Pub Date : 2020-10-25DOI: 10.1109/SENSORS47125.2020.9278884
B. B. Atitallah, Muhammed Bilal Abbasi, Rim Barioul, D. Bouchaala, N. Derbel, O. Kanoun
The tracking and prediction of gestures present a high interest in many applications such as Prosthesis control, robotic tele manipulation, and rehabilitation. The common challenge thereby is the acquisition of suitable signals related to muscles constructions and to identify the corresponding gestures. In this paper, an measurement band based on 8 FSR sensors is proposed for the monitoring of the forearm surface force distribution as a basis for detecting muscle contractions related to gesture. A measurement system realizing simultaneous data acquisition of all sensors has been developed based on Bit-banging over a SPI communication protocol in a Raspberry pi 3 B+ board and 8 external ADSs. To build a data basis, ten healthy male volunteers were asked to perform 11 gestures belonging to American Sign Language numbers (from 0 to 10). For a real time classification, an algorithm is developed based on the Extreme Learning Machine method. The results demonstrate the feasibility of monitoring 8 sensor values simultaneously every 6 ms. The classification accuracy reached 90.09% for all tests.
{"title":"Simultaneous Pressure Sensors Monitoring System for Hand Gestures Recognition","authors":"B. B. Atitallah, Muhammed Bilal Abbasi, Rim Barioul, D. Bouchaala, N. Derbel, O. Kanoun","doi":"10.1109/SENSORS47125.2020.9278884","DOIUrl":"https://doi.org/10.1109/SENSORS47125.2020.9278884","url":null,"abstract":"The tracking and prediction of gestures present a high interest in many applications such as Prosthesis control, robotic tele manipulation, and rehabilitation. The common challenge thereby is the acquisition of suitable signals related to muscles constructions and to identify the corresponding gestures. In this paper, an measurement band based on 8 FSR sensors is proposed for the monitoring of the forearm surface force distribution as a basis for detecting muscle contractions related to gesture. A measurement system realizing simultaneous data acquisition of all sensors has been developed based on Bit-banging over a SPI communication protocol in a Raspberry pi 3 B+ board and 8 external ADSs. To build a data basis, ten healthy male volunteers were asked to perform 11 gestures belonging to American Sign Language numbers (from 0 to 10). For a real time classification, an algorithm is developed based on the Extreme Learning Machine method. The results demonstrate the feasibility of monitoring 8 sensor values simultaneously every 6 ms. The classification accuracy reached 90.09% for all tests.","PeriodicalId":338240,"journal":{"name":"2020 IEEE Sensors","volume":"160 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134042295","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-10-25DOI: 10.1109/SENSORS47125.2020.9278610
M. Carandell, D. Toma, J. Río, M. Gasulla
Maximum Power Point Tracking (MPPT) techniques for low-power pendulum-type Wave Energy Converters were evaluated. A Kinetic Energy Harvester previously designed, together with a Power Management Unit, were tested on a linear shaker to compare three MPPT techniques, the Constant Voltage versus two variants of the Fractional Open Circuit Voltage (FOCV). Results show a 25% improvement on the scavenged energy with one of the proposed FOCV techniques with respect to the other ones.
{"title":"Optimum MPPT Strategy for Low-Power Pendulum-Type Wave Energy Converters","authors":"M. Carandell, D. Toma, J. Río, M. Gasulla","doi":"10.1109/SENSORS47125.2020.9278610","DOIUrl":"https://doi.org/10.1109/SENSORS47125.2020.9278610","url":null,"abstract":"Maximum Power Point Tracking (MPPT) techniques for low-power pendulum-type Wave Energy Converters were evaluated. A Kinetic Energy Harvester previously designed, together with a Power Management Unit, were tested on a linear shaker to compare three MPPT techniques, the Constant Voltage versus two variants of the Fractional Open Circuit Voltage (FOCV). Results show a 25% improvement on the scavenged energy with one of the proposed FOCV techniques with respect to the other ones.","PeriodicalId":338240,"journal":{"name":"2020 IEEE Sensors","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131808807","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-10-25DOI: 10.1109/SENSORS47125.2020.9278820
Arun Arun, S. Bhadra
This paper presents a smart eyeglass to monitor temporalis muscle movement for automatic food intake monitoring. The temple of the eyeglass is equipped with an accelerometer based sensing platform. The eyeglass is evaluated using four different classifiers for detection of chewing events during free-living studies. In addition, the in-lab studies are designed with two classifiers to detect chewing events and differentiate between various consumed foods based on their hardness. The system can achieve 86% accuracy, 82.14% precision, 85.49% recall and 82.23% F1-score for chewing detection in free living. For in lab studies, the system achieves 99.37% accuracy to detect chewing and 88% accuracy to differentiate between food based on hardness. The high accuracy results in both free living and in lab tests indicate that this eyeglass can be a preferable wearable to record food intake habits of people.
