Patient adherence to home exercise regimens, critical in achieving ideal treatment outcomes for physical therapy, is typically poor. Further, therapists lack quantitative data to review a patient's performance. In this work, we propose a virtual rehabilitation system for home exercise with continuous monitoring and quantitative performance measurements packaged with a fun and engaging interface. The solution is a complete feedback loop where the physical therapist and patient make shared decisions about appropriate regimens, patients use a sensor-enabled gaming interface at home to perform exercises, quantitative data is fed back to the therapist, and the therapist is able to properly adjust the regimen and give reinforcing feedback and social support. The system aims to address the multi-factorial nature of poor adherence and to apply appropriate behavior change models and persuasive feedback mechanisms. In addition, it will capture critical objective data that will help to guide therapy practices on both the individual and community level.
{"title":"Collaborative virtual rehabilitation system with home treatment integration","authors":"S. Moturu, John O. Moore, Franklin H. Moss","doi":"10.1145/2077546.2077562","DOIUrl":"https://doi.org/10.1145/2077546.2077562","url":null,"abstract":"Patient adherence to home exercise regimens, critical in achieving ideal treatment outcomes for physical therapy, is typically poor. Further, therapists lack quantitative data to review a patient's performance. In this work, we propose a virtual rehabilitation system for home exercise with continuous monitoring and quantitative performance measurements packaged with a fun and engaging interface. The solution is a complete feedback loop where the physical therapist and patient make shared decisions about appropriate regimens, patients use a sensor-enabled gaming interface at home to perform exercises, quantitative data is fed back to the therapist, and the therapist is able to properly adjust the regimen and give reinforcing feedback and social support. The system aims to address the multi-factorial nature of poor adherence and to apply appropriate behavior change models and persuasive feedback mechanisms. In addition, it will capture critical objective data that will help to guide therapy practices on both the individual and community level.","PeriodicalId":91386,"journal":{"name":"Proceedings Wireless Health ... [electronic resource]. Wireless Health (Conference)","volume":"11 1","pages":"14"},"PeriodicalIF":0.0,"publicationDate":"2011-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79710909","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}
Ming-chun Huang, Ethan Chen, Wenyao Xu, M. Sarrafzadeh
This paper presents a hand motion capture system. Its application is a wearable controller for an upper extremities rehabilitation game. The system consists of a wearable data glove platform (SmartGlove, a customized finger pressure, bending, and 9DOM motion extraction platform) and a 3D camera vision device (Kinect [1], vision based game controller supplied by Microsoft) to extract detailed upper extremities parameters as gaming inputs. The testing application is a jewel thief game [2] implemented with C# and Unity, which requires the tester, such as a stroked patient with upper extremities disabilities to perform a series of predefined upper extremities movements to accomplish the assigned jewel grasping tasks. The parameters and timing could recorded during the gaming process for further medical analysis. This system is targeted on lowering the cost of rehabilitating impaired limbs, providing remote patient monitoring, and acting as a natural interface for gaming systems. In addition, the extracted parameters can be exploited to reconstruct of an accurate model of the patient's limbs and body. Therefore, the proposed system can provide remote medical staffs a wide variety of information to aid a patient's rehabilitation, including, but not limited to aiding in progress evaluations and direct rehabilitative exercises and entertainment.
