluate the efficacy of the method, laser and electromagnetic samples are acquired by sensors from three realistic breast models with varying sizes and shapes. A set of metrics is developed to assist with the investigation and demonstrate that the algorithm is able to accurately estimate the shape of a realistic breast phantom when only a sparse set of data are available. Moreover, the algorithm is robust to the presence of measurement noise, and is effective when applied to measurement scans of patients acquired with the prototype. Full article
(This article belongs to the Special Issue State-of-the-Art Sensors Technology in Canada 2017)
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1041 KiB  
Article
Sensing Responses Based on Transfer Characteristics of InAs Nanowire Field-Effect Transistors
by Alex C. Tseng, David Lynall, Igor Savelyev, Marina Blumin, Shiliang Wang and Harry E. Ruda
Sensors 2017, 17(7), 1640; https://doi.org/10.3390/s17071640 - 16 Jul 2017
Cited by 13 | Viewed by 4920
Abstract
Nanowire-based field-effect transistors (FETs) have demonstrated considerable promise for a new generation of chemical and biological sensors. Indium arsenide (InAs), by virtue of its high electron mobility and intrinsic surface accumulation layer of electrons, holds properties beneficial for creating high performance sensors that [...] Read more.
Nanowire-based field-effect transistors (FETs) have demonstrated considerable promise for a new generation of chemical and biological sensors. Indium arsenide (InAs), by virtue of its high electron mobility and intrinsic surface accumulation layer of electrons, holds properties beneficial for creating high performance sensors that can be used in applications such as point-of-care testing for patients diagnosed with chronic diseases. Here, we propose devices based on a parallel configuration of InAs nanowires and investigate sensor responses from measurements of conductance over time and FET characteristics. The devices were tested in controlled concentrations of vapour containing acetic acid, 2-butanone and methanol. After adsorption of analyte molecules, trends in the transient current and transfer curves are correlated with the nature of the surface interaction. Specifically, we observed proportionality between acetic acid concentration and relative conductance change, off current and surface charge density extracted from subthreshold behaviour. We suggest the origin of the sensing response to acetic acid as a two-part, reversible acid-base and redox reaction between acetic acid, InAs and its native oxide that forms slow, donor-like states at the nanowire surface. We further describe a simple model that is able to distinguish the occurrence of physical versus chemical adsorption by comparing the values of the extracted surface charge density. These studies demonstrate that InAs nanowires can produce a multitude of sensor responses for the purpose of developing next generation, multi-dimensional sensor applications. Full article
(This article belongs to the Special Issue State-of-the-Art Sensors Technology in Canada 2017)
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8690 KiB  
Article
Multiport Circular Polarized RFID-Tag Antenna for UHF Sensor Applications
by Jamal Zaid, Abdulhadi Abdulhadi, Arun Kesavan, Yassin Belaizi and Tayeb A. Denidni
Sensors 2017, 17(7), 1576; https://doi.org/10.3390/s17071576 - 05 Jul 2017
Cited by 15 | Viewed by 6734
Abstract
A circular polarized patch antenna for UHF RFID tag-based sensor applications is presented, with the circular polarization (CP) generated by a new antenna shape, an asymmetric stars shaped slotted microstrip patch antenna (CP-ASSSMP). Four stars etched on the patch allow the antenna’s size [...] Read more.
