We describe an ultra low power pulse oximeter sensor for long term, non-invasive monitoring of SpO2 and heart rate in Body Area Networks (BAN). Commercial pulse oximeter sensors consume about 20-60 mW of power during continuous operation. Other researchers have shown that accurate and noise robust wireless pulse oximeter sensors can be designed to operate with as little as 1.5 mW. The LEDs consume bulk of the power budget in pulse oximeter sensors. In this work, we describe a compressed sensing approach to sample the photodetector output, so that the LEDs can be turned off for longer periods and thus save sensor power. We randomly sample Photoplethysmogram (PPG) signals with about 10-40x fewer samples than with uniform sampling and demonstrate that the accuracy of heart rate estimation and blood pressure estimation are not compromised, using MIMIC database. This provides power savings of the order of 10-40x for a pulse oximeter sensor, by reducing the duration LEDs need to be turned on.
{"title":"An Ultra Low Power Pulse Oximeter Sensor Based on Compressed Sensing","authors":"P. Baheti, H. Garudadri","doi":"10.1109/BSN.2009.32","DOIUrl":"https://doi.org/10.1109/BSN.2009.32","url":null,"abstract":"We describe an ultra low power pulse oximeter sensor for long term, non-invasive monitoring of SpO2 and heart rate in Body Area Networks (BAN). Commercial pulse oximeter sensors consume about 20-60 mW of power during continuous operation. Other researchers have shown that accurate and noise robust wireless pulse oximeter sensors can be designed to operate with as little as 1.5 mW. The LEDs consume bulk of the power budget in pulse oximeter sensors. In this work, we describe a compressed sensing approach to sample the photodetector output, so that the LEDs can be turned off for longer periods and thus save sensor power. We randomly sample Photoplethysmogram (PPG) signals with about 10-40x fewer samples than with uniform sampling and demonstrate that the accuracy of heart rate estimation and blood pressure estimation are not compromised, using MIMIC database. This provides power savings of the order of 10-40x for a pulse oximeter sensor, by reducing the duration LEDs need to be turned on.","PeriodicalId":269861,"journal":{"name":"2009 Sixth International Workshop on Wearable and Implantable Body Sensor Networks","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124338631","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}
Faults in WSN are very common and appear in different levels of the system. For pervasive applications to be adopted by end-users there is a need for autonomic self-healing. This paper discusses our initial approach to self-healing in WSN and describes experiments with two case studies of body sensor deployment. We evaluate the impact of sensor faults on activity and gesture classification accuracy respectively and develop mechanisms that will allow detection of those faults during system’s operation.
{"title":"Towards Self-Healing in Wireless Sensor Networks","authors":"Themistoklis Bourdenas, M. Sloman","doi":"10.1109/BSN.2009.14","DOIUrl":"https://doi.org/10.1109/BSN.2009.14","url":null,"abstract":"Faults in WSN are very common and appear in different levels of the system. For pervasive applications to be adopted by end-users there is a need for autonomic self-healing. This paper discusses our initial approach to self-healing in WSN and describes experiments with two case studies of body sensor deployment. We evaluate the impact of sensor faults on activity and gesture classification accuracy respectively and develop mechanisms that will allow detection of those faults during system’s operation.","PeriodicalId":269861,"journal":{"name":"2009 Sixth International Workshop on Wearable and Implantable Body Sensor Networks","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133812159","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}
T. Wartzek, Stefan Vogel, Thomas Hennig, O. Brodersen, M. Hülsbusch, M. Herzog, S. Leonhardt
The variability of the heart rate has emerged to a popular marker for the overall condition of the circulatory system. In this paper, a novel approach for determining the heart rate by pulseoxymetric measurements inside the ear (IN-MONIT) is presented. Pulse signals from the auditory canal are mainly influenced by jaw motions. This influence can complicate the precise determination of the pulse rate and may yield lacks in the derivated tachograms. Therefore, the correlation properties of heart beat intervals and the influence of possible lacks in the tachograms on the outcome of the analysis are studied. It is shown that the usage of advanced methods of statistical time series analysis (e.g. Lomb-periodograms) is suitable in order to analyse signals without further complex filter designs. Together with this mathematical approach, the IN-MONIT system offers the opportunity to perform a 24/7 monitoring without disturbing the normal life of the monitored subject.
