SPHA: Smart Personal Health Advisor Based on Deep Analytics

被引：93

作者：

Chen, Min ^{[1
,2
]}

Zhang, Yin ^{[3
]}

Qiu, Meikang ^{[4
]}

Guizani, Nadra ^{[5
]}

Hao, Yixue ^{[1
]}

机构：

[1] Huazhong Univ Sci & Technol, Sch Comp Sci & Technol, Wuhan, Hubei, Peoples R China

[2] WNLO, Wuhan, Hubei, Peoples R China

[3] Zhongnan Univ Econ & Law, Sch Informat & Safety Engn, Wuhan, Hubei, Peoples R China

[4] Columbia Univ, Elect Engn, New York, NY 10027 USA

[5] Purdue Univ, W Lafayette, IN 47907 USA

来源：

IEEE COMMUNICATIONS MAGAZINE | 2018年 / 56卷 / 03期

基金：

中国国家自然科学基金;

关键词：

D O I：

10.1109/MCOM.2018.1700274

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

According to a report by the World Health Organization, diseases caused by an unhealthy lifestyle represent the leading cause of death all over the world. Therefore, it is crucial to monitor and avoid users' unhealthy behaviors. Existing health monitoring approaches still face many challenges of limited intelligence due to insufficient healthcare data. Therefore, this article proposes a smart personal health advisor (SPHA) for comprehensive and intelligent health monitoring and guidance. The SPHA monitors both physiological and psychological states of the user. The SPHA-Score model is proposed to evaluate the overall health status of the user. Finally, a testbed for verification of feasibility and applicability of the proposed system was developed. The experimental and simulation results have shown that the proposed approach is efficient for proper user state monitoring.

引用

页码：164 / 169

页数：6

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