{"title":"An Accelerometer based EyeGlass to Monitor Food Intake in Free-Living and Lab Environment","authors":"Arun Arun, S. Bhadra","doi":"10.1109/SENSORS47125.2020.9278820","DOIUrl":"https://doi.org/10.1109/SENSORS47125.2020.9278820","url":null,"abstract":"This paper presents a smart eyeglass to monitor temporalis muscle movement for automatic food intake monitoring. The temple of the eyeglass is equipped with an accelerometer based sensing platform. The eyeglass is evaluated using four different classifiers for detection of chewing events during free-living studies. In addition, the in-lab studies are designed with two classifiers to detect chewing events and differentiate between various consumed foods based on their hardness. The system can achieve 86% accuracy, 82.14% precision, 85.49% recall and 82.23% F1-score for chewing detection in free living. For in lab studies, the system achieves 99.37% accuracy to detect chewing and 88% accuracy to differentiate between food based on hardness. The high accuracy results in both free living and in lab tests indicate that this eyeglass can be a preferable wearable to record food intake habits of people.","PeriodicalId":338240,"journal":{"name":"2020 IEEE Sensors","volume":"79 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132242228","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-10-25DOI: 10.1109/SENSORS47125.2020.9278765
Alexander C. Abad, Daniel Swarup, David Reid, Anuradha Ranasinghe
This study presents a novel 4×4 fingertip tactile matrix actuator that can be strapped on a finger. It is made from Dot Braille cells purchased from Dot Inc., Korea. The prototype has a surface area of 1.08 cm2 with a pin pitch of 2.6 mm and operates at 5V supply. Each tactile pin can be controlled using an h-bridge motor driver and Arduino microcontroller. The tactile matrix is coupled with a tactile matrix simulator that scans a binary image or edges of an image using Canny edge detector. The simulator has 16 sections corresponding to the 16 actuator pins. The integration of the simulator to the hardware prototype allows the user to feel a binary image of a plane geometric figure or to feel the edges of an image as the scanning region of interest (ROI) moves across the visual screen. This fingertip tactile matrix display would be useful in many Virtual Reality (VR) applications to provide tactile feedback on the textures of virtual objects. Therefore, the authors suggest that this device will be beneficial in many applications such as virtual surgery, virtual fashion, remote sensing, and telerobotics.
{"title":"4×4 Fingertip Tactile Matrix Actuator with Edge Detection Scanning ROI Simulator","authors":"Alexander C. Abad, Daniel Swarup, David Reid, Anuradha Ranasinghe","doi":"10.1109/SENSORS47125.2020.9278765","DOIUrl":"https://doi.org/10.1109/SENSORS47125.2020.9278765","url":null,"abstract":"This study presents a novel 4×4 fingertip tactile matrix actuator that can be strapped on a finger. It is made from Dot Braille cells purchased from Dot Inc., Korea. The prototype has a surface area of 1.08 cm2 with a pin pitch of 2.6 mm and operates at 5V supply. Each tactile pin can be controlled using an h-bridge motor driver and Arduino microcontroller. The tactile matrix is coupled with a tactile matrix simulator that scans a binary image or edges of an image using Canny edge detector. The simulator has 16 sections corresponding to the 16 actuator pins. The integration of the simulator to the hardware prototype allows the user to feel a binary image of a plane geometric figure or to feel the edges of an image as the scanning region of interest (ROI) moves across the visual screen. This fingertip tactile matrix display would be useful in many Virtual Reality (VR) applications to provide tactile feedback on the textures of virtual objects. Therefore, the authors suggest that this device will be beneficial in many applications such as virtual surgery, virtual fashion, remote sensing, and telerobotics.","PeriodicalId":338240,"journal":{"name":"2020 IEEE Sensors","volume":"65 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134156928","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-10-25DOI: 10.1109/SENSORS47125.2020.9278586
Daqian Cheng, Haowen Shi, M. Schwerin, Michelle Crivella, Lu Li, H. Choset
High-precision inspection and metrology in short-range and tight spaces are challenging due to the lack of a commercial off-the-shelf (COTS) 3D scanner that is compact and does not rely on any external infrastructure (e.g., fiducial markers, motion-capture cameras, or laser tracking interferometer) to provide positioning or localization support. This paper presents a hardware and software design framework for creating a low-cost, miniature, yet intelligent sensor that is able to capture visual imagery, reconstruct 3D geometry, and most importantly, perform Simultaneous Localization and Mapping (SLAM) without sensory feedback from external devices. We further present an example sensor design that follows this framework, with experiments to evaluate and compare the sensor performance against a state-of-the-art COTS sensor, under both feature-sparse and feature-dense scenarios to simulate industrial and household 3D scanning application scenarios.