A circular polarized patch antenna for UHF RFID tag-based sensor applications is presented, with the circular polarization (CP) generated by a new antenna shape, an asymmetric stars shaped slotted microstrip patch antenna (CP-ASSSMP). Four stars etched on the patch allow the antenna’s size to be reduced by close to 20%. The proposed antenna is matched with two RFID chips via inductive-loop matching. The first chip is connected to a resistive sensor and acts as a sensor node, and the second is used as a reference node. The proposed antenna is used for two targets, serving as both reference and sensor simultaneously, thereby eliminating the need for a second antenna. Its reader can read the RFID chips at any orientation of the tag due to the CP. The measured reading range is about 25 m with mismatch polarization. The operating frequency band is 902–929 MHz for the two ports, which is covered by the US RFID band, and the axial-ratio bandwidth is about 7 MHz. In addition, the reader can also detect temperature, based on the minimum difference in the power required by the reference and sensor. Full article
(This article belongs to the Special Issue State-of-the-Art Sensors Technology in Canada 2017)
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1652 KiB  
Article
Faller Classification in Older Adults Using Wearable Sensors Based on Turn and Straight-Walking Accelerometer-Based Features
by Dylan Drover, Jennifer Howcroft, Jonathan Kofman and Edward D. Lemaire
Sensors 2017, 17(6), 1321; https://doi.org/10.3390/s17061321 - 07 Jun 2017
Cited by 39 | Viewed by 5636
Abstract
Faller classification in elderly populations can facilitate preventative care before a fall occurs. A novel wearable-sensor based faller classification method for the elderly was developed using accelerometer-based features from straight walking and turns. Seventy-six older individuals (74.15 ± 7.0 years), categorized as prospective [...] Read more.
Faller classification in elderly populations can facilitate preventative care before a fall occurs. A novel wearable-sensor based faller classification method for the elderly was developed using accelerometer-based features from straight walking and turns. Seventy-six older individuals (74.15 ± 7.0 years), categorized as prospective fallers and non-fallers, completed a six-minute walk test with accelerometers attached to their lower legs and pelvis. After segmenting straight and turn sections, cross validation tests were conducted on straight and turn walking features to assess classification performance. The best “classifier model—feature selector” combination used turn data, random forest classifier, and select-5-best feature selector (73.4% accuracy, 60.5% sensitivity, 82.0% specificity, and 0.44 Matthew’s Correlation Coefficient (MCC)). Using only the most frequently occurring features, a feature subset (minimum of anterior-posterior ratio of even/odd harmonics for right shank, standard deviation (SD) of anterior left shank acceleration SD, SD of mean anterior left shank acceleration, maximum of medial-lateral first quartile of Fourier transform (FQFFT) for lower back, maximum of anterior-posterior FQFFT for lower back) achieved better classification results, with 77.3% accuracy, 66.1% sensitivity, 84.7% specificity, and 0.52 MCC score. All classification performance metrics improved when turn data was used for faller classification, compared to straight walking data. Combining turn and straight walking features decreased performance metrics compared to turn features for similar classifier model—feature selector combinations. Full article
(This article belongs to the Special Issue State-of-the-Art Sensors Technology in Canada 2017)
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541 KiB  
Article
Scalability Issues for Remote Sensing Infrastructure: A Case Study
by Yang Liu, Sean Picard and Carey Williamson
Sensors 2017, 17(5), 994; https://doi.org/10.3390/s17050994 - 29 Apr 2017
Cited by 2 | Viewed by 4151
Abstract
For the past decade, a team of University of Calgary researchers has operated a large “sensor Web” to collect, analyze, and share scientific data from remote measurement instruments across northern Canada. This sensor Web receives real-time data streams from over a thousand Internet-connected [...] Read more.
For the past decade, a team of University of Calgary researchers has operated a large “sensor Web” to collect, analyze, and share scientific data from remote measurement instruments across northern Canada. This sensor Web receives real-time data streams from over a thousand Internet-connected sensors, with a particular emphasis on environmental data (e.g., space weather, auroral phenomena, atmospheric imaging). Through research collaborations, we had the opportunity to evaluate the performance and scalability of their remote sensing infrastructure. This article reports the lessons learned from our study, which considered both data collection and data dissemination aspects of their system. On the data collection front, we used benchmarking techniques to identify and fix a performance bottleneck in the system’s memory management for TCP data streams, while also improving system efficiency on multi-core architectures. On the data dissemination front, we used passive and active network traffic measurements to identify and reduce excessive network traffic from the Web robots and JavaScript techniques used for data sharing. While our results are from one specific sensor Web system, the lessons learned may apply to other scientific Web sites with remote sensing infrastructure. Full article
(This article belongs to the Special Issue State-of-the-Art Sensors Technology in Canada 2017)
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3106 KiB  
Article
Enhancing the Responsivity of Uncooled Infrared Detectors Using Plasmonics for High-Performance Infrared Spectroscopy
by Amr Shebl Ahmed, Hye Jin Kim, Jinsik Kim, Kyo Seon Hwang and Seonghwan Kim
Sensors 2017, 17(4), 908; https://doi.org/10.3390/s17040908 - 20 Apr 2017
Cited by 12 | Viewed by 6704
Abstract
A lead zirconate titanate (PZT;Pb(Zr0.52Ti0.48)O3) layer embedded infrared (IR) detector decorated with wavelength-selective plasmonic crystals has been investigated for high-performance non-dispersive infrared (NDIR) spectroscopy. A plasmonic IR detector with an enhanced IR absorption band has been designed [...] Read more.
