摘要
为准确识别人体下肢步态运动,设计一种识别下肢步态摆动相和支撑相的方法。通过4个姿态传感器和足底压力鞋垫采集人体下肢角度信息和足底压力信息,将数据信息进行归一化、比例化处理后提取特征;利用模糊原理将传感器信息进行模糊化,将双腿步态划分为4种情况;利用MATLAB对下肢角度信息和足底压力信息采用不同核函数的支持向量机(support vector machine,SVM)进行识别;以同一人在不同步态速率下直线行走的步态和不同身高腿长的人在速率为0.6 m/s下的直线行走的步态进行实验。结果表明:该算法是有效、适用的,识别准确率均在90%以上。
To accurately identify human lower limb gait movements,a method to identify the swing phase and support phase of lower limb gait is designed.The human lower limb angle information and plantar pressure information are collected through four posture sensors and plantar pressure insoles,and the data information is normalized and scaled to extract features;the sensor information is fuzzified by using the fuzzy principle to classify the gait of both legs into four cases;the support vector machine(SVM)with different kernel functions is used to recognize the lower limb angle information and plantar pressure information using MATLAB;the same gait of a person walking in a straight line at different gait rates and the gait of a person of different height and leg length walking in a straight line at a rate of 0.6 m/s were experimented.The results show that the algorithm is effective and applicable,and the average recognition accuracy is above 90%in all cases.
作者
吕佳乐
高学山
石永杰
刘欢
吕鹏飞
赵鹏
车红娟
郝亮超
牛军道
LYU Jiale;Gao Xueshan;Shi Yongjie;Liu Huan;LYU Pengfei;Zhao Peng;Che Hongjuan;Hao Liangchao;Niu Jundao(School of Electrical&Information Engineering,Guangxi University of Science&Technology,Liuzhou 545000,China;School of Mechatronical Engineering,Beijing Institute of Technology,Beijing 100081,China;School of Mechanical&Transportation Engineering,Guangxi University of Science&Technology,Liuzhou 545000,China)
出处
《兵工自动化》
2021年第10期85-90,共6页
Ordnance Industry Automation
基金
中国老年失能预防与干预管理网络及技术研究(2020YFC2008503)。