{"title":"A Compact and Infrastructure-free Confined Space Sensor for 3D Scanning and SLAM","authors":"Daqian Cheng, Haowen Shi, M. Schwerin, Michelle Crivella, Lu Li, H. Choset","doi":"10.1109/SENSORS47125.2020.9278586","DOIUrl":"https://doi.org/10.1109/SENSORS47125.2020.9278586","url":null,"abstract":"High-precision inspection and metrology in short-range and tight spaces are challenging due to the lack of a commercial off-the-shelf (COTS) 3D scanner that is compact and does not rely on any external infrastructure (e.g., fiducial markers, motion-capture cameras, or laser tracking interferometer) to provide positioning or localization support. This paper presents a hardware and software design framework for creating a low-cost, miniature, yet intelligent sensor that is able to capture visual imagery, reconstruct 3D geometry, and most importantly, perform Simultaneous Localization and Mapping (SLAM) without sensory feedback from external devices. We further present an example sensor design that follows this framework, with experiments to evaluate and compare the sensor performance against a state-of-the-art COTS sensor, under both feature-sparse and feature-dense scenarios to simulate industrial and household 3D scanning application scenarios.","PeriodicalId":338240,"journal":{"name":"2020 IEEE Sensors","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134174070","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-10-25DOI: 10.1109/SENSORS47125.2020.9278845
D. Vatanparvar, A. Shkel
In order to improve the angular rate sensitivity in Coriolis Vibratory Gyroscopes (CVG), an electrostatic frequency tuning mechanism is often used to reduce the split in the resonant frequency of gyroscopes. In this paper, the effect of the amplitude-frequency coupling, as a ramification of the electrostatic frequency tuning, on gyroscope operation in the open-loop angular rate mode is studied. We demonstrate that the amplitude-frequency coupling results in instability in the resonant frequency along the drive axis which degrades the noise performance of a CVG. We present a model that describes the non-linear dynamics of a gyroscope along the drive axis, including the amplitude-frequency coupling terms beyond the Duffing and quintic nonlinearity. Analytical equations were derived to estimate the correlation between frequency noise and amplitude noise. The non-linear electrostatic spring stiffness and the frequency noise in a Dual Foucault Pendulum (DFP) gyroscope were characterized and a good agreement with the predictive analytical model was observed. Our study suggests that as the required tuning voltage for mode-matching is increased, the frequency stability in the gyroscope degrades and the quadrature noise limits the noise performance of the gyroscope. In the case of the DFP gyroscope, we demonstrated that a reduction of the drive amplitude, which reduces the amplitude-frequency coupling, resulted in a 3 times improvement in the Angle Random Walk (ARW) and Bias Instability (BI).