A lead zirconate titanate (PZT;Pb(Zr0.52Ti0.48)O3) layer embedded infrared (IR) detector decorated with wavelength-selective plasmonic crystals has been investigated for high-performance non-dispersive infrared (NDIR) spectroscopy. A plasmonic IR detector with an enhanced IR absorption band has been designed based on numerical simulations, fabricated by conventional microfabrication techniques, and characterized with a broadly tunable quantum cascade laser. The enhanced responsivity of the plasmonic IR detector at specific wavelength band has improved the performance of NDIR spectroscopy and pushed the limit of detection (LOD) by an order of magnitude. In this paper, a 13-fold enhancement in the LOD of a methane gas sensing using NDIR spectroscopy is demonstrated with the plasmonic IR detector. Full article
(This article belongs to the Special Issue State-of-the-Art Sensors Technology in Canada 2017)
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2247 KiB  
Article
Miniaturized FDDA and CMOS Based Potentiostat for Bio-Applications
by Elnaz Ghodsevali, Samuel Morneau-Gamache, Jessy Mathault, Hamza Landari, Élodie Boisselier, Mounir Boukadoum, Benoit Gosselin and Amine Miled
Sensors 2017, 17(4), 810; https://doi.org/10.3390/s17040810 - 10 Apr 2017
Cited by 11 | Viewed by 6502
Abstract
A novel fully differential difference CMOS potentiostat suitable for neurotransmitter sensing is presented. The described architecture relies on a fully differential difference amplifier (FDDA) circuit to detect a wide range of reduction-oxidation currents, while exhibiting low-power consumption and low-noise operation. This is made [...] Read more.
A novel fully differential difference CMOS potentiostat suitable for neurotransmitter sensing is presented. The described architecture relies on a fully differential difference amplifier (FDDA) circuit to detect a wide range of reduction-oxidation currents, while exhibiting low-power consumption and low-noise operation. This is made possible thanks to the fully differential feature of the FDDA, which allows to increase the source voltage swing without the need for additional dedicated circuitry. The FDDA also reduces the number of amplifiers and passive elements in the potentiostat design, which lowers the overall power consumption and noise. The proposed potentiostat was fabricated in 0.18 µm CMOS, with 1.8 V supply voltage. The device achieved 5 µA sensitivity and 0.99 linearity. The input-referred noise was 6.9 µV rms and the flicker noise was negligible. The total power consumption was under 55 µW. The complete system was assembled on a 20 mm × 20 mm platform that includes the potentiostat chip, the electrode terminals and an instrumentation amplifier for redox current buffering, once converted to a voltage by a series resistor. the chip dimensions were 1 mm × 0.5 mm and the other PCB components were off-chip resistors, capacitors and amplifiers for data acquisition. The system was successfully tested with ferricyanide, a stable electroactive compound, and validated with dopamine, a popular neurotransmitter. Full article
(This article belongs to the Special Issue State-of-the-Art Sensors Technology in Canada 2017)
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3584 KiB  
Article
Rapid and Low-Cost CRP Measurement by Integrating a Paper-Based Microfluidic Immunoassay with Smartphone (CRP-Chip)
by Meili Dong, Jiandong Wu, Zimin Ma, Hagit Peretz-Soroka, Michael Zhang, Paul Komenda, Navdeep Tangri, Yong Liu, Claudio Rigatto and Francis Lin
Sensors 2017, 17(4), 684; https://doi.org/10.3390/s17040684 - 26 Mar 2017
Cited by 42 | Viewed by 9316
Abstract
Traditional diagnostic tests for chronic diseases are expensive and require a specialized laboratory, therefore limiting their use for point-of-care (PoC) testing. To address this gap, we developed a method for rapid and low-cost C-reactive protein (CRP) detection from blood by integrating a paper-based [...] Read more.
