Shaw, Joseph W; Maloney, Brian; Mattiussi, Adam M; Brown, Derrick D; Springham, Matthew; Pedlar, Charles R; Tallent, Jamie (2023). The development and validation of an open-source accelerometery algorithm for measuring jump height and frequency in ballet. Journal of sports sciences, 41(5), pp. 463-469. Taylor & Francis 10.1080/02640414.2023.2223048
Full text not available from this repository. (Request a copy)The aim was to determine the validity of an open-source algorithm for measuring jump height and frequency in ballet using a wearable accelerometer. Nine professional ballet dancers completed a routine ballet class whilst wearing an accelerometer positioned at the waist. Two investigators independently conducted time-motion analysis to identify time-points at which jumps occurred. Accelerometer data were cross-referenced with time-motion data to determine classification accuracy. To determine the validity of the measurement of jump height, five participants completed nine jetés, nine sautés and three double tour en l'air from a force plate. The jump height predicted by the accelerometer algorithm was compared to the force plate jump height to determine agreement. Across 1440 jumps observed in time-motion analysis, 1371 true positives, 34 false positives and 69 false negatives were identified by the algorithm, resulting in a sensitivity of 0.98, a precision of 0.95 and a miss rate of 0.05. For all jump types, mean absolute error was 2.6 cm and the repeated measures correlation coefficient was 0.97. Bias was 1.2 cm and 95% limits of agreement were -4.9 to 7.2 cm. The algorithm may be used to manage jump load, implement periodization strategies, or plan return-to-jump pathways for rehabilitating athletes.
Item Type: |
Journal Article (Original Article) |
|---|---|
Division/Institute: |
07 Faculty of Human Sciences > Institute of Sport Science (ISPW) |
UniBE Contributor: |
Brown, Derrick Dewayne |
Subjects: |
700 Arts > 790 Sports, games & entertainment |
ISSN: |
1466-447X |
Publisher: |
Taylor & Francis |
Language: |
English |
Submitter: |
Pubmed Import |
Date Deposited: |
29 Jun 2023 09:33 |
Last Modified: |
12 Jul 2023 00:16 |
Publisher DOI: |
10.1080/02640414.2023.2223048 |
PubMed ID: |
37377013 |
Uncontrolled Keywords: |
athlete monitoring dance inertial measurement unit rehabilitation sensor training load |
URI: |
https://boris.unibe.ch/id/eprint/184200 |
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