摘要
针对老年人使用步行训练机器人康复过程中,因步行速度与机器人指定速度不协调而引发的跌倒事故问题,本文提出了一种人机速度协调防跌倒方法,该方法由跌倒预测模型和防跌倒控制方法两部分组成。首先,由惯性传感单元(IMU)采集受试者步行姿态信号,利用长短期记忆网络(LSTM)和注意力机制构建老年人跌倒预测模型;其次,在跌倒预测的基础上,设计多元相空间重构(PSR)速度预测模型,用于防跌倒控制器的设计;最后,将受试者的速度预测结果作为目标速度,利用PSR理论和模型预测控制技术(MPC),设计步行康复训练机器人的防跌倒控制器,实现对受试者步行速度的精确跟踪,避免在康复训练过程中因人机速度不协调引发的跌倒事故。仿真对比分析和实验研究结果表明,跌倒预测模型的预测准确率可达到95.2%,且跌倒预测的前置时间可达1.82 s,人机速度协调防跌倒方法可有效防止受试者步行速度与机器人指定速度不协调而发生跌倒事故,使受试者安全地完成步行康复训练。
In response to the problem of falls caused by incoordination between the walking speed of the elderly and the designated speed of the walking rehabilitation training robot during rehabilitation,this paper proposes a human-robot speed coordination anti-falling method,consisting of two parts:a falling prediction model and an anti-falling control method.First,the walking posture signals of the subject are collected by an inertial measurement unit(IMU),and a falling prediction model for the elderly is constructed using long short-term memory(LSTM)network and attention mechanism.Second,based on the falling prediction,a multi-dimensional phase space reconstruction(PSR)speed prediction model is designed for the anti-falling controller.Finally,the predicted speed of the subject is used as the target speed,and the PSR theory and model predictive control(MPC)technology are used to design an anti-falling controller for the walking rehabilitation training robot,achieving precise tracking of the subject’s walking speed and preventing falls caused by incoordination between the subject’s walking speed and the robot’s designated speed during rehabilitation training.Simulation and experimental results show that the prediction accuracy of the falling prediction model can reach 95.2%,and the lead time for falling prediction can reach 1.82 s.The human-robot speed coordination anti-falling method can effectively prevent falls caused by incoordination between the subject’s walking speed and the robot’s designated speed,enabling the subject to complete walking rehabilitation training safely.
作者
常洪彬
谷影冬
孙平
张迪
Chang Hongbin;Gu Yingdong;Sun Ping;Zhang Di(School of Artificial Intelligence,Shenyang University of Technology,Shenyang 110870,China)
出处
《电子测量与仪器学报》
CSCD
北大核心
2024年第12期218-227,共10页
Journal of Electronic Measurement and Instrumentation
基金
辽宁省自然科学基金项目(2024-MS-102)
辽宁省高等学校基本科研项目(JYTZD2023110,JYTMS20231223)资助。
关键词
步行康复训练机器人
人机速度协调
防跌倒控制
跌倒预测
速度预测
walking rehabilitation training robot
human-robot speed incoordination
anti-fall control
fall prediction
speed prediction
作者简介
通信作者:常洪彬,2011年于沈阳师范大学获得学士学位,2016年于沈阳工业大学获得硕士学位,2019年于日本高知工科大学获得博士学位,现为沈阳工业大学副教授,主要研究方向为康复机器人、智能控制等。E-mail:Chang.hongbin@sut.edu.cn。