{"title":"Analysis of Heart Rate Variability with an In-Ear Micro-Optic Sensor in View of Motion Artifacts","authors":"T. Wartzek, Stefan Vogel, Thomas Hennig, O. Brodersen, M. Hülsbusch, M. Herzog, S. Leonhardt","doi":"10.1109/BSN.2009.19","DOIUrl":"https://doi.org/10.1109/BSN.2009.19","url":null,"abstract":"The variability of the heart rate has emerged to a popular marker for the overall condition of the circulatory system. In this paper, a novel approach for determining the heart rate by pulseoxymetric measurements inside the ear (IN-MONIT) is presented. Pulse signals from the auditory canal are mainly influenced by jaw motions. This influence can complicate the precise determination of the pulse rate and may yield lacks in the derivated tachograms. Therefore, the correlation properties of heart beat intervals and the influence of possible lacks in the tachograms on the outcome of the analysis are studied. It is shown that the usage of advanced methods of statistical time series analysis (e.g. Lomb-periodograms) is suitable in order to analyse signals without further complex filter designs. Together with this mathematical approach, the IN-MONIT system offers the opportunity to perform a 24/7 monitoring without disturbing the normal life of the monitored subject.","PeriodicalId":269861,"journal":{"name":"2009 Sixth International Workshop on Wearable and Implantable Body Sensor Networks","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122558599","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}
Body Sensor Network-related applications such as assistive-living environment, orthopedic, physical medicines, and rehabilitation use wearable body sensors like motion trackers to track joint movements and electromyogram sensors to track muscular activities. These sensors provide information in the form of multidimensional time series data. Generally, for these applications, classification or similarity retrieval of human motions is performed by traditional clustering of dimensionally-reduced feature vectors based on joint movements and/or muscular activities. However, local variations in visually-similar sets of human motions cause them to group in different clusters resulting to a lower recall during retrieval. Hence, it is important to evaluate the effect of local variations on the given clustering of feature vectors. In this paper, we represent the local variations in the form of quantitative attributes that are measured from sensors' time series data. And further, we propose a multivariate analysis of variance technique for evaluating the effect of quantitative attributes on the clustering results that are based on different configurations of feature vectors representing joint movements and muscular activities.
{"title":"Evaluating the Effect of Local Variations in Visually-Similar Motions on the Clustering of Body Sensor Features","authors":"G. Pradhan, B. Prabhakaran","doi":"10.1109/BSN.2009.33","DOIUrl":"https://doi.org/10.1109/BSN.2009.33","url":null,"abstract":"Body Sensor Network-related applications such as assistive-living environment, orthopedic, physical medicines, and rehabilitation use wearable body sensors like motion trackers to track joint movements and electromyogram sensors to track muscular activities. These sensors provide information in the form of multidimensional time series data. Generally, for these applications, classification or similarity retrieval of human motions is performed by traditional clustering of dimensionally-reduced feature vectors based on joint movements and/or muscular activities. However, local variations in visually-similar sets of human motions cause them to group in different clusters resulting to a lower recall during retrieval. Hence, it is important to evaluate the effect of local variations on the given clustering of feature vectors. In this paper, we represent the local variations in the form of quantitative attributes that are measured from sensors' time series data. And further, we propose a multivariate analysis of variance technique for evaluating the effect of quantitative attributes on the clustering results that are based on different configurations of feature vectors representing joint movements and muscular activities.","PeriodicalId":269861,"journal":{"name":"2009 Sixth International Workshop on Wearable and Implantable Body Sensor Networks","volume":"110 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117217851","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}
The use of local processing to reduce data transmission rates, and thereby power and bandwidth requirements, is common in wireless sensor networks. Achieving the minimum possible data rate, however, is not always the optimal choice when the effects of packet loss on overall measurement error are considered. This paper presents a case study from the area of wireless inertial motion capture, in which the best distributed processing strategy is shown to be that which minimises inter-packet data dependency, rather than overall data rate. Drawing on this result and further analysis, we identify questions that should be raised during the design process in order to understand the effects of packet loss on distributed signal processing tasks, decide whether the errors are acceptable for an application, and choose appropriate techniques to mitigate them if necessary.
