Pub Date : 2015-06-09DOI: 10.1109/BSN.2015.7299403
P. Kassanos, H. Ip, Guang-Zhong Yang
Surgical Site Infection (SSI) imposes a significant burden clinically and compromises patient recovery. Anastomosis in the gastrointestinal (GI) tract is a particularly challenging case where failure of the anastomosis can lead to leakage, resulting in an increase in mortality rates. However early diagnosis and intervention are hampered by a lack of continuous sensing and long diagnostic intervals of current clinical practices. Tissue ischemia in the vicinity of the anastomosis has been found to be an early surrogate marker for anastomotic leakage. Electrical bio-impedance is a promising non-invasive technique for identifying and monitoring tissue ischemia. In this paper the modelling, design and validation of a bio-impedance system including compact instrumentation and a novel bio-impedance sensor optimized for mucosal tissue measurements in the GI tract are presented. The preliminary system, including the impedance probe, is validated experimentally for GI implant applications to provide early detection of tissue ischemia following GI surgery.
{"title":"A tetrapolar bio-impedance sensing system for gastrointestinal tract monitoring","authors":"P. Kassanos, H. Ip, Guang-Zhong Yang","doi":"10.1109/BSN.2015.7299403","DOIUrl":"https://doi.org/10.1109/BSN.2015.7299403","url":null,"abstract":"Surgical Site Infection (SSI) imposes a significant burden clinically and compromises patient recovery. Anastomosis in the gastrointestinal (GI) tract is a particularly challenging case where failure of the anastomosis can lead to leakage, resulting in an increase in mortality rates. However early diagnosis and intervention are hampered by a lack of continuous sensing and long diagnostic intervals of current clinical practices. Tissue ischemia in the vicinity of the anastomosis has been found to be an early surrogate marker for anastomotic leakage. Electrical bio-impedance is a promising non-invasive technique for identifying and monitoring tissue ischemia. In this paper the modelling, design and validation of a bio-impedance system including compact instrumentation and a novel bio-impedance sensor optimized for mucosal tissue measurements in the GI tract are presented. The preliminary system, including the impedance probe, is validated experimentally for GI implant applications to provide early detection of tissue ischemia following GI surgery.","PeriodicalId":447934,"journal":{"name":"2015 IEEE 12th International Conference on Wearable and Implantable Body Sensor Networks (BSN)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128570068","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 : 2015-06-09DOI: 10.1109/BSN.2015.7299371
Heike Leutheuser, Stefan Gradl, B. Eskofier, A. Tobola, N. Lang, L. Anneken, M. Arnold, S. Achenbach
Far too many people are dying from stroke or other heart related diseases each year. Early detection of abnormal heart rhythm could trigger the timely presentation to the emergency department or outpatient unit. Smartphones are an integral part of everyone;s life and they form the ideal basis for mobile monitoring and real-time analysis of signals related to the human heart. In this work, we investigated the performance of arrhythmia classification systems using only features calculated from the time instances of individual heart beats. We built a sinusoidal model using N (N = 10, 15, 20) consecutive RR intervals to predict the (N+1)th RR interval. The integration of the innovative sinusoidal regression feature, together with the amplitude and phase of the proposed sinusoidal model, led to an increase in the mean class-dependent classification accuracies. Best mean class-dependent classification accuracies of 90% were achieved using a Naïve Bayes classifier. Well-performing realtime analysis arrhythmia classification algorithms using only the time instances of individual heart beats could have a tremendous impact in reducing healthcare costs and reducing the high number of deaths related to cardiovascular diseases.
