Smartphones today not only provide computing and communication capabilities but are also equipped with many sensors that enable new applications across several domains, namely healthcare, environmental monitoring, social networks, and transportation. In this paper, we focus on the heathcare domain. We describe a location-based application called Fitness Tour that we have designed for Andorid-based smartphones. Our application includes several new features: (a) randomly generated exercise tours, (b) secure verification of any completed tour, and (c) social network interface that allows participating users to invite friends to view their records or participate in self-organized group competitions. This group feature allows users to exert social pressure on one another to adopt healthier lifestyle via outdoor physical activities. Our main goal is to use this application to encourage children and college students to adopt more active lifestyles and hence combat the obesity problem.
{"title":"Fitness Tour: a mobile application for combating obesity","authors":"M. Chuah, S. Sample","doi":"10.1145/2007036.2007048","DOIUrl":"https://doi.org/10.1145/2007036.2007048","url":null,"abstract":"Smartphones today not only provide computing and communication capabilities but are also equipped with many sensors that enable new applications across several domains, namely healthcare, environmental monitoring, social networks, and transportation. In this paper, we focus on the heathcare domain. We describe a location-based application called Fitness Tour that we have designed for Andorid-based smartphones. Our application includes several new features: (a) randomly generated exercise tours, (b) secure verification of any completed tour, and (c) social network interface that allows participating users to invite friends to view their records or participate in self-organized group competitions. This group feature allows users to exert social pressure on one another to adopt healthier lifestyle via outdoor physical activities. Our main goal is to use this application to encourage children and college students to adopt more active lifestyles and hence combat the obesity problem.","PeriodicalId":150900,"journal":{"name":"International Workshop on Pervasive Wireless Healthcare","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116162058","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}
Ambulances and emergency vehicles (buses and taxis as well), if equipped with wireless devices, can be exploited to harvest medical data during unexpected events and also on a daily basis, from all those patients that require a constant monitoring of health conditions. Ambulances can be utilized as trusted intermediaries to transport medical information, at little cost, to hospital central servers. Patients equipped with physiological sensors connected to wireless devices could dump, during each contact, all the medical information collected so far, thus utilizing emergency vehicles as data mules. Inevitably, contact times may be short and not sufficient to transfer all of the information collected from a patient's medical sensors. In such cases, computing in advance, or during the very initial phase of a data transfer, an estimate of how long a contact time will last is key to maximize the utility of any successfully transmitted chunks, in general of different sizes and priorities, of medical data. In this paper we address the problem of predicting patient-vehicle contact times, through an empirical model based on real-world experiments focused on the key sections of a road, which most influence the average speed of an emergency vehicle that traverses it. Our preliminary results are encouraging, as they indicate that it is possible to predict the time an emergency vehicle will spend traversing a given road segment within one third of its traversal.
{"title":"Efficient vehicle-to-pedestrian exchange of medical data: an empirical model with preliminary results","authors":"G. Marfia, M. Roccetti, C. Palazzi, A. Amoroso","doi":"10.1145/2007036.2007040","DOIUrl":"https://doi.org/10.1145/2007036.2007040","url":null,"abstract":"Ambulances and emergency vehicles (buses and taxis as well), if equipped with wireless devices, can be exploited to harvest medical data during unexpected events and also on a daily basis, from all those patients that require a constant monitoring of health conditions. Ambulances can be utilized as trusted intermediaries to transport medical information, at little cost, to hospital central servers. Patients equipped with physiological sensors connected to wireless devices could dump, during each contact, all the medical information collected so far, thus utilizing emergency vehicles as data mules. Inevitably, contact times may be short and not sufficient to transfer all of the information collected from a patient's medical sensors. In such cases, computing in advance, or during the very initial phase of a data transfer, an estimate of how long a contact time will last is key to maximize the utility of any successfully transmitted chunks, in general of different sizes and priorities, of medical data. In this paper we address the problem of predicting patient-vehicle contact times, through an empirical model based on real-world experiments focused on the key sections of a road, which most influence the average speed of an emergency vehicle that traverses it. Our preliminary results are encouraging, as they indicate that it is possible to predict the time an emergency vehicle will spend traversing a given road segment within one third of its traversal.","PeriodicalId":150900,"journal":{"name":"International Workshop on Pervasive Wireless Healthcare","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133795105","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}
Yang Liu, Robert Kelley, Phani C. Polina, S. Heragu, Anup Kumar
In this paper, we introduce iResTrac, a mobile device application and service-oriented architecture for capturing and retrieving hospital resource information such as beds or ventilators. Our system leverages the continuing penetration of smartphones in the hospital environment to provide medical, cleaning, and maintenance staff with an application that allows them to use a smartphone to scan barcodes to acquire and update information about resources. This solution does not require an additional hardware infrastructure like that required by RFID tags. It uses existing hospital Wi-Fi infrastructure that allows the application to access an in-house web service that exposes methods to update and retrieve information. In addition, the system provides a dashboard application that can be viewed in a traditional web browser or optimized for a tablet device.
