DocumentCode :
652149
Title :
Finding Needles in a Haystack: Reducing False Alarm Rate Using Telemedicine Mobile Cloud
Author :
Qiong Gui ; Xiaoliang Wang ; Bingwei Liu ; Zhanpeng Jin ; Yu Chen
Author_Institution :
Dept. of Electr. & Comput. Eng., Binghamton Univ., Binghamton, NY, USA
fYear :
2013
fDate :
9-11 Sept. 2013
Firstpage :
541
Lastpage :
544
Abstract :
Wearable body sensors have been widely used to monitor the health status of seniors or patients who live alone. Alarms are sent to e-Health providers when dangerous symptoms are detected. However, high false alarm rate significantly limits the effectiveness of medical monitoring. Telemedicine Mobile Cloud (TMC), leveraging recent advances in sensing, networking, and computing technologies, is an effective and promising solution. In this paper, a TMC based strategy has been proposed, which identifies needles (real dangers) among the haystacks (alarms) by taking advantage of the real-time, on-site monitoring capability of Android mobile device and the abundant computing power of the cloud. Extensive experimental study has verified that the TMC-enhanced strategy has effectively reduced the false alarm rate.
Keywords :
body sensor networks; cloud computing; mobile computing; patient monitoring; telemedicine; wearable computers; Android mobile device; TMC based strategy; TMC-enhanced strategy; e-health providers; false alarm rate; health status; medical monitoring; needles; onsite monitoring capability; telemedicine mobile cloud; wearable body sensors; Biomedical monitoring; Fuzzy logic; Medical services; Mobile handsets; Monitoring; Support vector machines; Telemedicine; False Positive Alarms; Remote Patient Monitoring; Telemedicine Mobile Cloud; e-Health Service;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Healthcare Informatics (ICHI), 2013 IEEE International Conference on
Conference_Location :
Philadelphia, PA
Type :
conf
DOI :
10.1109/ICHI.2013.84
Filename :
6680532
Link To Document :
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