{"title":"Arrhythmia classification using RR intervals: Improvement with sinusoidal regression feature","authors":"Heike Leutheuser, Stefan Gradl, B. Eskofier, A. Tobola, N. Lang, L. Anneken, M. Arnold, S. Achenbach","doi":"10.1109/BSN.2015.7299371","DOIUrl":"https://doi.org/10.1109/BSN.2015.7299371","url":null,"abstract":"Far too many people are dying from stroke or other heart related diseases each year. Early detection of abnormal heart rhythm could trigger the timely presentation to the emergency department or outpatient unit. Smartphones are an integral part of everyone;s life and they form the ideal basis for mobile monitoring and real-time analysis of signals related to the human heart. In this work, we investigated the performance of arrhythmia classification systems using only features calculated from the time instances of individual heart beats. We built a sinusoidal model using N (N = 10, 15, 20) consecutive RR intervals to predict the (N+1)th RR interval. The integration of the innovative sinusoidal regression feature, together with the amplitude and phase of the proposed sinusoidal model, led to an increase in the mean class-dependent classification accuracies. Best mean class-dependent classification accuracies of 90% were achieved using a Naïve Bayes classifier. Well-performing realtime analysis arrhythmia classification algorithms using only the time instances of individual heart beats could have a tremendous impact in reducing healthcare costs and reducing the high number of deaths related to cardiovascular diseases.","PeriodicalId":447934,"journal":{"name":"2015 IEEE 12th International Conference on Wearable and Implantable Body Sensor Networks (BSN)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128901437","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 : 2015-06-09DOI: 10.1109/BSN.2015.7299373
Peng Fang, Qifang Zhuo, Yan Cai, Lan Tian, Haoshi Zhang, Yue Zheng, Guanglin Li, Liming Wu, Xiaoqing Zhang
Piezoelectrets are polymer-foam based space-charge electrets with strong piezoelectric effect. The piezoelectricity in piezoelectrets occurs due to the elastic heterogeneous cellular structure and the regularly arranged dipolar space charges stored therein. Some polymers have been experimented for piezoelectret preparation, where polypropylene (PP) is the mostly applied material at present. PP piezoelectrets have several promising features, such as large piezoelectric d33 coefficient, small thickness, light weight, low cost, large area scale, as well as flexibility and even stretchability, which would enable them very suitable for applications in signal sensing and energy harvesting. In this work, the electromechanical properties of flexible and stretchable PP piezoelectrets are introduced and some of their possible applications as wearable physiological-signal sensors and micro-energy harvesters are demonstrated by experiments.
{"title":"Piezoelectrets and their applications as wearable physiological-signal sensors and energy harvesters","authors":"Peng Fang, Qifang Zhuo, Yan Cai, Lan Tian, Haoshi Zhang, Yue Zheng, Guanglin Li, Liming Wu, Xiaoqing Zhang","doi":"10.1109/BSN.2015.7299373","DOIUrl":"https://doi.org/10.1109/BSN.2015.7299373","url":null,"abstract":"Piezoelectrets are polymer-foam based space-charge electrets with strong piezoelectric effect. The piezoelectricity in piezoelectrets occurs due to the elastic heterogeneous cellular structure and the regularly arranged dipolar space charges stored therein. Some polymers have been experimented for piezoelectret preparation, where polypropylene (PP) is the mostly applied material at present. PP piezoelectrets have several promising features, such as large piezoelectric d33 coefficient, small thickness, light weight, low cost, large area scale, as well as flexibility and even stretchability, which would enable them very suitable for applications in signal sensing and energy harvesting. In this work, the electromechanical properties of flexible and stretchable PP piezoelectrets are introduced and some of their possible applications as wearable physiological-signal sensors and micro-energy harvesters are demonstrated by experiments.","PeriodicalId":447934,"journal":{"name":"2015 IEEE 12th International Conference on Wearable and Implantable Body Sensor Networks (BSN)","volume":"136 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114353003","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 : 2015-06-09DOI: 10.1109/BSN.2015.7299424
W. Tomlinson, Fabian Abarca, K. Chowdhury, M. Stojanovic, Christopher C. Yu
The recent surge of implantable and wearable medical devices have paved the way for realizing intra-body networks (IBNs). Traditional RF-based techniques fall short in wirelessly connecting such devices owing to absorption within body tissues. A different approach is known as galvanic coupling, which employs weak electrical current within naturally conducting tissues to enable intra-body communication. This work is focused on channel characterization of the human body tissues considering the propagation of such electrical signals through it that carry data. Experiments were conducted using porcine tissue (in lieu of actual human tissue) with skin, fat and muscle layers in the frequency range of 100 kHz to 1 MHz. By utilizing single-carrier BPSK modulated Pseudorandom Noise Sequences, a correlative channel sounding system was implemented, leading to the following contributions: (1) measurements of the channel impulse and frequency response, (2) a noise analysis and capacity estimation, and (3) the comparison of results with existing models.
