DocumentCode
128478
Title
Gait analysis of human locomotion based on motion capture system
Author
Jieyu Lei ; Qiuguo Zhu ; Jun Wu ; Rong Xiong
Author_Institution
State Key Lab. of Ind. Control Technol., Zhejiang Univ., Hangzhou, China
fYear
2014
fDate
9-11 June 2014
Firstpage
765
Lastpage
769
Abstract
This paper presents a segmentation method for human locomotion. The research on the rules of human locomotion plays an important role for the analysis of human movement strategy. We collected locomotion data from eighteen volunteers by motion capture system(MCS), and found that the measured stride length and frequency with speed had a mutation in the critical point between walking and running. To solve this problem, a segmentation method is proposed to describe the two gaits motion while the continuous formula is not suitable for using again. Especially, a running formula is proposed by introducing a compression of virtual leg based on the elastic linear inverted pendulum model(ELIPM), which can accurately describe the relationship between stride length, frequency and speed. By experimental comparisons, the proposed method can reduce 77% of the statistical error than Alexander´s one, which indicates this method is an effective approach and can uniform the motion rules for human walking and running.
Keywords
gait analysis; image motion analysis; image segmentation; pendulums; statistical analysis; ELIPM; MCS; critical point; elastic linear inverted pendulum model; gait analysis; human locomotion; human movement strategy; human running; human walking; measured stride length; motion capture system; segmentation method; statistical error; virtual leg; Cameras; Conferences; Fitting; Frequency measurement; Legged locomotion; Motion segmentation; Vectors; ELIPM; MCS; a segmentation method; human locomotion; virtual leg;
fLanguage
English
Publisher
ieee
Conference_Titel
Industrial Electronics and Applications (ICIEA), 2014 IEEE 9th Conference on
Conference_Location
Hangzhou
Print_ISBN
978-1-4799-4316-6
Type
conf
DOI
10.1109/ICIEA.2014.6931265
Filename
6931265
Link To Document