Traditional diagnostic tests for chronic diseases are expensive and require a specialized laboratory, therefore limiting their use for point-of-care (PoC) testing. To address this gap, we developed a method for rapid and low-cost C-reactive protein (CRP) detection from blood by integrating a paper-based microfluidic immunoassay with a smartphone (CRP-Chip). We chose CRP for this initial development because it is a strong biomarker of prognosis in chronic heart and kidney disease. The microfluidic immunoassay is realized by lateral flow and gold nanoparticle-based colorimetric detection of the target protein. The test image signal is acquired and analyzed using a commercial smartphone with an attached microlens and a 3D-printed chip–phone interface. The CRP-Chip was validated for detecting CRP in blood samples from chronic kidney disease patients and healthy subjects. The linear detection range of the CRP-Chip is up to 2 μg/mL and the detection limit is 54 ng/mL. The CRP-Chip test result yields high reproducibility and is consistent with the standard ELISA kit. A single CRP-Chip can perform the test in triplicate on a single chip within 15 min for less than 50 US cents of material cost. This CRP-Chip with attractive features of low-cost, fast test speed, and integrated easy operation with smartphones has the potential to enable future clinical PoC chronic disease diagnosis and risk stratification by parallel measurements of a panel of protein biomarkers. Full article
(This article belongs to the Special Issue State-of-the-Art Sensors Technology in Canada 2017)
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7520 KiB  
Article
A Comprehensive Analysis on Wearable Acceleration Sensors in Human Activity Recognition
by Majid Janidarmian, Atena Roshan Fekr, Katarzyna Radecka and Zeljko Zilic
Sensors 2017, 17(3), 529; https://doi.org/10.3390/s17030529 - 07 Mar 2017
Cited by 161 | Viewed by 10967
Abstract
Sensor-based motion recognition integrates the emerging area of wearable sensors with novel machine learning techniques to make sense of low-level sensor data and provide rich contextual information in a real-life application. Although Human Activity Recognition (HAR) problem has been drawing the attention of [...] Read more.
Sensor-based motion recognition integrates the emerging area of wearable sensors with novel machine learning techniques to make sense of low-level sensor data and provide rich contextual information in a real-life application. Although Human Activity Recognition (HAR) problem has been drawing the attention of researchers, it is still a subject of much debate due to the diverse nature of human activities and their tracking methods. Finding the best predictive model in this problem while considering different sources of heterogeneities can be very difficult to analyze theoretically, which stresses the need of an experimental study. Therefore, in this paper, we first create the most complete dataset, focusing on accelerometer sensors, with various sources of heterogeneities. We then conduct an extensive analysis on feature representations and classification techniques (the most comprehensive comparison yet with 293 classifiers) for activity recognition. Principal component analysis is applied to reduce the feature vector dimension while keeping essential information. The average classification accuracy of eight sensor positions is reported to be 96.44% ± 1.62% with 10-fold evaluation, whereas accuracy of 79.92% ± 9.68% is reached in the subject-independent evaluation. This study presents significant evidence that we can build predictive models for HAR problem under more realistic conditions, and still achieve highly accurate results. Full article
(This article belongs to the Special Issue State-of-the-Art Sensors Technology in Canada 2017)
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Review

Jump to: Research

3921 KiB  
Review
A Review of Hybrid Fiber-Optic Distributed Simultaneous Vibration and Temperature Sensing Technology and Its Geophysical Applications
by Khalid Miah and David K. Potter
Sensors 2017, 17(11), 2511; https://doi.org/10.3390/s17112511 - 01 Nov 2017
Cited by 81 | Viewed by 8779
Abstract
Distributed sensing systems can transform an optical fiber cable into an array of sensors, allowing users to detect and monitor multiple physical parameters such as temperature, vibration and strain with fine spatial and temporal resolution over a long distance. Fiber-optic distributed acoustic sensing [...] Read more.