{"title":"Experimental assessment of human-body-like tissue as a communication channel for galvanic coupling","authors":"W. Tomlinson, Fabian Abarca, K. Chowdhury, M. Stojanovic, Christopher C. Yu","doi":"10.1109/BSN.2015.7299424","DOIUrl":"https://doi.org/10.1109/BSN.2015.7299424","url":null,"abstract":"The recent surge of implantable and wearable medical devices have paved the way for realizing intra-body networks (IBNs). Traditional RF-based techniques fall short in wirelessly connecting such devices owing to absorption within body tissues. A different approach is known as galvanic coupling, which employs weak electrical current within naturally conducting tissues to enable intra-body communication. This work is focused on channel characterization of the human body tissues considering the propagation of such electrical signals through it that carry data. Experiments were conducted using porcine tissue (in lieu of actual human tissue) with skin, fat and muscle layers in the frequency range of 100 kHz to 1 MHz. By utilizing single-carrier BPSK modulated Pseudorandom Noise Sequences, a correlative channel sounding system was implemented, leading to the following contributions: (1) measurements of the channel impulse and frequency response, (2) a noise analysis and capacity estimation, and (3) the comparison of results with existing models.","PeriodicalId":447934,"journal":{"name":"2015 IEEE 12th International Conference on Wearable and Implantable Body Sensor Networks (BSN)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131999999","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 : 2015-06-09DOI: 10.1109/BSN.2015.7299384
Stepan Gorgutsa, M. Khalil, Victor Bélanger-Garnier, J. Viens, Y. Messaddeq, B. Gosselin, S. Larochelle
In this work, we present the emissive performance of wearable radio-frequency (RF) textiles made from multi-material fibers, for both on-body and off-body scenarios, for body area network applications through ISM (2.4 GHz) bands. It is shown that the emissive performance of the RF textiles in terms of return loss (S11), radiation pattern, and efficiency (gain) were similar to commercial router antennas, while the center frequency shift and band broadening were reduced due in part to the small form factor of the fiber antennas. The RF textiles were fabricated by integrating unobtrusive polymer-glass-metal fiber composites into a textile host using conventional weaving process. This approach provided good RF emissive performance in compliance with safety regulations while preserving the mechanical and cosmetic properties of the garments.
