Shaw, Joseph W and Maloney, Brian and Mattiussi, Adam M and Brown, Derrick D and Springham, Matthew and Pedlar, Charles R and 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. DOI https://doi.org/10.1080/02640414.2023.2223048
Shaw, Joseph W and Maloney, Brian and Mattiussi, Adam M and Brown, Derrick D and Springham, Matthew and Pedlar, Charles R and 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. DOI https://doi.org/10.1080/02640414.2023.2223048
Shaw, Joseph W and Maloney, Brian and Mattiussi, Adam M and Brown, Derrick D and Springham, Matthew and Pedlar, Charles R and 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. DOI https://doi.org/10.1080/02640414.2023.2223048
Abstract
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 <i>jetés</i>, nine <i>sautés</i> and three double <i>tour en l'air</i> 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: | Article |
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Uncontrolled Keywords: | Algorithms; Athletes; Biomechanical Phenomena; Dancing; Humans; Motion |
Divisions: | Faculty of Science and Health Faculty of Science and Health > Sport, Rehabilitation and Exercise Sciences, School of |
SWORD Depositor: | Unnamed user with email elements@essex.ac.uk |
Depositing User: | Unnamed user with email elements@essex.ac.uk |
Date Deposited: | 17 Oct 2023 16:07 |
Last Modified: | 30 Oct 2024 21:10 |
URI: | http://repository.essex.ac.uk/id/eprint/35926 |
Available files
Filename: Shaw et al.pdf
Licence: Creative Commons: Attribution-Noncommercial 4.0