Sarsfield, J ORCID: https://orcid.org/0000-0003-0146-9102, Brown, D ORCID: https://orcid.org/0000-0002-1677-7485, Sherkat, N ORCID: https://orcid.org/0000-0003-1488-5682, Langensiepen, C ORCID: https://orcid.org/0000-0002-0165-9048, Lewis, J ORCID: https://orcid.org/0000-0002-2788-5043, Taheri, M ORCID: https://orcid.org/0000-0001-7594-4530, Selwood, L, Standen, P and Logan, P, 2019. Segmentation of exercise repetitions enabling real-time patient analysis and feedback using a single exemplar. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 27 (5), pp. 1004-1019. ISSN 1558-0210
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Abstract
We present a segmentation algorithm capable of segmenting exercise repetitions in real-time. This approach uses subsequence dynamic time warping and requires only a single exemplar repetition of an exercise to correctly segment repetitions from other subjects, including those with limited mobility. This approach is invariant to low range of motion, instability in movements and sensor noise while remaining selective to different exercises. This algorithm enables responsive feedback for technology-assisted physical rehabilitation systems. We evaluated the algorithm against a publicly available dataset (CMU) and against a healthy population and stroke patient population performing rehabilitation exercises captured on a consumer-level depth sensor. We show the algorithm can consistently achieve correct segmentation in real-time.
Item Type: | Journal article |
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Publication Title: | IEEE Transactions on Neural Systems and Rehabilitation Engineering |
Creators: | Sarsfield, J., Brown, D., Sherkat, N., Langensiepen, C., Lewis, J., Taheri, M., Selwood, L., Standen, P. and Logan, P. |
Publisher: | Institute of Electrical and Electronics Engineers |
Date: | May 2019 |
Volume: | 27 |
Number: | 5 |
ISSN: | 1558-0210 |
Identifiers: | Number Type 10.1109/TNSRE.2019.2907483 DOI 913704 Other |
Divisions: | Schools > School of Science and Technology |
Record created by: | Jonathan Gallacher |
Date Added: | 12 Apr 2019 12:30 |
Last Modified: | 28 Sep 2021 10:55 |
URI: | https://irep.ntu.ac.uk/id/eprint/36241 |
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