Study on Automatic Identification and Quantification of Rehabilitation Exercises
| Autor: | Jia-Shiun Wu, 吳佳薰 |
|---|---|
| Rok vydání: | 2013 |
| Druh dokumentu: | 學位論文 ; thesis |
| Popis: | 101 According to the data announced by Executive Yuan Department of Health at 2011, Stroke is the third leading cause of death in Taiwan. The rehabilitation costs a lot of resources as conduct half of the physically disabled or hemiplegic side of the body may occur and a long-term follow-up and evaluation need to be conducted. Recent improvements in image processing and data analysis enable us for the automatic identification and quantification of rehabilitation exercises. In this study, an image sensing environment was setup for capturing the actions based on the integration of conventional assessment scale for stroke rehabilitation. The image data was tagged and transformed into kinematic parameters according to the frame-based averages of the locations of 6 major joints. Stepwise regression and linear discriminant analysis was applied for feature selection and action classification; the judgment of action completeness was determined by using dynamic time warping algorithm. The experimental results for intra-group of data showed that the accuracy of training and testing movement matching achieved an average of 98.86%; the inter-group results was about 89.00%. The experimental results encouraged us that the proposed approach is capable for the quantification and identification for rehabilitation movements. |
| Databáze: | Networked Digital Library of Theses & Dissertations |
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