{"title":"Gaming for upper extremities rehabilitation","authors":"Ming-chun Huang, Ethan Chen, Wenyao Xu, M. Sarrafzadeh","doi":"10.1145/2077546.2077576","DOIUrl":"https://doi.org/10.1145/2077546.2077576","url":null,"abstract":"This paper presents a hand motion capture system. Its application is a wearable controller for an upper extremities rehabilitation game. The system consists of a wearable data glove platform (SmartGlove, a customized finger pressure, bending, and 9DOM motion extraction platform) and a 3D camera vision device (Kinect [1], vision based game controller supplied by Microsoft) to extract detailed upper extremities parameters as gaming inputs. The testing application is a jewel thief game [2] implemented with C# and Unity, which requires the tester, such as a stroked patient with upper extremities disabilities to perform a series of predefined upper extremities movements to accomplish the assigned jewel grasping tasks. The parameters and timing could recorded during the gaming process for further medical analysis. This system is targeted on lowering the cost of rehabilitating impaired limbs, providing remote patient monitoring, and acting as a natural interface for gaming systems. In addition, the extracted parameters can be exploited to reconstruct of an accurate model of the patient's limbs and body. Therefore, the proposed system can provide remote medical staffs a wide variety of information to aid a patient's rehabilitation, including, but not limited to aiding in progress evaluations and direct rehabilitative exercises and entertainment.","PeriodicalId":91386,"journal":{"name":"Proceedings Wireless Health ... [electronic resource]. Wireless Health (Conference)","volume":"52 1","pages":"27"},"PeriodicalIF":0.0,"publicationDate":"2011-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85244655","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}
I. Romero, T. Berset, Dilpreet Buxi, L. Brown, J. Penders, Sunyoung Kim, N. V. Helleputte, Hyejung Kim, C. Hoof, R. Yazicioglu
Recent advances in low-power micro-electronics are revolutionizing ECG monitoring. Wearable patches now allow comfortable monitoring over several days. Achieving reliable and high integrity recording however remains a challenge, especially under daily-life activities. In this paper we present a system approach to motion artifact reduction in ambulatory recordings. A custom ultra-low-power ECG analog front-end read-out for simultaneous measurement of ECG and electrode-tissue impedance, from the same electrode, is reported. Integrating this front-end, we describe a wireless patch for the monitoring of 3-lead ECG, electrode electrical artifact and 3D-acceleration. Beyond ECG monitoring, this wireless patch provides the additional necessary data to filter out motion artifact. Two algorithm methods are tested. The first method applies ICA for de-noising multi-lead ECG recordings. The second method is an adaptive filter that uses skin/electrode impedance as the measurement of noise. Algorithms, circuits and system provide a platform for reliable ECG monitoring on-the-move.
{"title":"Motion artifact reduction in ambulatory ECG monitoring: an integrated system approach","authors":"I. Romero, T. Berset, Dilpreet Buxi, L. Brown, J. Penders, Sunyoung Kim, N. V. Helleputte, Hyejung Kim, C. Hoof, R. Yazicioglu","doi":"10.1145/2077546.2077558","DOIUrl":"https://doi.org/10.1145/2077546.2077558","url":null,"abstract":"Recent advances in low-power micro-electronics are revolutionizing ECG monitoring. Wearable patches now allow comfortable monitoring over several days. Achieving reliable and high integrity recording however remains a challenge, especially under daily-life activities. In this paper we present a system approach to motion artifact reduction in ambulatory recordings. A custom ultra-low-power ECG analog front-end read-out for simultaneous measurement of ECG and electrode-tissue impedance, from the same electrode, is reported. Integrating this front-end, we describe a wireless patch for the monitoring of 3-lead ECG, electrode electrical artifact and 3D-acceleration. Beyond ECG monitoring, this wireless patch provides the additional necessary data to filter out motion artifact. Two algorithm methods are tested. The first method applies ICA for de-noising multi-lead ECG recordings. The second method is an adaptive filter that uses skin/electrode impedance as the measurement of noise. Algorithms, circuits and system provide a platform for reliable ECG monitoring on-the-move.","PeriodicalId":91386,"journal":{"name":"Proceedings Wireless Health ... [electronic resource]. Wireless Health (Conference)","volume":"72 1","pages":"11"},"PeriodicalIF":0.0,"publicationDate":"2011-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79407538","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}
Philip Asare, Danyang Cong, Santosh G. Vattam, Baekgyu Kim, O. Sokolsky, Insup Lee, Sha-Sha Lin, M. Mullen-Fortino
Emerging medical applications require networked coordination between medical devices. However, most of the medical devices in use today do not support wireless communication or network connectivity. Currently, hospitals interested in coordinated medical care would have replace existing devices with expensive new devices. We believe that existing medical devices can be extended to support interoperable network connectivity. We demonstrate the Medical Device Dongle (MDD), an open-source platform that enables such extensions to current medical devices. The MDD can attach to any device that has a data output interface (RS-232 or USB) and enables it to connect wirelessly and in an interoperable manner for various applications. We show how multiple medical devices, including pulse oximeters and infusion pumps, can be connected and controlled together using an open-source platform, standards-based connectivity protocols, and model-driven software. The demo setup consists of medical devices attached to an MDD Agent, an MDD Manager device, and a mobile phone running monitoring applications. The MDD components can communicate over Bluetooth, WiFi and Ethernet.
