Pub Date : 2020-03-25DOI: 10.1109/FLEPS49123.2020.9239536
Kaize Lin, Jin Cao, Shuo Gao
Acupuncture is one of the most significant therapies of Chinese traditional medical science, and it is now globally utilized for treatment, e.g., pain management. Traditionally, there is no quantification means for storing masters’ skills and examining trainee’s learning effect, hence, strongly limiting the development of acupuncture. To address this issue, in this article, a piezoelectric glove based wearable stress sensing system is presented. Experimental results showcase that through the piezoelectric force sensing glove, key parameters (e.g., peak stress at needle) during performing acupuncture are detected and extracted, potentially improving the learning efficiency of trainees and therefore advancing the progress of acupuncture.
{"title":"A Piezoelectric Force Sensing Glove For Acupuncture Quantification","authors":"Kaize Lin, Jin Cao, Shuo Gao","doi":"10.1109/FLEPS49123.2020.9239536","DOIUrl":"https://doi.org/10.1109/FLEPS49123.2020.9239536","url":null,"abstract":"Acupuncture is one of the most significant therapies of Chinese traditional medical science, and it is now globally utilized for treatment, e.g., pain management. Traditionally, there is no quantification means for storing masters’ skills and examining trainee’s learning effect, hence, strongly limiting the development of acupuncture. To address this issue, in this article, a piezoelectric glove based wearable stress sensing system is presented. Experimental results showcase that through the piezoelectric force sensing glove, key parameters (e.g., peak stress at needle) during performing acupuncture are detected and extracted, potentially improving the learning efficiency of trainees and therefore advancing the progress of acupuncture.","PeriodicalId":101496,"journal":{"name":"2020 IEEE International Conference on Flexible and Printable Sensors and Systems (FLEPS)","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122084691","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 : 2020-03-21DOI: 10.1109/FLEPS49123.2020.9239591
Junliang Chen, Yanning Dai, Shuo Gao
Gait analysis is important in the field of healthcare, due to its close relationship to chronic diseases. With the development of the Internet of Health Things (IoHT), long-term gait monitoring and corresponding analysis can be performed remotely, reducing a patient’s time and traffic cost, while providing doctors more valuable gait information. In this paper, we present a piezoelectric insole gait monitoring system and its use in an IoHT architecture. Through the experimental results, the high detection sensitivity of 54 mN and responsivity of 163 mV/N are achieved, thereby satisfying the need for analyzing various diseases. Furthermore, the assembled system can continuously work for 16 hours, indicating its successful utilization when long-term gait monitoring is required. The presented work provides a feasible means for real-time, long-term, and accurate gait monitoring, prompting the development of gait analysis in the IoHT.
{"title":"A Piezoelectric Flexible Insole System for Gait Monitoring for the Internet of Health Things","authors":"Junliang Chen, Yanning Dai, Shuo Gao","doi":"10.1109/FLEPS49123.2020.9239591","DOIUrl":"https://doi.org/10.1109/FLEPS49123.2020.9239591","url":null,"abstract":"Gait analysis is important in the field of healthcare, due to its close relationship to chronic diseases. With the development of the Internet of Health Things (IoHT), long-term gait monitoring and corresponding analysis can be performed remotely, reducing a patient’s time and traffic cost, while providing doctors more valuable gait information. In this paper, we present a piezoelectric insole gait monitoring system and its use in an IoHT architecture. Through the experimental results, the high detection sensitivity of 54 mN and responsivity of 163 mV/N are achieved, thereby satisfying the need for analyzing various diseases. Furthermore, the assembled system can continuously work for 16 hours, indicating its successful utilization when long-term gait monitoring is required. The presented work provides a feasible means for real-time, long-term, and accurate gait monitoring, prompting the development of gait analysis in the IoHT.","PeriodicalId":101496,"journal":{"name":"2020 IEEE International Conference on Flexible and Printable Sensors and Systems (FLEPS)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130682713","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 : 2020-03-20DOI: 10.1109/FLEPS49123.2020.9239513
Shuo Gao, Mingqi Shao, Rong Guo, A. Nathan
Piezoelectric force touch panels are attractive as human-machine interfaces and 3-dimensional touch sensing in internet of things (IoT) applications. The piezoelectric material has the intrinsic ability to convert mechanical to electrical signals. But the force responsivity issue induced by different touch orientations can be unstable. This paper presents a piezoelectric touch panel that is sensitive to both capacitive and force stimulation. A touch orientation classification technique is developed to calibrate the detected force amplitude by training a machine learning model with finger induced capacitive information. A high and stable force voltage responsivity of 87.5% is achieved experimentally, demonstrating its potential significance in force touch based human-machine interactivity.
