DocumentCode :
3598586
Title :
Gait symmetry based on principal component analysis method
Author :
Fei Wang ; Lei Zhou ; Yifan Wang ; Jian Liu
Author_Institution :
Coll. of Inf. Sci. & Eng., Northeastern Univ., Shenyang, China
fYear :
2015
Firstpage :
6366
Lastpage :
6371
Abstract :
Taking advantage of PCA reconstruction algorithm, this thesis uses motion data of the left lower limb to reconstruct the motion data of right lower limb. Comparing to the original information of the right lower limb, a conclusion is drawn that the lower limb gait of healthy human is symmetrical. On this basis, for patients with hemiplegia or amputation of lower limb gait information in health has most probably not been recorded, this thesis proposes a average model using healthy people´s average gait information to construct the patient´s and demonstrates the rationality of the model.
Keywords :
gait analysis; health care; principal component analysis; PCA reconstruction algorithm; gait symmetry; healthy human; principal component analysis method; right lower limb; Angular velocity; Covariance matrices; Hip; Joints; Knee; Legged locomotion; Principal component analysis; Principal component analysis reconstruction symmetry; The average gait;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control and Decision Conference (CCDC), 2015 27th Chinese
Print_ISBN :
978-1-4799-7016-2
Type :
conf
DOI :
10.1109/CCDC.2015.7161963
Filename :
7161963
Link To Document :
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