Gait Signal Analysis with Similarity Measure
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...
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| Format: | Article |
| Language: | English |
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Wiley
2014-01-01
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| Series: | The Scientific World Journal |
| Online Access: | http://dx.doi.org/10.1155/2014/136018 |
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| _version_ | 1832558045639475200 |
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| author | Sanghyuk Lee Seungsoo Shin |
| author_facet | Sanghyuk Lee Seungsoo Shin |
| author_sort | Sanghyuk Lee |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-8172ec7a821b46caac057656d3789a01 |
| institution | Kabale University |
| issn | 2356-6140 1537-744X |
| language | English |
| publishDate | 2014-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | The Scientific World Journal |
| spelling | doaj-art-8172ec7a821b46caac057656d3789a012025-02-03T01:33:23ZengWileyThe Scientific World Journal2356-61401537-744X2014-01-01201410.1155/2014/136018136018Gait Signal Analysis with Similarity MeasureSanghyuk Lee0Seungsoo Shin1Department of Electrical and Electronic Engineering, Xi’an Jiaotong-Liverpool University, Suzhou 215123, ChinaDepartment of Information Security, Tongmyong University, Sinseonno, Nam-gu, Busan 608-711, Republic of KoreaHuman 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.http://dx.doi.org/10.1155/2014/136018 |
| spellingShingle | Sanghyuk Lee Seungsoo Shin Gait Signal Analysis with Similarity Measure The Scientific World Journal |
| title | Gait Signal Analysis with Similarity Measure |
| title_full | Gait Signal Analysis with Similarity Measure |
| title_fullStr | Gait Signal Analysis with Similarity Measure |
| title_full_unstemmed | Gait Signal Analysis with Similarity Measure |
| title_short | Gait Signal Analysis with Similarity Measure |
| title_sort | gait signal analysis with similarity measure |
| url | http://dx.doi.org/10.1155/2014/136018 |
| work_keys_str_mv | AT sanghyuklee gaitsignalanalysiswithsimilaritymeasure AT seungsooshin gaitsignalanalysiswithsimilaritymeasure |