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Sport training using body sensor networks: a statistical approach to measure wrist rotation for golf swing

Authors:

Hassan Ghasemzadeh,

Eric Guenterberg,

Roozbeh JafariAuthors Info & Claims

BodyNets '09: Proceedings of the Fourth International Conference on Body Area Networks

Article No.: 2, Pages 1 - 8

https://doi.org/10.4108/ICST.BODYNETS2009.6035

Published: 01 April 2009 Publication History

Abstract

Athletes in any sports can greatly benefit from feedback systems for improving the quality of their training. In this paper, we present a golf swing training system which incorporates wearable motion sensors to obtain inertial information and provide feedback on the quality of movements. The sensors are placed on a golf club and athlete's body at positions which capture the unique movements of a golf swing. We introduce a quantitative model which takes into consideration signal processing techniques on the collected data and quantifies the correctness of the performed actions. We evaluate the effectiveness of our framework on data obtained from four subjects and discuss ongoing research.

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Sport training using body sensor networks: a statistical approach to measure wrist rotation for golf swing

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Published In

cover image Guide Proceedings

BodyNets '09: Proceedings of the Fourth International Conference on Body Area Networks

April 2009

161 pages

ISBN:9789639799417

General Chair:
William Kaiser
UCLA

Publisher

ICST (Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering)

Brussels, Belgium

Publication History

Published: 01 April 2009

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Iwamoto MOhnishi ATerada TTsukamoto M(2021)Design and Implementation of Push Pass Practice Support System for Field Hockey with Auditory FeedbackProceedings of the 20th International Conference on Mobile and Ubiquitous Multimedia10.1145/3490632.3490648(56-61)Online publication date: 5-Dec-2021
https://dl.acm.org/doi/10.1145/3490632.3490648
Turakhia DWong AQi YBlumberg LKim YMueller S(2021)Adapt2Learn: A Toolkit for Configuring the Learning Algorithm for Adaptive Physical Tools for Motor-Skill LearningProceedings of the 2021 ACM Designing Interactive Systems Conference10.1145/3461778.3462128(1301-1312)Online publication date: 28-Jun-2021
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