{"title":"Demo of the medical device dongle: an open-source standards-based platform for interoperable medical device connectivity","authors":"Philip Asare, Danyang Cong, Santosh G. Vattam, Baekgyu Kim, O. Sokolsky, Insup Lee, Sha-Sha Lin, M. Mullen-Fortino","doi":"10.1145/2077546.2077565","DOIUrl":"https://doi.org/10.1145/2077546.2077565","url":null,"abstract":"Emerging medical applications require networked coordination between medical devices. However, most of the medical devices in use today do not support wireless communication or network connectivity. Currently, hospitals interested in coordinated medical care would have replace existing devices with expensive new devices. We believe that existing medical devices can be extended to support interoperable network connectivity. We demonstrate the Medical Device Dongle (MDD), an open-source platform that enables such extensions to current medical devices. The MDD can attach to any device that has a data output interface (RS-232 or USB) and enables it to connect wirelessly and in an interoperable manner for various applications. We show how multiple medical devices, including pulse oximeters and infusion pumps, can be connected and controlled together using an open-source platform, standards-based connectivity protocols, and model-driven software. The demo setup consists of medical devices attached to an MDD Agent, an MDD Manager device, and a mobile phone running monitoring applications. The MDD components can communicate over Bluetooth, WiFi and Ethernet.","PeriodicalId":91386,"journal":{"name":"Proceedings Wireless Health ... [electronic resource]. Wireless Health (Conference)","volume":"13 1","pages":"16"},"PeriodicalIF":0.0,"publicationDate":"2011-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90957308","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}
Remote physiological monitoring of first responders can become instrumental in the quick and timely detection of the onset of harmful cardiac events. This application finds use not only for first responders but for the physically susceptible senior population and recovering cardiac patients. Fusion of multiple physiological parameters has the potential to improve the overall performance of automated anomaly detection. In this demonstration, we demonstrate the improved performance achieved through the use of novel sensor fusion software integrated with a commercial physiological monitoring hardware system.