{"title":"iResTrac: an architecture for maintaining medical resource status with mobile devices","authors":"Yang Liu, Robert Kelley, Phani C. Polina, S. Heragu, Anup Kumar","doi":"10.1145/2007036.2007049","DOIUrl":"https://doi.org/10.1145/2007036.2007049","url":null,"abstract":"In this paper, we introduce iResTrac, a mobile device application and service-oriented architecture for capturing and retrieving hospital resource information such as beds or ventilators. Our system leverages the continuing penetration of smartphones in the hospital environment to provide medical, cleaning, and maintenance staff with an application that allows them to use a smartphone to scan barcodes to acquire and update information about resources. This solution does not require an additional hardware infrastructure like that required by RFID tags. It uses existing hospital Wi-Fi infrastructure that allows the application to access an in-house web service that exposes methods to update and retrieve information. In addition, the system provides a dashboard application that can be viewed in a traditional web browser or optimized for a tablet device.","PeriodicalId":150900,"journal":{"name":"International Workshop on Pervasive Wireless Healthcare","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121170142","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}
Obesity is a growing healthcare challenge in present days. Objective automated methods of food intake monitoring are necessary to face this challenge in future. A method for non-invasive monitoring of human food intake behavior by the evaluation of chewing and swallowing sounds has been developed. A wearable food intake sensor has been created by integrating in-ear microphone and a reference microphone in a hearing aid case. A concept for food intake monitoring requiring low computational cost is presented. After the detection of food intake activity periods, signal recognition algorithms based on Hidden Markov Models distinguish several types of food based on the sound properties of their chewing sounds. Algorithms are developed using manual labeled records of the food intake sounds of 40 participants.
{"title":"Food intake recognition conception for wearable devices","authors":"S. Päßler, M. Wolff, Wolf-Joachim Fischer","doi":"10.1145/2007036.2007045","DOIUrl":"https://doi.org/10.1145/2007036.2007045","url":null,"abstract":"Obesity is a growing healthcare challenge in present days. Objective automated methods of food intake monitoring are necessary to face this challenge in future. A method for non-invasive monitoring of human food intake behavior by the evaluation of chewing and swallowing sounds has been developed. A wearable food intake sensor has been created by integrating in-ear microphone and a reference microphone in a hearing aid case. A concept for food intake monitoring requiring low computational cost is presented. After the detection of food intake activity periods, signal recognition algorithms based on Hidden Markov Models distinguish several types of food based on the sound properties of their chewing sounds. Algorithms are developed using manual labeled records of the food intake sounds of 40 participants.","PeriodicalId":150900,"journal":{"name":"International Workshop on Pervasive Wireless Healthcare","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128823133","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}
With the rapid growth of elderly population, u-healthcare service combined with advanced wireless networking technology is gaining popularity. The advance in medical sensor technology has boasted up the u-healthcare market potential. However, the global connectivity with a sufficient level of reliability is still an issue to study for its prototype development. The energy efficient packet-level scheduling was studied but the scheduling and management topics in the access stratum, which is the beginning part of end-to-end connection for ubiquitous healthcare service, are still open. In this paper, we study an efficient and adaptive method that can provide u-healthcare user devices with an increased level of access privilege so that the healthcare related user data, which is sometimes delay-critical, can be more favorable admitted to the access stratum. We develop a mathematical formulation for the access control in access stratum domain over the existing 3.9-th generation (3.9G) cellular communication standard, called Long Term Evolution (LTE) and devise an efficient and exact algorithm to solve it. The proposed method has simplicity in implementation and efficiency in operation. In addition, it can improve key performance measures, such as call blocking and call dropping performance.
