Proceedings Wireless Health ... [electronic resource]. Wireless Health (Conference)最新文献_第10页

A context-management framework for telemedicine: an emergency medicine case study 远程医疗情境管理框架:急诊医学案例研究

Proceedings Wireless Health ... [electronic resource]. Wireless Health (Conference) Pub Date : 2010-10-05 DOI: 10.1145/1921081.1921101

Rita H. Wouhaybi, M. Yarvis, Philip Muse, Chieh-Yih Wan, Sangita Sharma, Sai Prasad, Lenitra M. Durham, R. Sahni, R. Norton, Merlin Curry, H. Jimison, R. Harper, R. Lowe

引用次数: 8

Breath analysis with laser sensors on an Android platform 在Android平台上使用激光传感器进行呼吸分析

Proceedings Wireless Health ... [electronic resource]. Wireless Health (Conference) Pub Date : 2010-10-05 DOI: 10.1145/1921081.1921111

Siddharth Gupta, P. Breen, Duo Wu, A. Sabharwal

引用次数: 2

Blood oxygen estimation from compressively sensed photoplethysmograph 用压感光容积描记仪估计血氧

Proceedings Wireless Health ... [electronic resource]. Wireless Health (Conference) Pub Date : 2010-10-05 DOI: 10.1145/1921081.1921084

P. Baheti, H. Garudadri, Somdeb Majumdar

引用次数: 4

The Berkeley Tricorder: wireless health monitoring 伯克利三录仪:无线健康监测

Proceedings Wireless Health ... [electronic resource]. Wireless Health (Conference) Pub Date : 2010-10-05 DOI: 10.1145/1921081.1921117

Reza Naima, J. Canny

引用次数: 1

A platform for implantable medical device validation: demo abstract 植入式医疗器械验证平台:演示摘要

Proceedings Wireless Health ... [electronic resource]. Wireless Health (Conference) Pub Date : 2010-10-05 DOI: 10.1145/1921081.1921115

Zhihao Jiang, M. Pajic, Allison T. Connolly, S. Dixit, R. Mangharam

{"title":"A platform for implantable medical device validation: demo abstract","authors":"Zhihao Jiang, M. Pajic, Allison T. Connolly, S. Dixit, R. Mangharam","doi":"10.1145/1921081.1921115","DOIUrl":"https://doi.org/10.1145/1921081.1921115","url":null,"abstract":"We present the design of an integrated modeling platform to investigate efficient methodologies for certifying medical device software. The outcome of this research has the potential to expedite medical device software certification for safer operation. Our specific focus in this study is on our ongoing research in artificial pacemaker software. Designing bug-free medical device software is difficult, especially in complex implantable devices that may be used in unanticipated contexts. In the 20-year period from 1985 to 2005, the US Food and Drug Administration's (FDA) Maude database records almost 30,000 deaths and almost 600,000 injuries from device failures [1]. There is currently no formal methodology or open experimental platform to validate and verify the correct operation of medical device software. To this effect, a real-time Virtual Heart Model (VHM) has been developed to model the electrophysiological operation of the functioning (i.e. during normal sinus rhythm) and malfunctioning (i.e. during arrhythmia) heart. We present a methodology to extract timing properties of the heart to construct a timed-automata model. The platform exposes functional and formal interfaces for validation and verification of implantable cardiac devices. We demonstrate the VHM is capable of generating clinically-relevant response to intrinsic (i.e. premature stimuli) and external (i.e. artificial pacemaker) signals for a variety of common arrhythmias. By connecting the VHM with a pacemaker model, we are able to pace and synchronize the heart during the onset of irregular heart rhythms. The VHM has been implemented on a hardware platform for closed-loop experimentation with existing and virtual medical devices.","PeriodicalId":91386,"journal":{"name":"Proceedings Wireless Health ... [electronic resource]. Wireless Health (Conference)","volume":"3 1","pages":"208-209"},"PeriodicalIF":0.0,"publicationDate":"2010-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87445694","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}

引用次数: 5

Comparative study of segmentation of periodic motion data for mobile gait analysis 周期运动数据分割在移动步态分析中的比较研究

Proceedings Wireless Health ... [electronic resource]. Wireless Health (Conference) Pub Date : 2010-10-05 DOI: 10.1145/1921081.1921099

Aris Valtazanos, D. Arvind, S. Ramamoorthy

引用次数: 19

A multimodal sensing system for detection of traumatic brain injury 一种用于外伤性脑损伤检测的多模态传感系统

Proceedings Wireless Health ... [electronic resource]. Wireless Health (Conference) Pub Date : 2010-10-05 DOI: 10.1145/1921081.1921110

P. Ganapathy, J. Yadegar, Niranajan Kamath, Shantanu H. Joshi, C. Caluser

{"title":"A multimodal sensing system for detection of traumatic brain injury","authors":"P. Ganapathy, J. Yadegar, Niranajan Kamath, Shantanu H. Joshi, C. Caluser","doi":"10.1145/1921081.1921110","DOIUrl":"https://doi.org/10.1145/1921081.1921110","url":null,"abstract":"We propose to develop a portable, handheld, noninvasive solution for accurate screening and real-time monitoring of traumatic brain injury (TBI) in ambulatory/emergency response scenarios. A layered sensing concept that unifies modalities such as a) ultrasound (US) (B-mode, Doppler flow), b) tonometry and c) pulse oximeter to predict TBI, its severity and mode of recommendations for emergency medical service (EMS) personnel is currently investigated. Specifically, we aim to determine novel 3D morphometric parameters of optic nerve sheath (ONS) that can predict elevated intracranial pressure (EICP) from US data. These parameters when combined with intraocular pressure (IOP), blood oxygen saturation (SaO2) and Doppler flow readings of the carotid artery can improve the overall classification accuracy. In addition, we have also developed a preliminary decision-support system (DSS) to provide an automated analysis of subject's brain health status and thereby, recommend further screening, etc. In the demo, we would show the chain of processing starting from capture of our desired signals from a volunteer, pre-processing (reformatting, de-noising) of US data, post-processing of features extracted from the 3D US model and finally, the classification output of the DSS.","PeriodicalId":91386,"journal":{"name":"Proceedings Wireless Health ... [electronic resource]. Wireless Health (Conference)","volume":"20 1","pages":"198-199"},"PeriodicalIF":0.0,"publicationDate":"2010-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86063731","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}

