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作 者:Maowen Sun Songya Cui Zezheng Wang Huayu Luo Huayong Yang Xiaoping Ouyang Kaichen Xu
机构地区:[1]State Key Laboratory of Fluid Power and Mechatronic Systems,School of Mechanical Engineering,Zhejiang University,Hangzhou,310027,China [2]School of Information and Electrical Engineering,Hangzhou City University,Hangzhou,310015,China
出 处:《Microsystems & Nanoengineering》2024年第2期269-277,共9页微系统与纳米工程(英文)
基 金:supported by the STI 2030—Major Projects(2022ZD0208601);the National Natural Science Foundation of China(52305077,52105593);the Zhejiang Provincial Natural Science Foundation of China(LDQ24E050001);the“Pioneer”and“Leading Goose”R&D Program of Zhejiang(2023C01051,2023C03007).
摘 要:As a reinforcement technology that improves load-bearing ability and prevents injuries,assisted exoskeleton robots have extensive applications in freight transport and health care.The perception of gait information by such robots is vital for their control.This information is the basis for motion planning in assistive and collaborative functions.Here,a wearable gait recognition sensor system for exoskeleton robots is presented.Pressure sensor arrays based on laser-induced graphene are developed with flexibility and reliability.Multiple sensor units are integrated into an insole to detect real-time pressure at key plantar positions.In addition,the circuit hardware and the algorithm are designed to reinforce the sensor system with the capability of gait recognition.The experimental results show that the accuracy of gait recognition by the proposed system is 99.85%,and the effectiveness of the system is further verified through testing on an exoskeleton robot.
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