{"title":"Managing resources for healthcare service calls in a cellular network with relays and machine-type communication nodes","authors":"Ki-Dong Lee, A. Vasilakos","doi":"10.1145/2007036.2007038","DOIUrl":"https://doi.org/10.1145/2007036.2007038","url":null,"abstract":"With the rapid growth of elderly population, u-healthcare service combined with advanced wireless networking technology is gaining popularity. The advance in medical sensor technology has boasted up the u-healthcare market potential. However, the global connectivity with a sufficient level of reliability is still an issue to study for its prototype development. The energy efficient packet-level scheduling was studied but the scheduling and management topics in the access stratum, which is the beginning part of end-to-end connection for ubiquitous healthcare service, are still open. In this paper, we study an efficient and adaptive method that can provide u-healthcare user devices with an increased level of access privilege so that the healthcare related user data, which is sometimes delay-critical, can be more favorable admitted to the access stratum. We develop a mathematical formulation for the access control in access stratum domain over the existing 3.9-th generation (3.9G) cellular communication standard, called Long Term Evolution (LTE) and devise an efficient and exact algorithm to solve it. The proposed method has simplicity in implementation and efficiency in operation. In addition, it can improve key performance measures, such as call blocking and call dropping performance.","PeriodicalId":150900,"journal":{"name":"International Workshop on Pervasive Wireless Healthcare","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133089384","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 primary challenges in deploying a wireless healthcare solution stem from real-time, distributed resource constraints, as well as stringent clinical requirements of reliability, safety, device interoperability, QoS guarantee, and privacy/security. Although optimized solutions exist for each individual element of the system, the complex, distributed, and concurrent interactions among multiple subsystems make system integration a costly bottleneck. We show that end-to-end modeling and analysis using the formalisms of architecture description languages like AADL can alleviate the hurdles of system integration and provide an effective way of addressing these challenges, thereby, making deployments possible.
{"title":"Model-based architecture analysis for wireless healthcare","authors":"Amitava Ghosh, Y. Hui, M. Chiang","doi":"10.1145/2007036.2007051","DOIUrl":"https://doi.org/10.1145/2007036.2007051","url":null,"abstract":"The primary challenges in deploying a wireless healthcare solution stem from real-time, distributed resource constraints, as well as stringent clinical requirements of reliability, safety, device interoperability, QoS guarantee, and privacy/security. Although optimized solutions exist for each individual element of the system, the complex, distributed, and concurrent interactions among multiple subsystems make system integration a costly bottleneck. We show that end-to-end modeling and analysis using the formalisms of architecture description languages like AADL can alleviate the hurdles of system integration and provide an effective way of addressing these challenges, thereby, making deployments possible.","PeriodicalId":150900,"journal":{"name":"International Workshop on Pervasive Wireless Healthcare","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120934402","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}
In this paper, we consider a radio fingerprinting-based localization system for indoor motion capture applications. Fingerprinting allows target localization on the basis of radio-frequency measurements of the Received radio Signal Strength (RSS), taking into account the presence of fading by means of a training phase. Motion capture is then performed by localizing, through fingerprinting, a group of targets placed on the portion of interest of the user arm---the approach can be easily extended to other portions of the user body. We experimentally investigate, through a SunSPOT wireless sensor network test-bed, different fingerprinting-based localization algorithms, namely deterministic and probabilistic, optimizing, in each case, the system parameters. In particular, the optimization is carried out by minimizing the localization error.
{"title":"Fingerprinting-based wireless 3D localization for motion capture applications","authors":"M. Giuberti, M. Martalò, G. Ferrari","doi":"10.1145/2007036.2007044","DOIUrl":"https://doi.org/10.1145/2007036.2007044","url":null,"abstract":"In this paper, we consider a radio fingerprinting-based localization system for indoor motion capture applications. Fingerprinting allows target localization on the basis of radio-frequency measurements of the Received radio Signal Strength (RSS), taking into account the presence of fading by means of a training phase. Motion capture is then performed by localizing, through fingerprinting, a group of targets placed on the portion of interest of the user arm---the approach can be easily extended to other portions of the user body. We experimentally investigate, through a SunSPOT wireless sensor network test-bed, different fingerprinting-based localization algorithms, namely deterministic and probabilistic, optimizing, in each case, the system parameters. In particular, the optimization is carried out by minimizing the localization error.","PeriodicalId":150900,"journal":{"name":"International Workshop on Pervasive Wireless Healthcare","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131311990","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}
A. Weder, M. Pietzsch, S. Zaunseder, M. Zimmerling, S. Netz
The pulse transit time (PTT) is a parameter which can be used to characterize the functional state of the cardiovascular system. The PTT, which is closely connected to the blood pressure, can be derived from an electrocardiogram (ECG) and a simultaneously recorded photoplethysmogram (PPG) signal. In contrast to conventional non-invasive blood pressure measurements, the PTT can be calculated quasi continuously, giving instant feedback to condition changes. Many proposed systems use cables to connect ECG and PPG sensors. This is sufficient for stationary applications. This paper presents a system for wireless PTT measurements that permits patient mobility and thus makes new application scenarios possible. The main challenge of wireless time synchronization, necessary for precise PTT results, is solved using the IEEE 802.15.4 beacon enabled mode.