{"title":"Sensor fusion for remote health assessment of first responders","authors":"Tejaswi Tamminedi, Lei Zhang, P. Ganapathy","doi":"10.1145/2077546.2077581","DOIUrl":"https://doi.org/10.1145/2077546.2077581","url":null,"abstract":"Remote physiological monitoring of first responders can become instrumental in the quick and timely detection of the onset of harmful cardiac events. This application finds use not only for first responders but for the physically susceptible senior population and recovering cardiac patients. Fusion of multiple physiological parameters has the potential to improve the overall performance of automated anomaly detection. In this demonstration, we demonstrate the improved performance achieved through the use of novel sensor fusion software integrated with a commercial physiological monitoring hardware system.","PeriodicalId":91386,"journal":{"name":"Proceedings Wireless Health ... [electronic resource]. Wireless Health (Conference)","volume":"14 1","pages":"32"},"PeriodicalIF":0.0,"publicationDate":"2011-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82394614","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}
Tejaswi Tamminedi, Aditya Kothari, A. Tiwari, A. Ganguli, S. Avadhanam
Several body worn medical sensing and physiological monitoring devices are currently on the market or are under development. For portable body worn sensor systems battery life is a critical issue. We demonstrate how intelligent energy management techniques that utilize contextual information can be used for extending battery life of wearable health monitoring devices
{"title":"The role of peripheral energy management for wireless health applications","authors":"Tejaswi Tamminedi, Aditya Kothari, A. Tiwari, A. Ganguli, S. Avadhanam","doi":"10.1145/1921081.1921121","DOIUrl":"https://doi.org/10.1145/1921081.1921121","url":null,"abstract":"Several body worn medical sensing and physiological monitoring devices are currently on the market or are under development. For portable body worn sensor systems battery life is a critical issue. We demonstrate how intelligent energy management techniques that utilize contextual information can be used for extending battery life of wearable health monitoring devices","PeriodicalId":91386,"journal":{"name":"Proceedings Wireless Health ... [electronic resource]. Wireless Health (Conference)","volume":"36 1","pages":"220-221"},"PeriodicalIF":0.0,"publicationDate":"2010-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77698714","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}
Ubiquitous physiological monitoring will be a key driving force in the upcoming wireless health revolution. Cardiac and brain signals in the form of ECG and EEG are two critical health indicators that directly benefit from long-term monitoring. Despite advancements in wireless technology and electronics miniaturization, however, the use of wireless home ECG/EEG monitoring is still limited by the inconvenience and discomfort of wet adhesive electrodes. We have developed a wireless biopotential instrumentation system using non-contact capacitive electrodes that operate without skin contact. The compact, battery-powered, wireless system accepts inputs from both standard Ag/AgCl electrodes and non-contact sensors and provides live telemetry to a laptop computer. We will demonstrate the interactive, prototype ECG/EEG system for acquiring cardiac and brain signals quickly and through clothing.
{"title":"Wireless non-contact biopotential electrodes","authors":"Y. Chi, P. Ng, C. Maier, G. Cauwenberghs","doi":"10.1145/1921081.1921108","DOIUrl":"https://doi.org/10.1145/1921081.1921108","url":null,"abstract":"Ubiquitous physiological monitoring will be a key driving force in the upcoming wireless health revolution. Cardiac and brain signals in the form of ECG and EEG are two critical health indicators that directly benefit from long-term monitoring. Despite advancements in wireless technology and electronics miniaturization, however, the use of wireless home ECG/EEG monitoring is still limited by the inconvenience and discomfort of wet adhesive electrodes.\u0000 We have developed a wireless biopotential instrumentation system using non-contact capacitive electrodes that operate without skin contact. The compact, battery-powered, wireless system accepts inputs from both standard Ag/AgCl electrodes and non-contact sensors and provides live telemetry to a laptop computer. We will demonstrate the interactive, prototype ECG/EEG system for acquiring cardiac and brain signals quickly and through clothing.","PeriodicalId":91386,"journal":{"name":"Proceedings Wireless Health ... [electronic resource]. Wireless Health (Conference)","volume":"6 1","pages":"194-195"},"PeriodicalIF":0.0,"publicationDate":"2010-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90387522","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}
What is the role of face-to-face interactions in the diffusion of health-related behaviors- diet choices, exercise habits, and long-term weight changes? We use co-location and communication sensors in mass-market mobile phones to model the diffusion of health-related behaviors via face-to-face interactions amongst the residents of an undergraduate residence hall during the academic year of 2008--09. The dataset used in this analysis includes bluetooth proximity scans, 802.11 WLAN AP scans, calling and SMS networks and self-reported diet, exercise and weight-related information collected periodically over a nine month period. We find that the health behaviors of participants are correlated with the behaviors of peers that they are exposed to over long durations. Such exposure can be estimated using automatically captured social interactions between individuals. To better understand this adoption mechanism, we contrast the role of exposure to different sub-behaviors, i.e., exposure to peers that are obese, are inactive, have unhealthy dietary habits and those that display similar weight changes in the observation period. These results suggest that it is possible to design self-feedback tools and real-time interventions in the future. In stark contrast to previous work, we find that self-reported friends and social acquaintances do not show similar predictive ability for these social health behaviors.
