Segmentation of exercise repetitions enabling real-time patient analysis and feedback using a single exemplar
- Submitting institution
-
Nottingham Trent University
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 29 - 913719
- Type
- D - Journal article
- DOI
-
10.1109/TNSRE.2019.2907483
- Title of journal
- IEEE Transactions on Neural Systems and Rehabilitation Engineering
- Article number
- -
- First page
- 1004
- Volume
- 27
- Issue
- 5
- ISSN
- 1558-0210
- Open access status
- Compliant
- Month of publication
- April
- Year of publication
- 2019
- URL
-
https://ieeexplore.ieee.org/document/8688440
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
8
- Research group(s)
-
A - Computing and Informatics Research Centre
- Citation count
- 0
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- Using Dynamic Time Warping, we were able to identify movements in realtime with a single reference segment. Allowing single reference segments, means the segmentation of various data is more practical in a single package (10.21105/joss.02404). This research has led to enhanced partnerships between NTU, UoN Medical School (Prof Penny Standen - Division of Rehabilitation and Ageing: P.Standen@nottingham.ac.uk) and Nottingham CityCare (Louise Selwood - Clinical Specialist Physiotherapist: louise.selwood@nottinghamcitycare.nhs.uk)."
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
