5GSS: a framework for 5G-secure-smart healthcare monitoring

被引:22
作者
Hu, Jianqiang [1 ]
Liang, Wei [2 ]
Hosam, Osama [3 ]
Hsieh, Meng-Yen [4 ]
Su, Xin [5 ]
机构
[1] Xiamen Univ Technol, Sch Comp & Informat Engn, Xiamen 361024, Peoples R China
[2] Hunan Univ, Coll Comp Sci & Elect Engn, Changsha, Peoples R China
[3] Taibah Univ, Coll Comp Sci & Engn Yanbu, Yanbu, Saudi Arabia
[4] Providence Univ, Dept Comp Sci & Informat Engn, Taichung, Taiwan
[5] Hunan Police Acad, Hunan Prov Key Lab Network Invest Technol, Changsha, Peoples R China
基金
中国国家自然科学基金;
关键词
Context-aware health situation identification; edge cloud; 5G; healthcare monitoring; EDGE; IOT;
D O I
10.1080/09540091.2021.1977243
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Currently, the main challenges of the frameworks for healthcare monitoring are as follows: minimising latency, especially for delay-sensitive diseases such as sudden heart disease; identifying health situation in a timely and accurate manner when correlating physiological indicators and context information; reducing the risk of exposure because health data are highly private. In response to the above, this paper proposes a framework for 5G-secure-smart healthcare monitoring (5GSS) to achieve the following goals: fast and accurate identification of context-aware health situation, blockchain-based secure data sharing, and low-latency services for emergent patients. The framework consists of a data acquisition layer, a diagnosis and security layer (edge cloud), and a health service layer. The proposed framework adopts the following key technologies: a 5G-IPv6 communication network, context-aware health situation identification-based similarity measure, and blockchain-based secure data sharing mechanism. Finally, a prototype system has been implemented to monitor hypertensive heart disease, confirming its effectiveness with respect to a real scenario. Combined with the data of 45 patients, the prototype system can identify health situations with an accuracy of 96.34% at a sensitivity of 92.46% and a specificity of 93.62%, while significantly reducing the latency and improving the data sharing security.
引用
收藏
页码:139 / 161
页数:23
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