{"title":"Minimising Loss-Induced Errors in Real Time Wireless Sensing by Avoiding Data Dependency","authors":"A. Young, M. J. Ling","doi":"10.1109/BSN.2009.26","DOIUrl":"https://doi.org/10.1109/BSN.2009.26","url":null,"abstract":"The use of local processing to reduce data transmission rates, and thereby power and bandwidth requirements, is common in wireless sensor networks. Achieving the minimum possible data rate, however, is not always the optimal choice when the effects of packet loss on overall measurement error are considered. This paper presents a case study from the area of wireless inertial motion capture, in which the best distributed processing strategy is shown to be that which minimises inter-packet data dependency, rather than overall data rate. Drawing on this result and further analysis, we identify questions that should be raised during the design process in order to understand the effects of packet loss on distributed signal processing tasks, decide whether the errors are acceptable for an application, and choose appropriate techniques to mitigate them if necessary.","PeriodicalId":269861,"journal":{"name":"2009 Sixth International Workshop on Wearable and Implantable Body Sensor Networks","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124502306","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}
C. Hertleer, L. Langenhove, H. Rogier, L. Vallozzi
Because of the emerging research into wearable textile systems, functionality of personal protective clothing is increasingly enhanced. High performance fabrics protect the wearer from extreme environmental conditions, whereas monitoring systems provide information about his physical and surrounding conditions during emergency activities. To transfer the collected data from the sensors as part of the wearable system to an external nearby base station, a wireless communication device is required in the garment. In order to allow maximum integration of this antenna into the clothing, flexible textile antennas are introduced. In this work, a foam-based antenna for integration into a protective outer garment is developed and tested.
{"title":"Off-body Communication for Protective Clothing","authors":"C. Hertleer, L. Langenhove, H. Rogier, L. Vallozzi","doi":"10.1109/BSN.2009.37","DOIUrl":"https://doi.org/10.1109/BSN.2009.37","url":null,"abstract":"Because of the emerging research into wearable textile systems, functionality of personal protective clothing is increasingly enhanced. High performance fabrics protect the wearer from extreme environmental conditions, whereas monitoring systems provide information about his physical and surrounding conditions during emergency activities. To transfer the collected data from the sensors as part of the wearable system to an external nearby base station, a wireless communication device is required in the garment. In order to allow maximum integration of this antenna into the clothing, flexible textile antennas are introduced. In this work, a foam-based antenna for integration into a protective outer garment is developed and tested.","PeriodicalId":269861,"journal":{"name":"2009 Sixth International Workshop on Wearable and Implantable Body Sensor Networks","volume":"65 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124636842","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}
Cairan He, A. Arora, M. Kiziroglou, D. Yates, D. O’Hare, E. Yeatman
One of the main challenges in developing wireless biometric sensors is the requirement for integration of various systems into a very compact device. Such systems include sensing units, conditioning electronics, transmitters and power supplies. In this work, a novel system integration architecture is presented. A unique feature of this new architecture is that the sub-systems are selected and designed for direct output-to-input connection. An array of active pH sensors is used to transform a pH level to an electrical potential in the range of 0 - 2 Volts. This signal is amplified by an electrostatic energy harvester suitable for human motion operation. The amplified signal drives a custom LC transmitter specially designed to suit the harvester output. A system of notable simplicity is achieved and may serve as a demonstrator for other wireless sensors.
{"title":"MEMS Energy Harvesting Powered Wireless Biometric Sensor","authors":"Cairan He, A. Arora, M. Kiziroglou, D. Yates, D. O’Hare, E. Yeatman","doi":"10.1109/BSN.2009.28","DOIUrl":"https://doi.org/10.1109/BSN.2009.28","url":null,"abstract":"One of the main challenges in developing wireless biometric sensors is the requirement for integration of various systems into a very compact device. Such systems include sensing units, conditioning electronics, transmitters and power supplies. In this work, a novel system integration architecture is presented. A unique feature of this new architecture is that the sub-systems are selected and designed for direct output-to-input connection. An array of active pH sensors is used to transform a pH level to an electrical potential in the range of 0 - 2 Volts. This signal is amplified by an electrostatic energy harvester suitable for human motion operation. The amplified signal drives a custom LC transmitter specially designed to suit the harvester output. A system of notable simplicity is achieved and may serve as a demonstrator for other wireless sensors.","PeriodicalId":269861,"journal":{"name":"2009 Sixth International Workshop on Wearable and Implantable Body Sensor Networks","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132120478","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. Cutcutache, T. Dang, W. Leong, Shanshan Liu, K. D. Nguyen, Linh T. X. Phan, J. Sim, Z. Sun, T. Tok, Lin Xu, F. Tay, W. Wong
A biomonitoring application running on wireless BAN has stringent timing and energy requirements. Developing such applications therefore presents unique challenges in both hardware and software designs. This paper shows how we successfully apply our full-system simulator to a MEMSWear-Biomonitoring application. The simulation results, together with a set of investigative guidelines, enable us to identify and overcome performance bottlenecks. Our simulator is able to obtain timing and energy measurements for each function in the program as well as for each module in the hardware. Without such detail and accurate information, we would not be able to identify the reason for the low performance in the original application.
