Abstract

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Title:: Neural network-based blood pressure detection algorithms for pulse wave signals

Author(s):: WANG Yifei1; LIU Guangjun1; LIU Xuanji1; CHEN Zhanchun1; 2; ZHANG Yingdong3; 1.College of Mechanical and Vehicle Engineering, Taiyuan University of Technology, Taiyuan 030024, China 2.Plastic Machinery Engineering Virtual Simulation Experiments Teaching Center of Shanxi Province, Taiyuan 030024, China 3. TCM Internal Medicine, Shanxi Hospital of Integrated Traditional Chinese and Western Medicine, Taiyuan 030013, China

Keywords:: Keywords: blood pressure pulse wave characteristic parameter neural network

Abstract:: Abstract: The pulse wave signal contains a large amount of human physiological and pathological information which is closely related to the changes of blood pressure. The blood pressure can be measured continuously and noninvasively using the characteristic parameters of pulse wave signals. Neural network is used in pulse wave blood pressure extraction algorithm because of its strong learning ability, generalization ability and the ability to fully approximate any complex nonlinear relationship. Herein the characteristic parameters of pulse wave are introduced. The advances in research of blood pressure measurement based on the pulse wave characteristic parameters are briefly described, and the neural network-based blood pressure detection algorithm using the pulse wave characteristic parameters is described in details. Finally, the advantages and disadvantages of the network model are analyzed, and the research direction of the neural network-based blood pressure monitoring algorithm using the pulse wave characteristic parameters is discussed.