Application of intelligent monitoring system for integrated multi-physiological parameters and environment information for CAPF sentry based on domestic CPU
CHENG Naijun1, ZHOU Jinzhi2, ZHOU Jianli1, WU Bin2, HAN Bin2, and LUO Lu1
1.Sichuan Provincial Corps Hospital,Chinese People's Armed Police Force, Leshan 614000 ,China; 2.School of Information Engineering, Southwest University of Science and Technology,Mianyang 621010, China
Abstract：Objective To design a surveillance system for the Chinese Armed Police Force (CAPF below)that can monitor integrated physiological signal parameters with environment prescreening using informationization methods so as to provide visualized early warning about the physiological and environmental status of CAPF sentry for supervisors.Methods Massive data and artificial intelligence(AI) were used to build an intelligent surveillance system based on home-made CPU that could collect integrated multi-physiological parameters and environment information for CAPF sentry. This system was capable of real-time monitoring and analysis of CAPF sentry's physiological signal parameters and the environment information on the post in an integrated monitoring center.Results The construction of this system optimized information security methods to a great extent, thus improving the quality of real-time and multi-path care to CAPF sentry. Sentry supervisors could be warned of any health emergency according to the change of physiological parameters of the sentry in order to take immediate measures.Conclusions This system is capable of real-time surveillance and analysis of physiological signal parameters and environment information of the sentry so that early warning has become possible.
程乃俊, 周金治, 周建丽, 吴斌, 韩宾, 罗卢. 武警哨兵国产CPU 芯片集成多生理参数及环境信息智能监测系统的设计与应用研究[J]. 武警医学, 2018, 29(1): 32-34.
CHENG Naijun, ZHOU Jinzhi, ZHOU Jianli, WU Bin, HAN Bin, and LUO Lu. Application of intelligent monitoring system for integrated multi-physiological parameters and environment information for CAPF sentry based on domestic CPU. Med. J. Chin. Peop. Armed Poli. Forc., 2018, 29(1): 32-34.
2018, Vol. 29 