{"title":"Emissive performance of wearable RF textiles made from multi-material fibers","authors":"Stepan Gorgutsa, M. Khalil, Victor Bélanger-Garnier, J. Viens, Y. Messaddeq, B. Gosselin, S. Larochelle","doi":"10.1109/BSN.2015.7299384","DOIUrl":"https://doi.org/10.1109/BSN.2015.7299384","url":null,"abstract":"In this work, we present the emissive performance of wearable radio-frequency (RF) textiles made from multi-material fibers, for both on-body and off-body scenarios, for body area network applications through ISM (2.4 GHz) bands. It is shown that the emissive performance of the RF textiles in terms of return loss (S11), radiation pattern, and efficiency (gain) were similar to commercial router antennas, while the center frequency shift and band broadening were reduced due in part to the small form factor of the fiber antennas. The RF textiles were fabricated by integrating unobtrusive polymer-glass-metal fiber composites into a textile host using conventional weaving process. This approach provided good RF emissive performance in compliance with safety regulations while preserving the mechanical and cosmetic properties of the garments.","PeriodicalId":447934,"journal":{"name":"2015 IEEE 12th International Conference on Wearable and Implantable Body Sensor Networks (BSN)","volume":"118 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133380147","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 : 2015-06-09DOI: 10.1109/BSN.2015.7299400
Jiaqi Gong, J. Lach, Yanjun Qi, M. Goldman
Gait assessment is a common method for diagnosing various diseases, disorders, and injuries, studying their impact on mobility, and evaluating the efficacy of various therapeutic interventions. The recent emergence of inertial body sensors for gait assessment addresses the limitations of visual observation and subjective clinical evaluation by providing more precise and objective measures. Inertial sensors have been included in an ongoing study at the University of Virginia Medical Center on Multiple Sclerosis (MS), a chronic autoimmune disorder of the central nervous system (CNS) that produces neurologic impairment and functional disability over time, with the goal of improving the ability to assess MS-affected gait and to distinguish between subjects with MS and those without MS. This work presents a gait assessment technique based on causal modeling to distinguish MS-affected gait and healthy gait. The approach in this work is based on the hypothesis that the strength of interaction between body parts during walking is greater in healthy controls that in MS subjects. The strength of interaction was quantified using a causality index based on the pairwise causal relationships between body parts as characterized by the Phase Slope Index (PSI) of inertial signals from pairs of body parts. In a pilot study with 41 subjects (28 MS subjects and 13 healthy controls), the approach developed in this paper provided better separability (p <; 0.0001) compared with existing methods.
{"title":"Causal analysis of inertial body sensors for enhancing gait assessment separability towards multiple sclerosis diagnosis","authors":"Jiaqi Gong, J. Lach, Yanjun Qi, M. Goldman","doi":"10.1109/BSN.2015.7299400","DOIUrl":"https://doi.org/10.1109/BSN.2015.7299400","url":null,"abstract":"Gait assessment is a common method for diagnosing various diseases, disorders, and injuries, studying their impact on mobility, and evaluating the efficacy of various therapeutic interventions. The recent emergence of inertial body sensors for gait assessment addresses the limitations of visual observation and subjective clinical evaluation by providing more precise and objective measures. Inertial sensors have been included in an ongoing study at the University of Virginia Medical Center on Multiple Sclerosis (MS), a chronic autoimmune disorder of the central nervous system (CNS) that produces neurologic impairment and functional disability over time, with the goal of improving the ability to assess MS-affected gait and to distinguish between subjects with MS and those without MS. This work presents a gait assessment technique based on causal modeling to distinguish MS-affected gait and healthy gait. The approach in this work is based on the hypothesis that the strength of interaction between body parts during walking is greater in healthy controls that in MS subjects. The strength of interaction was quantified using a causality index based on the pairwise causal relationships between body parts as characterized by the Phase Slope Index (PSI) of inertial signals from pairs of body parts. In a pilot study with 41 subjects (28 MS subjects and 13 healthy controls), the approach developed in this paper provided better separability (p <; 0.0001) compared with existing methods.","PeriodicalId":447934,"journal":{"name":"2015 IEEE 12th International Conference on Wearable and Implantable Body Sensor Networks (BSN)","volume":"134 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121530816","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 : 2015-06-09DOI: 10.1109/BSN.2015.7299361
Shumei Zhang, P. Mccullagh, Huiyu Zhou, Zhe Wen, Zhengcheng Xu
Three RFID reader based network deployment algorithms (grid-covering, diagonal and mixed) were evaluated in this paper. Experimental results show that the grid-covering method can be used to minimize hardware costs, but it leads to many indeterminate positions. The diagonal method can be used to solve the indeterminate problem, however increases the number of readers, especially in a large tracking field. The mixed algorithm can be used to avoid the indeterminate issue and also has the minimum reader number when deployed in a large space. However, it is not suitable for a small tracking field. An optimal deployment algorithm is selected from these three algorithms according to the environmental conditions and the localization requirement. In addition, an optimal RFID reader network deployment combined with a subarea-mapping algorithm can be used to minimize the hardware costs while improving the fine-grained indoor localization accuracy.
