Can an Inertial Measurement Unit, Combined with Machine Learning, Accurately Measure Ground Reaction Forces in Cricket Fast Bowling?

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aut.relation.endpage13
aut.relation.issueahead-of-print
aut.relation.journalSport Biomechanics
aut.relation.startpage1
aut.relation.volumeahead-of-print
dc.contributor.authorMcGrath, Joseph W
dc.contributor.authorNeville, Jonathon
dc.contributor.authorStewart, Tom
dc.contributor.authorLamb, Matt
dc.contributor.authorAlway, Peter
dc.contributor.authorKing, Mark
dc.contributor.authorCronin, John
dc.date.accessioned2024-03-05T22:47:21Z
dc.date.available2024-03-05T22:47:21Z
dc.date.issued2023-11-09
dc.description.abstractThis study examined whether an inertial measurement unit (IMU) could measure ground reaction force (GRF) during a cricket fast bowling delivery. Eighteen male fast bowlers had IMUs attached to their upper back and bowling wrist. Each participant bowled 36 deliveries, split into three different intensity zones: low = 70% of maximum perceived bowling effort, medium = 85%, and high = 100%. A force plate was embedded into the bowling crease to measure the ground truth GRF. Three machine learning models were used to estimate GRF from the IMU data. The best results from all models showed a mean absolute percentage error of 22.1% body weights (BW) for vertical and horizontal peak force, 24.1% for vertical impulse, 32.6% and 33.6% for vertical and horizontal loading rates, respectively. The linear support vector machine model had the most consistent results. Although results were similar to other papers that have estimated GRF, the error would likely prevent its use in individual monitoring. However, due to the large differences in raw GRFs between participants, researchers may be able to help identify links among GRF, injury, and performance by categorising values into levels (i.e., low and high).
dc.identifier.citationSport Biomechanics, ISSN: 1476-3141 (Print); 1752-6116 (Online), Taylor and Francis Group, ahead-of-print(ahead-of-print), 1-13. doi: 10.1080/14763141.2023.2275251
dc.identifier.doi10.1080/14763141.2023.2275251
dc.identifier.issn1476-3141
dc.identifier.issn1752-6116
dc.identifier.urihttp://hdl.handle.net/10292/17292
dc.languageeng
dc.publisherTaylor and Francis Group
dc.relation.urihttps://www.tandfonline.com/doi/full/10.1080/14763141.2023.2275251
dc.rights© 2023 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited, and is not altered, transformed, or built upon in any way. The terms on which this article has been published allow the posting of the Accepted Manuscript in a repository by the author(s) or with their consent.
dc.rights.accessrightsOpenAccess
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectIMU
dc.subjectinjury prevention
dc.subjectperformance enhancement
dc.subjectsports technology
dc.subjectwearable sensors
dc.subjectIMU
dc.subjectinjury prevention
dc.subjectperformance enhancement
dc.subjectsports technology
dc.subjectwearable sensors
dc.subject42 Health Sciences
dc.subject4207 Sports Science and Exercise
dc.subject0913 Mechanical Engineering
dc.subject1106 Human Movement and Sports Sciences
dc.subject1303 Specialist Studies in Education
dc.subjectSport Sciences
dc.subject3202 Clinical sciences
dc.subject4207 Sports science and exercise
dc.titleCan an Inertial Measurement Unit, Combined with Machine Learning, Accurately Measure Ground Reaction Forces in Cricket Fast Bowling?
dc.typeJournal Article
pubs.elements-id529311
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