{"title":"Social sensing: obesity, unhealthy eating and exercise in face-to-face networks","authors":"Anmol Madan, S. Moturu, D. Lazer, A. Pentland","doi":"10.1145/1921081.1921094","DOIUrl":"https://doi.org/10.1145/1921081.1921094","url":null,"abstract":"What is the role of face-to-face interactions in the diffusion of health-related behaviors- diet choices, exercise habits, and long-term weight changes? We use co-location and communication sensors in mass-market mobile phones to model the diffusion of health-related behaviors via face-to-face interactions amongst the residents of an undergraduate residence hall during the academic year of 2008--09. The dataset used in this analysis includes bluetooth proximity scans, 802.11 WLAN AP scans, calling and SMS networks and self-reported diet, exercise and weight-related information collected periodically over a nine month period. We find that the health behaviors of participants are correlated with the behaviors of peers that they are exposed to over long durations. Such exposure can be estimated using automatically captured social interactions between individuals. To better understand this adoption mechanism, we contrast the role of exposure to different sub-behaviors, i.e., exposure to peers that are obese, are inactive, have unhealthy dietary habits and those that display similar weight changes in the observation period. These results suggest that it is possible to design self-feedback tools and real-time interventions in the future. In stark contrast to previous work, we find that self-reported friends and social acquaintances do not show similar predictive ability for these social health behaviors.","PeriodicalId":91386,"journal":{"name":"Proceedings Wireless Health ... [electronic resource]. Wireless Health (Conference)","volume":"3 1","pages":"104-110"},"PeriodicalIF":0.0,"publicationDate":"2010-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89974279","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}
K. Y. Au-Yeung, T. Robertson, H. Hafezi, G. Moon, L. DiCarlo, M. Zdeblick, G. Savage
Background: A networked wellness system is under development to document actual ingestions of oral medications, to differentiate types/doses of drugs taken simultaneously, and to provide these data along with other metrics to patients and providers for individually tailored care. Methods: After ingestion, an edible sensor (embedded in drug) is activated by stomach fluid and communicates to a wearable monitor that identifies the sensor as unique and records ingestion time/date. The monitor also collects physiologic data and communicates via mobile phone to a secure server that integrates the data with other wireless devices (e.g. blood pressure, weight). Summary reports are generated periodically for patient and physician review. Results: No adverse effects were observed in animals using repeated, exaggerated doses of sensors. Two drug-sensor form factors have been tested in 3392 human ingestions with no major and very few minor adverse effects. Sensitivity was 97.0% and specificity was 97.7% when compared to directly observed ingestion. The system identified and differentiated up to 4 simultaneously ingested sensors with an identification accuracy of 100%. Data integration with multiple devices and report generation have been piloted successfully. Conclusions: Pre-clinical and early clinical system safety appear satisfactory; data integration and communication appear to be feasible. By providing context-rich information and fostering communication, this system may enhance patient-provider relationship and care coordination.
