NDLI: A vision-based walking posture analysis system without markers

Content Provider	IEEE Xplore Digital Library
Author	Tsung-Yen Liao Shaou-Gang Miaou Yu-Ren Li
Copyright Year	2010
Description	Author affiliation: Department of Electronic Engineering Chung Yuan Christian University Chung-Li, Taiwan (Tsung-Yen Liao; Shaou-Gang Miaou; Yu-Ren Li)
Abstract	Using a simple method or instrument to realize our health condition not only reduces the cost of medical resources but also achieves the objective of self-health management. This study proposes a vision-based human walking posture analysis system without the need of markers. The system can be applied at home for self-health care or used in health-care institutions. This study analyzes the human walking posture based on side-view and front-view images of a subject. Four features are extracted from the images for walking posture evaluation, including body line, neck line, center of gravity (COG) and gait width. Tilting angles associated with body line and neck line and their periodic variation are adopted to evaluate upper body posture for any abnormality and its correction. The COG and gait width features are used to evaluate the posture condition of lower body parts. Since these two features show an inverse relationship for a normal posture, they can be used to evaluate the stability of a walking posture and see if any posture correction is needed. The experiment results show that this study successfully extracts all the four features mentioned above from the silhouette image of human body. In addition, the proposed system is compared to a traditional marker-based system by performing correlation analysis between their experimental results on the 8 standard decompositions of a full gait cycle, resulting in very high positive correlation. It shows that the proposed walking posture analyzer achieves the performance of a traditional marker-based system with lower cost and higher convenience.
File Size	549031
File Format	PDF
ISBN	9781424468928
e-ISBN	9781424468935
DOI	10.1109/ICSPS.2010.5555656
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-07-05
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Legged locomotion Correlation Humans walking posture and its characteristics Feature extraction Cameras Neck health management Foot silhouette image
Content Type	Text
Resource Type	Article

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