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The Scientific World Journal
Volume 2014, Article ID 136018, 8 pages
http://dx.doi.org/10.1155/2014/136018
Research Article

Gait Signal Analysis with Similarity Measure

1Department of Electrical and Electronic Engineering, Xi’an Jiaotong-Liverpool University, Suzhou 215123, China
2Department of Information Security, Tongmyong University, Sinseonno, Nam-gu, Busan 608-711, Republic of Korea

Received 25 April 2014; Accepted 10 June 2014; Published 7 July 2014

Academic Editor: T. O. Ting

Copyright © 2014 Sanghyuk Lee and Seungsoo Shin. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Human gait decision was carried out with the help of similarity measure design. Gait signal was selected through hardware implementation including all in one sensor, control unit, and notebook with connector. Each gait signal was considered as high dimensional data. Therefore, high dimensional data analysis was considered via heuristic technique such as the similarity measure. Each human pattern such as walking, sitting, standing, and stepping up was obtained through experiment. By the results of the analysis, we also identified the overlapped and nonoverlapped data relation, and similarity measure analysis was also illustrated, and comparison with conventional similarity measure was also carried out. Hence, nonoverlapped data similarity analysis provided the clue to solve the similarity of high dimensional data. Considered high dimensional data analysis was designed with consideration of neighborhood information. Proposed similarity measure was applied to identify the behavior patterns of different persons, and different behaviours of the same person. Obtained analysis can be extended to organize health monitoring system for specially elderly persons.