Human motion state recognition based on flexible, wearable capacitive pressure sensors

被引:2
|
作者
Yu, Qingyang [1 ]
Zhang, Peng [2 ]
Chen, Yucheng [2 ]
机构
[1] College of Control Science and Engineering, China University of Petroleum, Qingdao,266580, China
[2] Key Laboratory for Robot Intelligent Technology of Shandong Province, Shandong University of Science and Technology, Qingdao,266590, China
基金
中国国家自然科学基金;
关键词
Electrodes - Yarn - Capacitive sensors - Dielectric losses - Pressure sensors - Backpropagation - Composite films - Multiwalled carbon nanotubes (MWCN) - Silicones - Multilayer neural networks - Polydimethylsiloxane - Wearable sensors - Network layers - Barium titanate - Multilayers;
D O I
暂无
中图分类号
学科分类号
摘要
Human motion state recognition technology based on flexible, wearable sensor devices has been widely applied in the fields of human–computer interaction and health monitoring. In this study, a new type of flexible capacitive pressure sensor is designed and applied to the recognition of human motion state. The electrode layers use multi-walled carbon nanotubes (MWCNTs) as con-ductive materials, and polydimethylsiloxane (PDMS) with microstructures is embedded in the surface as a flexible substrate. A composite film of barium titanate (BaTiO3) with a high dielectric con-stant and low dielectric loss and PDMS is used as the intermediate dielectric layer. The sensor has the advantages of high sensitivity (2.39 kPa−1), wide pressure range (0–120 kPa), low pressure reso-lution (6.8 Pa), fast response time (16 ms), fast recovery time (8 ms), lower hysteresis, and stability. The human body motion state recognition system is designed based on a multi-layer back propagation neural network, which can collect, process, and recognize the sensor signals of different motion states (sitting, standing, walking, and running). The results indicate that the overall recognition rate of the system for the human motion state reaches 94%. This proves the feasibility of the human motion state recognition system based on the flexible wearable sensor. Furthermore, the system has high application potential in the field of wearable motion detection. © 2021 by the authors. Li-censee MDPI, Basel, Switzerland.
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