{"title":"BSN Simulator: Optimizing Application Using System Level Simulation","authors":"I. Cutcutache, T. Dang, W. Leong, Shanshan Liu, K. D. Nguyen, Linh T. X. Phan, J. Sim, Z. Sun, T. Tok, Lin Xu, F. Tay, W. Wong","doi":"10.1109/BSN.2009.22","DOIUrl":"https://doi.org/10.1109/BSN.2009.22","url":null,"abstract":"A biomonitoring application running on wireless BAN has stringent timing and energy requirements. Developing such applications therefore presents unique challenges in both hardware and software designs. This paper shows how we successfully apply our full-system simulator to a MEMSWear-Biomonitoring application. The simulation results, together with a set of investigative guidelines, enable us to identify and overcome performance bottlenecks. Our simulator is able to obtain timing and energy measurements for each function in the program as well as for each module in the hardware. Without such detail and accurate information, we would not be able to identify the reason for the low performance in the original application.","PeriodicalId":269861,"journal":{"name":"2009 Sixth International Workshop on Wearable and Implantable Body Sensor Networks","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130680616","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}
This paper presents a novel ear-worn reflective photoplethysmography (PPG) sensor that addresses the mechanical complexities of coupling the sensor to the surface of the skin and a detection circuit that minimises ambient noise artefacts. The flexible optoelectronic transducer structure can adapt to a variety of skin surface contours. Light emitting diode (LED) modulation and a unique integrating photocurrent demodulator reduce susceptibility to wideband noise and allow subtraction of ambient light from the desired PPG signal. Experimental results demonstrate that the sensitivity is robust to sensor location and application pressure variations. Simulations also show that the photodetection method is resilient against high levels of wideband noise.
{"title":"A Flexible, Low Noise Reflective PPG Sensor Platform for Ear-Worn Heart Rate Monitoring","authors":"J. Patterson, D. McIlwraith, Guang-Zhong Yang","doi":"10.1109/BSN.2009.16","DOIUrl":"https://doi.org/10.1109/BSN.2009.16","url":null,"abstract":"This paper presents a novel ear-worn reflective photoplethysmography (PPG) sensor that addresses the mechanical complexities of coupling the sensor to the surface of the skin and a detection circuit that minimises ambient noise artefacts. The flexible optoelectronic transducer structure can adapt to a variety of skin surface contours. Light emitting diode (LED) modulation and a unique integrating photocurrent demodulator reduce susceptibility to wideband noise and allow subtraction of ambient light from the desired PPG signal. Experimental results demonstrate that the sensitivity is robust to sensor location and application pressure variations. Simulations also show that the photodetection method is resilient against high levels of wideband noise.","PeriodicalId":269861,"journal":{"name":"2009 Sixth International Workshop on Wearable and Implantable Body Sensor Networks","volume":"104 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126928240","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}
R. King, D. McIlwraith, Benny P. L. Lo, J. Pansiot, A. Mcgregor, Guang-Zhong Yang
This paper presents a prototype for monitoring the kinematics of the femur and lower back (sacrum and thoraco-lumbar junction) during rowing. Data is collected from inertial sensors attached to the rower and a simple yet relatively accurate method for determining the rotation of the lower back and femur in the sagittal plane is presented. We also present results from an initial validation experiment using an optical tracking system which demonstrate that it is possible to monitor rowers using the proposed sensors and identify some common poor rowing techniques. Due to their small size, wireless capability and lightweight characteristics, the proposed Body Sensor Network (BSN) system has the potential to be used during ergometer sessions and whilst training on the water.
{"title":"Body Sensor Networks for Monitoring Rowing Technique","authors":"R. King, D. McIlwraith, Benny P. L. Lo, J. Pansiot, A. Mcgregor, Guang-Zhong Yang","doi":"10.1109/BSN.2009.60","DOIUrl":"https://doi.org/10.1109/BSN.2009.60","url":null,"abstract":"This paper presents a prototype for monitoring the kinematics of the femur and lower back (sacrum and thoraco-lumbar junction) during rowing. Data is collected from inertial sensors attached to the rower and a simple yet relatively accurate method for determining the rotation of the lower back and femur in the sagittal plane is presented. We also present results from an initial validation experiment using an optical tracking system which demonstrate that it is possible to monitor rowers using the proposed sensors and identify some common poor rowing techniques. Due to their small size, wireless capability and lightweight characteristics, the proposed Body Sensor Network (BSN) system has the potential to be used during ergometer sessions and whilst training on the water.","PeriodicalId":269861,"journal":{"name":"2009 Sixth International Workshop on Wearable and Implantable Body Sensor Networks","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134500560","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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