{"title":"RFID network deployment approaches for indoor localisation","authors":"Shumei Zhang, P. Mccullagh, Huiyu Zhou, Zhe Wen, Zhengcheng Xu","doi":"10.1109/BSN.2015.7299361","DOIUrl":"https://doi.org/10.1109/BSN.2015.7299361","url":null,"abstract":"Three RFID reader based network deployment algorithms (grid-covering, diagonal and mixed) were evaluated in this paper. Experimental results show that the grid-covering method can be used to minimize hardware costs, but it leads to many indeterminate positions. The diagonal method can be used to solve the indeterminate problem, however increases the number of readers, especially in a large tracking field. The mixed algorithm can be used to avoid the indeterminate issue and also has the minimum reader number when deployed in a large space. However, it is not suitable for a small tracking field. An optimal deployment algorithm is selected from these three algorithms according to the environmental conditions and the localization requirement. In addition, an optimal RFID reader network deployment combined with a subarea-mapping algorithm can be used to minimize the hardware costs while improving the fine-grained indoor localization accuracy.","PeriodicalId":447934,"journal":{"name":"2015 IEEE 12th International Conference on Wearable and Implantable Body Sensor Networks (BSN)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125372448","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 : 2015-06-09DOI: 10.1109/BSN.2015.7299349
Wen-Tien Huang, Tony Q. S. Quek
In this paper, we design a medium access control (MAC) layer prootocol for wireless body area networks (WBANs) to cope with inter-WBAN interference. Each WBAN consists of a coordinator and multiple sensor nodes. Interference happens when multiple nodes transmit to their coordinators at the same time. To avoid interference among WBANs, carrier sensing multiple access with collision avoidance (CSMA/CA) is implemented at the coordinator level; while for communications within each WBAN, the coordinator uses beacon messages to centrally arrange all the transmissions to avoid collisions. In the proposed protocol, the coordinator adaptively adjusts its frame length based on its perceived interference level. By doing so, a WBAN can enjoy a high throughput under a light interference level, while giving other WBANs a fair share of channel access chance when the number of surrounding WBANs is large. We further design a sensing scheme to reduce the sensing power consumption for the sensor nodes and discuss how to extend the protocol for multi-channel and QoS support. Finally the simulation results verify the effectiveness of the proposed protocol.
{"title":"Adaptive CSMA/CA MAC protocol to reduce inter-WBAN interference for wireless body area networks","authors":"Wen-Tien Huang, Tony Q. S. Quek","doi":"10.1109/BSN.2015.7299349","DOIUrl":"https://doi.org/10.1109/BSN.2015.7299349","url":null,"abstract":"In this paper, we design a medium access control (MAC) layer prootocol for wireless body area networks (WBANs) to cope with inter-WBAN interference. Each WBAN consists of a coordinator and multiple sensor nodes. Interference happens when multiple nodes transmit to their coordinators at the same time. To avoid interference among WBANs, carrier sensing multiple access with collision avoidance (CSMA/CA) is implemented at the coordinator level; while for communications within each WBAN, the coordinator uses beacon messages to centrally arrange all the transmissions to avoid collisions. In the proposed protocol, the coordinator adaptively adjusts its frame length based on its perceived interference level. By doing so, a WBAN can enjoy a high throughput under a light interference level, while giving other WBANs a fair share of channel access chance when the number of surrounding WBANs is large. We further design a sensing scheme to reduce the sensing power consumption for the sensor nodes and discuss how to extend the protocol for multi-channel and QoS support. Finally the simulation results verify the effectiveness of the proposed protocol.","PeriodicalId":447934,"journal":{"name":"2015 IEEE 12th International Conference on Wearable and Implantable Body Sensor Networks (BSN)","volume":"68 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129365649","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 : 2015-06-09DOI: 10.1109/BSN.2015.7299390
Timm Hormann, Peter Christ, Marc Hesse, U. Rückert
Raising the awareness of being physically active by utilizing wearable body sensors has become a popular research topic. Recent approaches combine physical and physiological information to obtain a precise prediction of a person;s physical activity ratio. However, the error in the determination of physical activity due to invalid physiological values that are resulting from underlying signal disturbances, has so far not been considered. We therefore present a robust measure of activity that fuses accelerometer data, heart rate and other personalized features, and is adaptively responding to missing physiological sensor data. To set up the model, we make use of regression analysis (MARS). Our findings indicate the need for considering signal quality when estimating physical activity. The predictive model shows close agreement (R2 = 0.97) to the reference from indirect calorimetry, even if the physiological information is partly corrupted.
