title: Wireless Sensor-Based Smart-Clothing Platform for ECG Monitoring.
abstract: The goal of this study is to use wireless sensor technologies to develop a smart clothes service platform for health monitoring. Our platform consists of smart clothes, a sensor node, a gateway server, and a health cloud. The smart clothes have fabric electrodes to detect electrocardiography (ECG) signals. The sensor node improves the accuracy of QRS complexes detection by morphology analysis and reduces power consumption by the power-saving transmission functionality. The gateway server provides a reconfigurable finite state machine (RFSM) software architecture for abnormal ECG detection to support online updating. Most normal ECG can be filtered out, and the abnormal ECG is further analyzed in the health cloud. Three experiments are conducted to evaluate the platform's performance. The results demonstrate that the signal-to-noise ratio (SNR) of the smart clothes exceeds 37 dB, which is within the "very good signal" interval. The average of the QRS sensitivity and positive prediction is above 99.5%. Power-saving transmission is reduced by nearly 1980 times the power consumption in the best-case analysis.
authors.affiliation: School of Software Technology, Dalian University of Technology, Dalian 116620, China.
authors.forename: Jie
authors.initials: J
authors.lastname: Wang
authors.affiliation: Department of Computer Science and Information Engineering, Healthy Aging Research Center, Chang Gung University, Taoyuan 33302, Taiwan.
authors.forename: Chung-Chih
authors.initials: CC
authors.lastname: Lin
authors.affiliation: School of Software Technology, Dalian University of Technology, Dalian 116620, China.
authors.forename: Yan-Shuo
authors.initials: YS
authors.lastname: Yu
authors.affiliation: Department of Computer Science and Information Engineering, Healthy Aging Research Center, Chang Gung University, Taoyuan 33302, Taiwan.
authors.forename: Tsang-Chu
authors.initials: TC
authors.lastname: Yu
mesh_terms: D000465:Algorithms; D003020:Clothing; D019295:Computational Biology; D003936:Diagnosis, Computer-Assisted / Q000295:instrumentation / Q000379:methods / Q000706:statistics & numerical data; D004562:Electrocardiography / Q000295:instrumentation / Q000379:methods* / Q000706:statistics & numerical data; D004867:Equipment Design; D006801:Humans; D059629:Signal-To-Noise Ratio; D012984:Software; D059015:Wireless Technology / Q000295:instrumentation / Q000706:statistics & numerical data