【摘 要】
：
In order to solve the problem that traditional eigenvalue analysis of time domain and frequency domain cant classify pedestrians motion state correctly in pedestrian navigation because of the changing
【机 构】
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Digital Navigation Center, Beihang University, Beijing, China
论文部分内容阅读
In order to solve the problem that traditional eigenvalue analysis of time domain and frequency domain cant classify pedestrians 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 pedestrians 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 get more reliable and stronger anti-interference capacity compared with the characteristics of time domain.
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