{"title":"A mobile system for precise wireless pulse transit time (PTT) monitoring","authors":"A. Weder, M. Pietzsch, S. Zaunseder, M. Zimmerling, S. Netz","doi":"10.1145/2007036.2007046","DOIUrl":"https://doi.org/10.1145/2007036.2007046","url":null,"abstract":"The pulse transit time (PTT) is a parameter which can be used to characterize the functional state of the cardiovascular system. The PTT, which is closely connected to the blood pressure, can be derived from an electrocardiogram (ECG) and a simultaneously recorded photoplethysmogram (PPG) signal. In contrast to conventional non-invasive blood pressure measurements, the PTT can be calculated quasi continuously, giving instant feedback to condition changes. Many proposed systems use cables to connect ECG and PPG sensors. This is sufficient for stationary applications. This paper presents a system for wireless PTT measurements that permits patient mobility and thus makes new application scenarios possible. The main challenge of wireless time synchronization, necessary for precise PTT results, is solved using the IEEE 802.15.4 beacon enabled mode.","PeriodicalId":150900,"journal":{"name":"International Workshop on Pervasive Wireless Healthcare","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127690274","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}
Low duty-cycle (LDC) algorithm is interference mitigation technique, which can reduce the average interference to the existing radio systems by lowering pulse repetition interval or pulse occupation time. Moreover, LDC algorithm is also low power consumption by using lowering pulse repetition interval or pulse occupation time. Thus, in order to design a novel ultra wideband (UWB) system for body area network (BAN) application in the low data low power regime, it is necessary to pay special attentions in the energy requirements and the risk factor for tissue heating (damage) of UWB systems from theoretical and practical viewpoints. In this paper, the coexistence environment between low data rate UWB system such as wireless sensor network including BAN and the existing wideband system using OFDM is considered. In order to analyze the interference mitigation capability of LDC algorithm with impulse based UWB (LDC-UWB) system, the frame error rate (FER) of wideband OFDM system is examined for two types of LDC-UWB system: binary pole signals and mono pole signals. We present that LDC algorithm is an efficient interference mitigation technique for low data rate UWB communication for BAN via computer simulations regardless of definitions of transmitted energy of UWB communication system, and also that the binary pole signal is suitable for LDC-UWB system to mitigate interference to the other radio systems. We further investigate the adequate duty-cycle of LDC-UWB system for each definition of transmitted power of UWB communication.
{"title":"Low duty-cycle UWB communications design for body area network","authors":"K. Sodeyama, R. Kohno","doi":"10.1145/2007036.2007039","DOIUrl":"https://doi.org/10.1145/2007036.2007039","url":null,"abstract":"Low duty-cycle (LDC) algorithm is interference mitigation technique, which can reduce the average interference to the existing radio systems by lowering pulse repetition interval or pulse occupation time. Moreover, LDC algorithm is also low power consumption by using lowering pulse repetition interval or pulse occupation time. Thus, in order to design a novel ultra wideband (UWB) system for body area network (BAN) application in the low data low power regime, it is necessary to pay special attentions in the energy requirements and the risk factor for tissue heating (damage) of UWB systems from theoretical and practical viewpoints. In this paper, the coexistence environment between low data rate UWB system such as wireless sensor network including BAN and the existing wideband system using OFDM is considered. In order to analyze the interference mitigation capability of LDC algorithm with impulse based UWB (LDC-UWB) system, the frame error rate (FER) of wideband OFDM system is examined for two types of LDC-UWB system: binary pole signals and mono pole signals. We present that LDC algorithm is an efficient interference mitigation technique for low data rate UWB communication for BAN via computer simulations regardless of definitions of transmitted energy of UWB communication system, and also that the binary pole signal is suitable for LDC-UWB system to mitigate interference to the other radio systems. We further investigate the adequate duty-cycle of LDC-UWB system for each definition of transmitted power of UWB communication.","PeriodicalId":150900,"journal":{"name":"International Workshop on Pervasive Wireless Healthcare","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116856611","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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