Distributed sensing systems can transform an optical fiber cable into an array of sensors, allowing users to detect and monitor multiple physical parameters such as temperature, vibration and strain with fine spatial and temporal resolution over a long distance. Fiber-optic distributed acoustic sensing (DAS) and distributed temperature sensing (DTS) systems have been developed for various applications with varied spatial resolution, and spectral and sensing range. Rayleigh scattering-based phase optical time domain reflectometry (OTDR) for vibration and Raman/Brillouin scattering-based OTDR for temperature and strain measurements have been developed over the past two decades. The key challenge has been to find a methodology that would enable the physical parameters to be determined at any point along the sensing fiber with high sensitivity and spatial resolution, yet within acceptable frequency range for dynamic vibration, and temperature detection. There are many applications, especially in geophysical and mining engineering where simultaneous measurements of vibration and temperature are essential. In this article, recent developments of different hybrid systems for simultaneous vibration, temperature and strain measurements are analyzed based on their operation principles and performance. Then, challenges and limitations of the systems are highlighted for geophysical applications. Full article
(This article belongs to the Special Issue State-of-the-Art Sensors Technology in Canada 2017)
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2986 KiB  
Review
Time-Resolved Diffuse Optical Spectroscopy and Imaging Using Solid-State Detectors: Characteristics, Present Status, and Research Challenges
by Mrwan Alayed and M. Jamal Deen
Sensors 2017, 17(9), 2115; https://doi.org/10.3390/s17092115 - 14 Sep 2017
Cited by 30 | Viewed by 6629
Abstract
Diffuse optical spectroscopy (DOS) and diffuse optical imaging (DOI) are emerging non-invasive imaging modalities that have wide spread potential applications in many fields, particularly for structural and functional imaging in medicine. In this article, we review time-resolved diffuse optical imaging (TR-DOI) systems using [...] Read more.
Diffuse optical spectroscopy (DOS) and diffuse optical imaging (DOI) are emerging non-invasive imaging modalities that have wide spread potential applications in many fields, particularly for structural and functional imaging in medicine. In this article, we review time-resolved diffuse optical imaging (TR-DOI) systems using solid-state detectors with a special focus on Single-Photon Avalanche Diodes (SPADs) and Silicon Photomultipliers (SiPMs). These TR-DOI systems can be categorized into two types based on the operation mode of the detector (free-running or time-gated). For the TR-DOI prototypes, the physical concepts, main components, figures-of-merit of detectors, and evaluation parameters are described. The performance of TR-DOI prototypes is evaluated according to the parameters used in common protocols to test DOI systems particularly basic instrumental performance (BIP). In addition, the potential features of SPADs and SiPMs to improve TR-DOI systems and expand their applications in the foreseeable future are discussed. Lastly, research challenges and future developments for TR-DOI are discussed for each component in the prototype separately and also for the entire system. Full article
(This article belongs to the Special Issue State-of-the-Art Sensors Technology in Canada 2017)
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2104 KiB  
Review
On-Chip High-Finesse Fabry-Perot Microcavities for Optical Sensing and Quantum Information
by Mohammad H. Bitarafan and Ray G. DeCorby
Sensors 2017, 17(8), 1748; https://doi.org/10.3390/s17081748 - 31 Jul 2017
Cited by 46 | Viewed by 9487
Abstract
For applications in sensing and cavity-based quantum computing and metrology, open-access Fabry-Perot cavities—with an air or vacuum gap between a pair of high reflectance mirrors—offer important advantages compared to other types of microcavities. For example, they are inherently tunable using MEMS-based actuation strategies, [...] Read more.
