ISSN 0914-4935
Sensors and Materials
is an international peer-reviewed open access journal to provide a forum for researchers working in multidisciplinary fields of sensing technology.
Sensors and Materials
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Development of a Novel Health Promotion System Based on Wireless Sensor Network and Cloud Computing

Shih-Sung Lin and Jia-Jun Lin

(Received October 24, 2018; Accepted January 30, 2019)

Keywords: health promotion system, exercise prescription, cloud service, wireless sensor network, mobile phone push service

Existing health promotion systems (HPSs) have possess some shortcomings, such as lacking in the ability to plan exercise prescriptions for individuals automatically, being difficult to timely acquire physiologic signals of users who are doing exercise, and having no efficient mechanisms for notifying the medical personnel of users’ emergent conditions. Aimed at addressing these shortcomings, this study leverages the technologies of wireless sensor network (WSN), mobile communication, and cloud computing to develop a cloud-based HPS. The HPS contains a health promotion cloud service platform that can construct users’ physical fitness models and then generate appropriate exercise prescriptions for the users to do various exercises. On the user side, this study designs an exercise sensing device that can timely acquire the physiologic signals and global positioning system (GPS) positioning information of users who are doing exercise through the WSN. Several sensors are design into the exercise sensing device, such as SpO_2 and GPS sensor. It can then send those data to the cloud service platform through mobile phone communication to facilitate the users to master their exercise records. This study also designs a cloud alarm mechanism that can efficiently notify the medical personnel and family members of the user’s emergent states through mobile phone push service. In addition, on the basis of fuzzy inference, this study develops an exercise prescription adaptation mechanism that can accept the feedback information from the user and can then automatically adjust the user’s exercise prescription to an appropriate strength level. The results of this study can be a useful reference for constructing new-generation HPSs.

Corresponding author: Shih-Sung Lin



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