An Adaptive Sensor Data Segments Selection Method for Wearable Health Care Services.
As cloud computing and wearable devices technologies mature, relevant services have grown more and more popular in recent years. The healthcare field is one of the popular services for this technology that adopts wearable devices to sense signals of negative physiological events, and to notify users. The development and implementation of long-term healthcare monitoring that can prevent or quickly respond to the occurrence of disease and accidents present an interesting challenge for computing power and energy limits. This study proposed an adaptive sensor data segments selection method for wearable health care services, and considered the sensing frequency of the various signals from human body, as well as the data transmission among the devices. The healthcare service regulates the sensing frequency of devices by considering the overall cloud computing environment and the sensing variations of wearable health care services. The experimental results show that the proposed service can effectively transmit the sensing data and prolong the overall lifetime of health care services.
Department of Engineering Science, National Cheng Kung University, Tainan, 701, Taiwan, Republic of China. n98014045@mail.ncku.edu.tw.
Shih-Yeh
SY
Chen
School of Computer & Software, 210044, Nanjing, China. cinfon@ieee.org.|Department of Computer Science and Information Engineering, National Chung Cheng University, Chiayi, 621, Taiwan, Republic of China. cinfon@ieee.org.
Chin-Feng
CF
Lai
Department of Computer Science and Information Engineering, National Chung Cheng University, Chiayi, 621, Taiwan, Republic of China. rhhwang@cs.ccu.edu.tw.
Ren-Hung
RH
Hwang
Smart Network System Institute, Institute for Information Industry, Taipei, 105, Taiwan, Republic of China. teddylai@iii.org.tw.
Ying-Hsun
YH
Lai
Department of Engineering Science, National Cheng Kung University, Tainan, 701, Taiwan, Republic of China. mswang@mail.ncku.edu.tw.
Ming-Shi
MS
Wang
D000465:Algorithms; D000067917:Cloud Computing; D003195:Computer Communication Networks / Q000295:instrumentation*; D006801:Humans; D058998:Remote Sensing Technology / Q000295:instrumentation*; D017216:Telemedicine / Q000295:instrumentation*; D059015:Wireless Technology / Q000295:instrumentation*
Cloud computing; Segments selection; Wearable health care