{"title":"Instabilities due to Electrostatic Tuning of Frequency-Split in Coriolis Vibratory Gyroscopes","authors":"D. Vatanparvar, A. Shkel","doi":"10.1109/SENSORS47125.2020.9278845","DOIUrl":"https://doi.org/10.1109/SENSORS47125.2020.9278845","url":null,"abstract":"In order to improve the angular rate sensitivity in Coriolis Vibratory Gyroscopes (CVG), an electrostatic frequency tuning mechanism is often used to reduce the split in the resonant frequency of gyroscopes. In this paper, the effect of the amplitude-frequency coupling, as a ramification of the electrostatic frequency tuning, on gyroscope operation in the open-loop angular rate mode is studied. We demonstrate that the amplitude-frequency coupling results in instability in the resonant frequency along the drive axis which degrades the noise performance of a CVG. We present a model that describes the non-linear dynamics of a gyroscope along the drive axis, including the amplitude-frequency coupling terms beyond the Duffing and quintic nonlinearity. Analytical equations were derived to estimate the correlation between frequency noise and amplitude noise. The non-linear electrostatic spring stiffness and the frequency noise in a Dual Foucault Pendulum (DFP) gyroscope were characterized and a good agreement with the predictive analytical model was observed. Our study suggests that as the required tuning voltage for mode-matching is increased, the frequency stability in the gyroscope degrades and the quadrature noise limits the noise performance of the gyroscope. In the case of the DFP gyroscope, we demonstrated that a reduction of the drive amplitude, which reduces the amplitude-frequency coupling, resulted in a 3 times improvement in the Angle Random Walk (ARW) and Bias Instability (BI).","PeriodicalId":338240,"journal":{"name":"2020 IEEE Sensors","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133896752","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-10-25DOI: 10.1109/SENSORS47125.2020.9278863
Fangzhi Mu, Xiao Gu, Yao Guo, B. Lo
Inertial measurement units (IMUs) together with advanced machine learning algorithms have enabled pervasive gait analysis. However, the worn positions of IMUs can be varied due to movements, and they are difficult to standardize across different trials, causing signal variations. Such variation contributes to a bias in the underlying distribution of training and testing data, and hinder the generalization ability of a computational gait analysis model. In this paper, we propose a position-independent IMU based gait analysis framework based on unsupervised domain adaptation. It is based on transferring knowledge from the trained data positions to a novel position without labels. Our framework was validated on gait event detection and pathological gait pattern recognition tasks based on different computational models and achieved consistently high performance on both tasks.
{"title":"Unsupervised Domain Adaptation for Position-Independent IMU Based Gait Analysis","authors":"Fangzhi Mu, Xiao Gu, Yao Guo, B. Lo","doi":"10.1109/SENSORS47125.2020.9278863","DOIUrl":"https://doi.org/10.1109/SENSORS47125.2020.9278863","url":null,"abstract":"Inertial measurement units (IMUs) together with advanced machine learning algorithms have enabled pervasive gait analysis. However, the worn positions of IMUs can be varied due to movements, and they are difficult to standardize across different trials, causing signal variations. Such variation contributes to a bias in the underlying distribution of training and testing data, and hinder the generalization ability of a computational gait analysis model. In this paper, we propose a position-independent IMU based gait analysis framework based on unsupervised domain adaptation. It is based on transferring knowledge from the trained data positions to a novel position without labels. Our framework was validated on gait event detection and pathological gait pattern recognition tasks based on different computational models and achieved consistently high performance on both tasks.","PeriodicalId":338240,"journal":{"name":"2020 IEEE Sensors","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122155504","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-10-25DOI: 10.1109/SENSORS47125.2020.9278945
S. Bader, Xinyv Ma, B. Oelmann
Ambient light measurements and an understanding of light conditions are essential for the accurate estimation of available energy in indoor photovoltaic applications. Light conditions may vary with respect to illumination intensity, duration, and spectral composition. Although the importance of the light spectrum has been documented in laboratory studies, previous distributed measurement methods are limited to intensity as a measure for output power. In this paper, we propose and implement a system for distributed measurement of light conditions that includes spectral information with low overhead. Based on a prototype implementation, we demonstrate that the illumination intensity and spectrum varies considerably over time and space, which confirms the demand for the proposed solution. We, moreover, characterize the energy consumption of the prototype, demonstrating that long-term, unattended characterization of light conditions can be achieved.
