[1]陈天麟,戴佺民,程光,等.基于肌电信号的膝关节跨越障碍角度预测方法[J].中国医学物理学杂志,2020,37(10):1293-1301.[doi:DOI:10.3969/j.issn.1005-202X.2020.10.014]
　CHEN Tianlin,DAI Quanmin,CHENG Guang,et al.Prediction of knee joint angle when crossing obstacles based on myoelectric signals[J].Chinese Journal of Medical Physics,2020,37(10):1293-1301.[doi:DOI:10.3969/j.issn.1005-202X.2020.10.014]
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基于肌电信号的膝关节跨越障碍角度预测方法()
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《中国医学物理学杂志》[ISSN:1005-202X/CN:44-1351/R]

卷:
37
期数:
2020年第10期
页码:
1293-1301
栏目:
医学信号处理与医学仪器
出版日期:
2020-10-29

文章信息/Info

Title:
Prediction of knee joint angle when crossing obstacles based on myoelectric signals
文章编号:
1005-202X（2020）10-1293-09
作者:
陈天麟1; 戴佺民1; 2; 程光1; 2; 马勇杰1; 孙佰鑫1; 刘伟锋1; 许晓容2
1.北京联合大学机器人学院， 北京 100101； 2.北京联合大学城市轨道交通与物流学院， 北京 100101
Author(s):
CHEN Tianlin1;  DAI Quanmin1;  2;  CHENG Guang1;  2;  MA Yongjie1;  SUN Baixin1;  LIU Weifeng1;  XU Xiaorong2
1. College of Robotics, Beijing Union University, Beijing 100101, China 2. College of Urban Rail Transit and Logistics, Beijing Union University, Beijing 100101, China
关键词:
膝关节; 跨越障碍; 肌肉电信号; BP神经网络; 角度预测
Keywords:
Keywords: knee joint obstacle crossing myoelectrical signal BP neural network angle prediction
分类号:
R318；TN911.7
DOI:
DOI:10.3969/j.issn.1005-202X.2020.10.014
文献标志码:
A
摘要:
为解决人体跨越障碍物时膝关节角度输出的问题，针对性设计一种穿戴式信号获取实验台，对下肢运动姿态进行运动分析，将肌肉电信号及关节角度信号作为运动数据，对信号进行处理后利用BP神经网络预测跨越障碍时输出角度，提出一种利用BP神经网络算法，根据不同大腿抬起高度，分析膝关节运动主动肌与被动肌发力程度，预测输出人体跨越障碍时膝关节角度的方法，能够有效帮助假肢膝关节或康复机器人实现跨越障碍的复杂动作。
Abstract:
Abstract: In order to solve the problem of knee joint angle output when the human body crosses obstacles, a wearable signal acquisition test bench is designed. The motion analysis of the lower limb is carried out, and the myoelectrical signals and joint angle signals are used as motion data. After signal processing, BP neural network is used to predict the output angle when crossing obstacles. Herein a novel method based on BP neural network algorithm is proposed to analyze the forces of knee joint motion active muscle and passive muscle according to different thigh lift heights, and to predict the knee joint angle when the human body crosses obstacles. The proposed method can effectively help the prosthetic knee joint or rehabilitation robots implement the complex movement of obstacle crossing.

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备注/Memo

备注/Memo:
【收稿日期】2020-04-11 【基金项目】北京市自然科学基金-市教委重点基金（KZ201811417048）；北京市自然科学基金-轨道交通联合基金（L191006）；北京联合大学人才强校优选计划（BPHR2020DZ03） 【作者简介】陈天麟，硕士研究生，研究领域为智能假肢膝关节、人体行走步态分析，E-mail: ctl2552@163.com 【通信作者】戴佺民，博士，讲师，主要研究方为向电力设备在线监测与故障诊断、先进传感技术、智能机械装备等，E-mail:zdhtquanmin@buu.edu.cn；程光，博士，教授，博导，主要研究领域为机械设计与理论，E-mail: chengguang@buu.edu.cn
更新日期/Last Update: 2020-10-29