{"title":"Robust estimation of physical activity by adaptively fusing multiple parameters","authors":"Timm Hormann, Peter Christ, Marc Hesse, U. Rückert","doi":"10.1109/BSN.2015.7299390","DOIUrl":"https://doi.org/10.1109/BSN.2015.7299390","url":null,"abstract":"Raising the awareness of being physically active by utilizing wearable body sensors has become a popular research topic. Recent approaches combine physical and physiological information to obtain a precise prediction of a person;s physical activity ratio. However, the error in the determination of physical activity due to invalid physiological values that are resulting from underlying signal disturbances, has so far not been considered. We therefore present a robust measure of activity that fuses accelerometer data, heart rate and other personalized features, and is adaptively responding to missing physiological sensor data. To set up the model, we make use of regression analysis (MARS). Our findings indicate the need for considering signal quality when estimating physical activity. The predictive model shows close agreement (R2 = 0.97) to the reference from indirect calorimetry, even if the physiological information is partly corrupted.","PeriodicalId":447934,"journal":{"name":"2015 IEEE 12th International Conference on Wearable and Implantable Body Sensor Networks (BSN)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128842015","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 : 2015-06-09DOI: 10.1109/BSN.2015.7299348
H. Kalantarian, N. Alshurafa, Ebrahim Nemati, Tuan Le, M. Sarrafzadeh
Poor adherence to prescription medication can compromise treatment effectiveness and cost the billions of dollars in unnecessary health care expenses. Though various interventions have been proposed for estimating adherence rates, few have been shown to be effective. Digital systems are capable of estimating adherence without extensive user involvement and can potentially provide higher accuracy with lower user burden than manual methods. In this paper, we propose a smartwatch-based system for detecting adherence to prescription medication based the identification of several motions using the built-in tri-axial accelerometers and gyroscopes. The efficacy of the proposed technique is confirmed through a survey of medication ingestion habits and experimental results on movement classification.
{"title":"A smartwatch-based medication adherence system","authors":"H. Kalantarian, N. Alshurafa, Ebrahim Nemati, Tuan Le, M. Sarrafzadeh","doi":"10.1109/BSN.2015.7299348","DOIUrl":"https://doi.org/10.1109/BSN.2015.7299348","url":null,"abstract":"Poor adherence to prescription medication can compromise treatment effectiveness and cost the billions of dollars in unnecessary health care expenses. Though various interventions have been proposed for estimating adherence rates, few have been shown to be effective. Digital systems are capable of estimating adherence without extensive user involvement and can potentially provide higher accuracy with lower user burden than manual methods. In this paper, we propose a smartwatch-based system for detecting adherence to prescription medication based the identification of several motions using the built-in tri-axial accelerometers and gyroscopes. The efficacy of the proposed technique is confirmed through a survey of medication ingestion habits and experimental results on movement classification.","PeriodicalId":447934,"journal":{"name":"2015 IEEE 12th International Conference on Wearable and Implantable Body Sensor Networks (BSN)","volume":"180 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121823112","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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