The Analysis of Pedestrian's Motion State Based on the Entropy of sEMG

被引：2

作者：

Li, Min ^{[1
]}

Zhao, Long ^{[2
]}

机构：

[1] Beihang Univ, Digital Nav Ctr, Beijing, Peoples R China

[2] Beihang Univ, Sci & Technol Aircraft Control Lab, Beijing, Peoples R China

来源：

CHINA SATELLITE NAVIGATION CONFERENCE (CSNC) 2016 PROCEEDINGS, VOL I | 2016年 / 388卷

关键词：

Entropy; sEMG; Feature extraction; Pedestrian's motion state;

D O I：

10.1007/978-981-10-0934-1_26

中图分类号：

V [航空、航天];

学科分类号：

08 ; 0825 ;

摘要：

In order to solve the problem that traditional eigenvalue analysis of time domain and frequency domain cannot classify pedestrian's motion state correctly in pedestrian navigation because of the changing of stride frequency and length, etc., a method for motion state analysis in combination with time domain characteristics and entropy of sEMG was presented. This method analyzed the complexity and amplitude of pedestrian's motion state, estimated the stride frequency, and classified four movement state include walking, running, upstairs, and downstairs according to variation feature of sEMG. The experimental results show that the average classification accuracy went up at least by 8.25 % with presented method, it gets more reliable and stronger anti-interference capacity compared with the characteristics of time domain.

引用

页码：287 / 297

页数：11

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