{"title":"Distributed Measurement of Light Conditions for Indoor Photovoltaic Applications","authors":"S. Bader, Xinyv Ma, B. Oelmann","doi":"10.1109/SENSORS47125.2020.9278945","DOIUrl":"https://doi.org/10.1109/SENSORS47125.2020.9278945","url":null,"abstract":"Ambient light measurements and an understanding of light conditions are essential for the accurate estimation of available energy in indoor photovoltaic applications. Light conditions may vary with respect to illumination intensity, duration, and spectral composition. Although the importance of the light spectrum has been documented in laboratory studies, previous distributed measurement methods are limited to intensity as a measure for output power. In this paper, we propose and implement a system for distributed measurement of light conditions that includes spectral information with low overhead. Based on a prototype implementation, we demonstrate that the illumination intensity and spectrum varies considerably over time and space, which confirms the demand for the proposed solution. We, moreover, characterize the energy consumption of the prototype, demonstrating that long-term, unattended characterization of light conditions can be achieved.","PeriodicalId":338240,"journal":{"name":"2020 IEEE Sensors","volume":"278 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132410695","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-10-25DOI: 10.1109/SENSORS47125.2020.9278658
Pascal E. Fortin, Jeffrey R. Blum, Antoine Weill--Duflos, J. Cooperstock
Commercial smartwatches and fitness trackers are integrating increasingly advanced physiological sensors. For optimal performance, such devices need to be firmly coupled to the body, yet also remain comfortable when worn for extended periods of time. Existing solutions for measuring the contact force in order to ensure it is in an optimal tightness range typically depend on direct force measurement, but this adds hardware, and therefore cost, to the devices. This paper presents a novel method for estimating contact force by using only an optical heart rate sensor, as already found in many wearable devices. Initial tests indicate that the proposed method can estimate contact force with a mean absolute error of 0.36N, on par with FSRs. This new approach has the potential to expand the utility of existing sensors for both researchers and end-users, with anticipated applications not only in optimizing physiological sensing, but also in haptic information delivery.
{"title":"Contact Force Estimation from Raw Photoplethysmogram Signal","authors":"Pascal E. Fortin, Jeffrey R. Blum, Antoine Weill--Duflos, J. Cooperstock","doi":"10.1109/SENSORS47125.2020.9278658","DOIUrl":"https://doi.org/10.1109/SENSORS47125.2020.9278658","url":null,"abstract":"Commercial smartwatches and fitness trackers are integrating increasingly advanced physiological sensors. For optimal performance, such devices need to be firmly coupled to the body, yet also remain comfortable when worn for extended periods of time. Existing solutions for measuring the contact force in order to ensure it is in an optimal tightness range typically depend on direct force measurement, but this adds hardware, and therefore cost, to the devices. This paper presents a novel method for estimating contact force by using only an optical heart rate sensor, as already found in many wearable devices. Initial tests indicate that the proposed method can estimate contact force with a mean absolute error of 0.36N, on par with FSRs. This new approach has the potential to expand the utility of existing sensors for both researchers and end-users, with anticipated applications not only in optimizing physiological sensing, but also in haptic information delivery.","PeriodicalId":338240,"journal":{"name":"2020 IEEE Sensors","volume":"144 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134064135","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-10-25DOI: 10.1109/SENSORS47125.2020.9278642
J. Juillard, A. Mostafa, Pietro M. Ferreira, Manon Gouspy, M. Kraft
In this paper, we propose an alternative output metric for amplitude-modulated resonant sensors based on weakly-coupled resonators. The analog-to-digital conversion of this output metric is less demanding than that of the amplitude ratio, because of its boundedness and of its better linearity. In particular, we show that this output metric provides a perfectly linear measurement of the quantity of interest when a specific resonant sensor architecture based on mutually-injection locked oscillators (MILOs) is used. These results are supported by analytical calculations and by experimental data.
{"title":"A highly-linear, integration-compatible output metric for amplitude-modulated resonant sensors based on weakly-coupled resonators","authors":"J. Juillard, A. Mostafa, Pietro M. Ferreira, Manon Gouspy, M. Kraft","doi":"10.1109/SENSORS47125.2020.9278642","DOIUrl":"https://doi.org/10.1109/SENSORS47125.2020.9278642","url":null,"abstract":"In this paper, we propose an alternative output metric for amplitude-modulated resonant sensors based on weakly-coupled resonators. The analog-to-digital conversion of this output metric is less demanding than that of the amplitude ratio, because of its boundedness and of its better linearity. In particular, we show that this output metric provides a perfectly linear measurement of the quantity of interest when a specific resonant sensor architecture based on mutually-injection locked oscillators (MILOs) is used. These results are supported by analytical calculations and by experimental data.","PeriodicalId":338240,"journal":{"name":"2020 IEEE Sensors","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134438121","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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