{"title":"A Force – Voltage Responsivity Stabilization Method for Piezoelectric Touch Panels in the Internet of Things","authors":"Shuo Gao, Mingqi Shao, Rong Guo, A. Nathan","doi":"10.1109/FLEPS49123.2020.9239513","DOIUrl":"https://doi.org/10.1109/FLEPS49123.2020.9239513","url":null,"abstract":"Piezoelectric force touch panels are attractive as human-machine interfaces and 3-dimensional touch sensing in internet of things (IoT) applications. The piezoelectric material has the intrinsic ability to convert mechanical to electrical signals. But the force responsivity issue induced by different touch orientations can be unstable. This paper presents a piezoelectric touch panel that is sensitive to both capacitive and force stimulation. A touch orientation classification technique is developed to calibrate the detected force amplitude by training a machine learning model with finger induced capacitive information. A high and stable force voltage responsivity of 87.5% is achieved experimentally, demonstrating its potential significance in force touch based human-machine interactivity.","PeriodicalId":101496,"journal":{"name":"2020 IEEE International Conference on Flexible and Printable Sensors and Systems (FLEPS)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129412047","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 : 2020-03-18DOI: 10.1109/FLEPS49123.2020.9239596
Yanning Dai, Shuo Gao
Artificial smart skins capable of interacting with people and sensing environmental stimuli have become a research topic in humanoid robotic applications. However, previously reported architectures suffer difficulties in achieving multi-dimensional sensing in a simple structure with a low system cost. To address this issue, in this paper, an artificial smart skin constructed with polyimide/copper/polyvinylidene fluoride (PVDF) is presented for detecting 2D-position, proximity, dynamic force, and humidity via a smart combination of piezoelectric- and capacitive-effects. The proposed system achieves overall force and capacitive sensitivities of 0.051 N and 8.7 fF; the humidity measurements show a responsivity at 0.20%/RH% over a relative humidity range of 10%–90% RH. And a follow-up filtering algorithm is proposed to separate the stimuli associated with capacitance changes (position, proximity, and humidity). This simple-structured device supports multiple functions with its low system cost, thus advancing the field of robotics smart skins.
{"title":"Multi-functional Smart Skin for Multi-dimensional Perception for Humanoid Robots","authors":"Yanning Dai, Shuo Gao","doi":"10.1109/FLEPS49123.2020.9239596","DOIUrl":"https://doi.org/10.1109/FLEPS49123.2020.9239596","url":null,"abstract":"Artificial smart skins capable of interacting with people and sensing environmental stimuli have become a research topic in humanoid robotic applications. However, previously reported architectures suffer difficulties in achieving multi-dimensional sensing in a simple structure with a low system cost. To address this issue, in this paper, an artificial smart skin constructed with polyimide/copper/polyvinylidene fluoride (PVDF) is presented for detecting 2D-position, proximity, dynamic force, and humidity via a smart combination of piezoelectric- and capacitive-effects. The proposed system achieves overall force and capacitive sensitivities of 0.051 N and 8.7 fF; the humidity measurements show a responsivity at 0.20%/RH% over a relative humidity range of 10%–90% RH. And a follow-up filtering algorithm is proposed to separate the stimuli associated with capacitance changes (position, proximity, and humidity). This simple-structured device supports multiple functions with its low system cost, thus advancing the field of robotics smart skins.","PeriodicalId":101496,"journal":{"name":"2020 IEEE International Conference on Flexible and Printable Sensors and Systems (FLEPS)","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121029170","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 : 2020-03-17DOI: 10.1109/FLEPS49123.2020.9239486
Shuo Gao, Ruihan Lv, Shijie Sun
In traditional touch panels, electrodes are settled on or above the surface of displays, weakening the optical transmittance, hence resulting in high power consumption of the display for providing customers satisfied visual experience, giving rise to reduced battery’s lifetime which brings users inconvenience. To address this issue, in this article, we propose a new sensor architecture, in which electrodes are settled only at the edge of the touch panel, ensuring a very high optical transmittance. The touch event detection relies on electrical capacitance tomography (ECT) technique, through which 2-dimensional location recognition is achieved, indicating the presented technique provides a feasible means to boost the optical transmittance of the touch panel layer.