{"title":"A networked system for self-management of drug therapy and wellness","authors":"K. Y. Au-Yeung, T. Robertson, H. Hafezi, G. Moon, L. DiCarlo, M. Zdeblick, G. Savage","doi":"10.1145/1921081.1921083","DOIUrl":"https://doi.org/10.1145/1921081.1921083","url":null,"abstract":"Background: A networked wellness system is under development to document actual ingestions of oral medications, to differentiate types/doses of drugs taken simultaneously, and to provide these data along with other metrics to patients and providers for individually tailored care. Methods: After ingestion, an edible sensor (embedded in drug) is activated by stomach fluid and communicates to a wearable monitor that identifies the sensor as unique and records ingestion time/date. The monitor also collects physiologic data and communicates via mobile phone to a secure server that integrates the data with other wireless devices (e.g. blood pressure, weight). Summary reports are generated periodically for patient and physician review. Results: No adverse effects were observed in animals using repeated, exaggerated doses of sensors. Two drug-sensor form factors have been tested in 3392 human ingestions with no major and very few minor adverse effects. Sensitivity was 97.0% and specificity was 97.7% when compared to directly observed ingestion. The system identified and differentiated up to 4 simultaneously ingested sensors with an identification accuracy of 100%. Data integration with multiple devices and report generation have been piloted successfully. Conclusions: Pre-clinical and early clinical system safety appear satisfactory; data integration and communication appear to be feasible. By providing context-rich information and fostering communication, this system may enhance patient-provider relationship and care coordination.","PeriodicalId":91386,"journal":{"name":"Proceedings Wireless Health ... [electronic resource]. Wireless Health (Conference)","volume":"149 1","pages":"1-9"},"PeriodicalIF":0.0,"publicationDate":"2010-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86123772","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}
Y. Chi, P. Ng, E. Kang, Joseph Kang, Jennifer Fang, G. Cauwenberghs
Ubiquitous physiological monitoring will be a key driving force in the upcoming wireless health revolution. Cardiac and brain signals in the form of ECG and EEG are two critical health indicators that directly benefit from long-term monitoring. Despite advancements in wireless technology and electronics miniaturization, however, the use of wireless home ECG/EEG monitoring is still limited by the inconvenience and discomfort of wet adhesive electrodes. We have developed a wireless biopotential instrumentation system using non-contact capacitive electrodes that operate without skin contact. The sensors can be embedded within comfortable layers of fabric for unobtrusive use. All of the issues relating to the design of low noise, high performance capacitive sensors are discussed along with full technical details, circuit schematics and construction techniques. The non-contact electrode has been integrated into both a wearable ECG chest harness as well a EEG headband. We have also designed a compact, battery-powered, wireless data acquisition system to interface with multiple electrodes and monitor patient cardiac and neural signals in real time. Experimental data shows that the non-contact capacitive electrode perform comparable to Ag/AgCl electrodes using our special chest harness and head bands to ensure tight, movement-free electrode positioning.
{"title":"Wireless non-contact cardiac and neural monitoring","authors":"Y. Chi, P. Ng, E. Kang, Joseph Kang, Jennifer Fang, G. Cauwenberghs","doi":"10.1145/1921081.1921085","DOIUrl":"https://doi.org/10.1145/1921081.1921085","url":null,"abstract":"Ubiquitous physiological monitoring will be a key driving force in the upcoming wireless health revolution. Cardiac and brain signals in the form of ECG and EEG are two critical health indicators that directly benefit from long-term monitoring. Despite advancements in wireless technology and electronics miniaturization, however, the use of wireless home ECG/EEG monitoring is still limited by the inconvenience and discomfort of wet adhesive electrodes.\u0000 We have developed a wireless biopotential instrumentation system using non-contact capacitive electrodes that operate without skin contact. The sensors can be embedded within comfortable layers of fabric for unobtrusive use. All of the issues relating to the design of low noise, high performance capacitive sensors are discussed along with full technical details, circuit schematics and construction techniques.\u0000 The non-contact electrode has been integrated into both a wearable ECG chest harness as well a EEG headband. We have also designed a compact, battery-powered, wireless data acquisition system to interface with multiple electrodes and monitor patient cardiac and neural signals in real time. Experimental data shows that the non-contact capacitive electrode perform comparable to Ag/AgCl electrodes using our special chest harness and head bands to ensure tight, movement-free electrode positioning.","PeriodicalId":91386,"journal":{"name":"Proceedings Wireless Health ... [electronic resource]. Wireless Health (Conference)","volume":"38 1","pages":"15-23"},"PeriodicalIF":0.0,"publicationDate":"2010-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88739986","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：