引用次数: 0

AndWellness: an open mobile system for activity and experience sampling AndWellness:一个用于活动和体验采样的开放式移动系统

Proceedings Wireless Health ... [electronic resource]. Wireless Health (Conference) Pub Date : 2010-10-05 DOI: 10.1145/1921081.1921087

John Hicks, N. Ramanathan, Donnie H. Kim, Mohamad Monibi, J. Selsky, Mark H. Hansen, D. Estrin

引用次数: 132

Dandelion: a framework for transparently programming phone-centered wireless body sensor applications for health 蒲公英:一个透明的以手机为中心的健康无线身体传感器应用程序编程框架

Proceedings Wireless Health ... [electronic resource]. Wireless Health (Conference) Pub Date : 2010-10-05 DOI: 10.1145/1921081.1921091

F. Lin, Ahmad Rahmati, Lin Zhong

{"title":"Dandelion: a framework for transparently programming phone-centered wireless body sensor applications for health","authors":"F. Lin, Ahmad Rahmati, Lin Zhong","doi":"10.1145/1921081.1921091","DOIUrl":"https://doi.org/10.1145/1921081.1921091","url":null,"abstract":"Many innovative mobile health applications can be enabled by augmenting wireless body sensors to mobile phones, e.g. monitoring personal fitness with on-body accelerometer and EKG sensors. However, it is difficult for the majority of smartphone developers to program wireless body sensors directly; current sensor nodes require developers to master node-level programming, implement the communication between the smartphone and sensors, and even learn new languages. The large gap between existing programming styles for smartphones and sensors prevents body sensors from being widely adopted by smartphone applications, despite the burgeoning Apple App Store and Android Market.\u0000 To bridge this programming gap, we present Dandelion1, a novel framework for developing wireless body sensor applications on smartphones. Dandelion provides three major benefits: 1) platform-agnostic programming abstraction for in-sensor data processing, called senselet, 2) transparent integration of senselets and the smartphone code, and 3) platform-independent development and distribution of senselets.\u0000 We provide an implementation of Dandelion on the Maemo Linux smartphone platform and the Rice Orbit body sensor platform. We evaluate Dandelion by implementing real-world applications, and show that Dandelion effectively eliminates the programming gap and significantly reduces the development efforts. We further show that Dandelion incurs a very small overhead; in total less than 5% of the memory capacity and less than 3% of the processor time of a typical ultra low power sensor.","PeriodicalId":91386,"journal":{"name":"Proceedings Wireless Health ... [electronic resource]. Wireless Health (Conference)","volume":"59 1","pages":"74-83"},"PeriodicalIF":0.0,"publicationDate":"2010-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88513644","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}

引用次数: 30

Remote physiological monitoring of first responders with intermittent network connectivity 具有间歇性网络连接的急救人员的远程生理监测

Proceedings Wireless Health ... [electronic resource]. Wireless Health (Conference) Pub Date : 2010-10-05 DOI: 10.1145/1921081.1921090

Jingyuan Li, Tejaswi Tamminedi, Guy Yosiphon, A. Ganguli, Lei Zhang, J. Stankovic, J. Yadegar

{"title":"Remote physiological monitoring of first responders with intermittent network connectivity","authors":"Jingyuan Li, Tejaswi Tamminedi, Guy Yosiphon, A. Ganguli, Lei Zhang, J. Stankovic, J. Yadegar","doi":"10.1145/1921081.1921090","DOIUrl":"https://doi.org/10.1145/1921081.1921090","url":null,"abstract":"First responders have been observed to be at increased risk of cardio-vascular diseases compared to the general population. A high percentage of cardiac events have been found to occur during missions. Continuous physiological monitoring during missions can be effective in reducing the number of fatalities. Real-time physiological data such as ECG can be collected using body-worn sensors. This sensor data can be processed on the body itself or can be communicated over an ad hoc wireless network to the incident command center located nearby. First responder missions often take place inside building structures where network connectivity is intermittent. Intermittent connectivity can lead to loss of critical physiological data or delay in that information reaching the base station. Hence, some amount of local processing is needed in order to limit the amount of data that is communicated. In this paper, we introduce a novel Hidden Markov Model based classifier for myocardial infarction detection. The classifier fidelity can be adapted based on the processing power available. We present a peer-to-peer networking protocol for communication over disrupted networks. A low fidelity classifier is used to perform local processing and assign priorities to the data based on its criticality. It is complemented by a disruption-aware epidemic forwarding protocol for transferring first responder's physiological data to the base station. We show that with prioritized epidemic forwarding and buffer eviction policy, packet delivery ratio for abnormal data increases and the latency associated with abnormal packets reaching the destination decreases.","PeriodicalId":91386,"journal":{"name":"Proceedings Wireless Health ... [electronic resource]. Wireless Health (Conference)","volume":"9 1","pages":"64-73"},"PeriodicalIF":0.0,"publicationDate":"2010-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86968767","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}

引用次数: 1