For applications in sensing and cavity-based quantum computing and metrology, open-access Fabry-Perot cavities—with an air or vacuum gap between a pair of high reflectance mirrors—offer important advantages compared to other types of microcavities. For example, they are inherently tunable using MEMS-based actuation strategies, and they enable atomic emitters or target analytes to be located at high field regions of the optical mode. Integration of curved-mirror Fabry-Perot cavities on chips containing electronic, optoelectronic, and optomechanical elements is a topic of emerging importance. Micro-fabrication techniques can be used to create mirrors with small radius-of-curvature, which is a prerequisite for cavities to support stable, small-volume modes. We review recent progress towards chip-based implementation of such cavities, and highlight their potential to address applications in sensing and cavity quantum electrodynamics. Full article
(This article belongs to the Special Issue State-of-the-Art Sensors Technology in Canada 2017)
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20565 KiB  
Review
Novel Flexible Wearable Sensor Materials and Signal Processing for Vital Sign and Human Activity Monitoring
by Amir Servati, Liang Zou, Z. Jane Wang, Frank Ko and Peyman Servati
Sensors 2017, 17(7), 1622; https://doi.org/10.3390/s17071622 - 13 Jul 2017
Cited by 82 | Viewed by 14730
Abstract
Advances in flexible electronic materials and smart textile, along with broad availability of smart phones, cloud and wireless systems have empowered the wearable technologies for significant impact on future of digital and personalized healthcare as well as consumer electronics. However, challenges related to [...] Read more.
Advances in flexible electronic materials and smart textile, along with broad availability of smart phones, cloud and wireless systems have empowered the wearable technologies for significant impact on future of digital and personalized healthcare as well as consumer electronics. However, challenges related to lack of accuracy, reliability, high power consumption, rigid or bulky form factor and difficulty in interpretation of data have limited their wide-scale application in these potential areas. As an important solution to these challenges, we present latest advances in novel flexible electronic materials and sensors that enable comfortable and conformable body interaction and potential for invisible integration within daily apparel. Advances in novel flexible materials and sensors are described for wearable monitoring of human vital signs including, body temperature, respiratory rate and heart rate, muscle movements and activity. We then present advances in signal processing focusing on motion and noise artifact removal, data mining and aspects of sensor fusion relevant to future clinical applications of wearable technology. Full article
(This article belongs to the Special Issue State-of-the-Art Sensors Technology in Canada 2017)
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4307 KiB  
Review
Wearable Sensors for Remote Health Monitoring
by Sumit Majumder, Tapas Mondal and M. Jamal Deen
Sensors 2017, 17(1), 130; https://doi.org/10.3390/s17010130 - 12 Jan 2017
Cited by 779 | Viewed by 53315
Abstract
Life expectancy in most countries has been increasing continually over the several few decades thanks to significant improvements in medicine, public health, as well as personal and environmental hygiene. However, increased life expectancy combined with falling birth rates are expected to engender a [...] Read more.
Life expectancy in most countries has been increasing continually over the several few decades thanks to significant improvements in medicine, public health, as well as personal and environmental hygiene. However, increased life expectancy combined with falling birth rates are expected to engender a large aging demographic in the near future that would impose significant burdens on the socio-economic structure of these countries. Therefore, it is essential to develop cost-effective, easy-to-use systems for the sake of elderly healthcare and well-being. Remote health monitoring, based on non-invasive and wearable sensors, actuators and modern communication and information technologies offers an efficient and cost-effective solution that allows the elderly to continue to live in their comfortable home environment instead of expensive healthcare facilities. These systems will also allow healthcare personnel to monitor important physiological signs of their patients in real time, assess health conditions and provide feedback from distant facilities. In this paper, we have presented and compared several low-cost and non-invasive health and activity monitoring systems that were reported in recent years. A survey on textile-based sensors that can potentially be used in wearable systems is also presented. Finally, compatibility of several communication technologies as well as future perspectives and research challenges in remote monitoring systems will be discussed. Full article
(This article belongs to the Special Issue State-of-the-Art Sensors Technology in Canada 2017)
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