Real-time performance test evaluation system for lower limb motion intention recognition algorithm

被引：0
|
作者：
Li X. [1 ,2 ,3 ]
Tian L. [1 ,3 ]
Zheng Y. [1 ,2 ,3 ]
Li G. [1 ,2 ,3 ]
机构：
[1] Shenzhen Institutes of Advanced Technology (SIAT), Chinese Academy of Sciences (CAS), Shenzhen
[2] Guangdong-Hong Kong-Macao Joint Laboratory of Human-Machine Intelligence-Synergy Systems, Shenzhen
[3] Shenzhen Institutes of Advanced Technology, University of Chinese Academy of Sciences, Shenzhen
来源：
Yi Qi Yi Biao Xue Bao/Chinese Journal of Scientific Instrument | 2020年 / 41卷 / 05期
关键词：
Algorithm performance evaluation; Algorithm test evaluation system; Lower limb prosthesis; Motion intention recognition;
D O I：
10.19650/j.cnki.cjsi.J2006204
中图分类号：
学科分类号：
摘要：
Comprehensive and reliable evaluation of the real-time performance of leg motion intention recognition algorithms is the premise to realize flexible and stable control of lower limb prosthesis. In this paper, a multi-layer real time test evaluation method for lower limb motion intention recognition algorithms is proposed, which comprehensively evaluate the reliability, stability and motion intention recognition speed of the algorithms. Using the developed test evaluation system for lower limb motion intention recognition algorithms, two motion intention recognition algorithms based on myoelectric signal source and mechanical signal source were tested in real time, respectively. The results show that the motion recognition time of the myoelectric signal source based algorithm is longer than that of the mechanical signal source based algorithm; however, the stability of the myoelectric signal source based algorithm is better than that of the mechanical signal source based algorithm. Additionally, the performances of normal and abnormal recognition strategies can be effectively distinguished using the proposed test evaluation system, and it is found that the motion recognition stability index for normal strategy is 25% higher than that for the abnormal strategy. These results demonstrate that the proposed real time test evaluation method for lower limb motion intention recognition algorithms can effectively evaluate the real time performance of different signal source based algorithms and different recognition strategies, and can provide a testing platform for the development of intelligent lower limb prostheses control system. © 2020, Science Press. All right reserved.
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页码：99 / 107
页数：8
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