{"title":"A Novel Touch Panel Design for High Optical Transmittance for Interactive Displays","authors":"Shuo Gao, Ruihan Lv, Shijie Sun","doi":"10.1109/FLEPS49123.2020.9239486","DOIUrl":"https://doi.org/10.1109/FLEPS49123.2020.9239486","url":null,"abstract":"In traditional touch panels, electrodes are settled on or above the surface of displays, weakening the optical transmittance, hence resulting in high power consumption of the display for providing customers satisfied visual experience, giving rise to reduced battery’s lifetime which brings users inconvenience. To address this issue, in this article, we propose a new sensor architecture, in which electrodes are settled only at the edge of the touch panel, ensuring a very high optical transmittance. The touch event detection relies on electrical capacitance tomography (ECT) technique, through which 2-dimensional location recognition is achieved, indicating the presented technique provides a feasible means to boost the optical transmittance of the touch panel layer.","PeriodicalId":101496,"journal":{"name":"2020 IEEE International Conference on Flexible and Printable Sensors and Systems (FLEPS)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132759548","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}
Concurrent high force detection accuracy and extended battery lifetime are strongly expected in wearable gait monitoring systems, which are important for many Internet of Health Things (IoHT) applications. In this article, a piezoelectric insole device and rectifying circuitry based technique is presented to achieve these two ultimate goals. Here, walking induced positive and negative charges are separated for plantar stress detection and energy harvesting respectively, realizing the two functions concurrently. Experimental results demonstrate that first, the high detection sensitivity of 55 mN and responsivity of 231 mV/N are achieved, satisfying the need for diagnosing various diseases; second, energy of 1.6 pJ is stored during a walking event, consequently extending the battery lifetime. The developed technique enhances the development of gait monitoring in IoHT.
{"title":"Concurrent Plantar Stress Sensing and Energy Harvesting Technique by Piezoelectric Insole Device and Rectifying Circuitry for Gait Monitoring in the Internet of Health Things","authors":"Shuaibo Kang, Jingjing Lin, Junliang Chen, Yanning Dai, Zhiheng Wang, Shuo Gao","doi":"10.1109/FLEPS49123.2020.9239566","DOIUrl":"https://doi.org/10.1109/FLEPS49123.2020.9239566","url":null,"abstract":"Concurrent high force detection accuracy and extended battery lifetime are strongly expected in wearable gait monitoring systems, which are important for many Internet of Health Things (IoHT) applications. In this article, a piezoelectric insole device and rectifying circuitry based technique is presented to achieve these two ultimate goals. Here, walking induced positive and negative charges are separated for plantar stress detection and energy harvesting respectively, realizing the two functions concurrently. Experimental results demonstrate that first, the high detection sensitivity of 55 mN and responsivity of 231 mV/N are achieved, satisfying the need for diagnosing various diseases; second, energy of 1.6 pJ is stored during a walking event, consequently extending the battery lifetime. The developed technique enhances the development of gait monitoring in IoHT.","PeriodicalId":101496,"journal":{"name":"2020 IEEE International Conference on Flexible and Printable Sensors and Systems (FLEPS)","volume":"203 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129934213","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 : 2020-03-17DOI: 10.1109/FLEPS49123.2020.9239559
Anbiao Huang, Shuo Gao, A. Nathan
In Internet of Things (IoT) applications, secure access to smart systems, e.g., smartphones, is important for protecting private information. Among various authentication techniques, keystroke authentication methods based on touch behavior of the user have received increasing attention. This is due to the unique benefits, such as no additional hardware component and the ease of use in most smart systems. In this paper, we present a technique for obtaining high user authentication accuracy by utilizing a user’s touch time and force information, which are obtained from a piezoelectric touch panel. After combining artificial neural networks with the user’s touch features, an equal error rate (EER) of 1.09% is achieved, validating the feasibility of the proposed technique for achieving highly secure user authentication, hence advancing the development of security techniques potentially deployable in the field of IoT.
{"title":"A User Authentication Enabled Piezoelectric Force Touch System for the Internet of Things","authors":"Anbiao Huang, Shuo Gao, A. Nathan","doi":"10.1109/FLEPS49123.2020.9239559","DOIUrl":"https://doi.org/10.1109/FLEPS49123.2020.9239559","url":null,"abstract":"In Internet of Things (IoT) applications, secure access to smart systems, e.g., smartphones, is important for protecting private information. Among various authentication techniques, keystroke authentication methods based on touch behavior of the user have received increasing attention. This is due to the unique benefits, such as no additional hardware component and the ease of use in most smart systems. In this paper, we present a technique for obtaining high user authentication accuracy by utilizing a user’s touch time and force information, which are obtained from a piezoelectric touch panel. After combining artificial neural networks with the user’s touch features, an equal error rate (EER) of 1.09% is achieved, validating the feasibility of the proposed technique for achieving highly secure user authentication, hence advancing the development of security techniques potentially deployable in the field of IoT.","PeriodicalId":101496,"journal":{"name":"2020 IEEE International Conference on Flexible and Printable Sensors and Systems (FLEPS)","volume":"100 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124592162","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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