Abstract
Contemporary physiotherapy and rehabilitation practice uses subjective measures for motion evaluation and requires time-consuming supervision. Algorithms that can accurately segment patient movement would provide valuable data for progress tracking and on-line patient feedback. In this paper, we propose a two-class classifier approach to label each data point in the patient movement data as either a segment point or a non-segment point. The proposed technique was applied to 20 healthy subjects performing lower body rehabilitation exercises, and achieves a segmentation accuracy of 82%.
Original language | English |
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Title of host publication | 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society |
Editors | Jeff Duerk, Jim Ji |
Place of Publication | Piscataway NJ USA |
Publisher | IEEE, Institute of Electrical and Electronics Engineers |
Pages | 9-13 |
Number of pages | 5 |
ISBN (Electronic) | 9781424479290 |
ISBN (Print) | 9781424479276 |
DOIs | |
Publication status | Published - 6 Nov 2014 |
Externally published | Yes |
Event | International Conference of the IEEE Engineering in Medicine and Biology Society 2014 - Sheraton Chicago Hotel and Towers, Chicago, United States of America Duration: 26 Aug 2014 → 30 Aug 2014 Conference number: 36th https://ieeexplore-ieee-org.ezproxy.lib.monash.edu.au/xpl/conhome/6923026/proceeding (Proceedings) https://web.archive.org/web/20140331105330/http://embc.embs.org/2014/?page_id=120 (Website) |
Conference
Conference | International Conference of the IEEE Engineering in Medicine and Biology Society 2014 |
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Abbreviated title | EMBC 2014 |
Country/Territory | United States of America |
City | Chicago |
Period | 26/08/14 → 30/08/14 |
Internet address |