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A framework for comprehensive analysis of a swing in sports using low-cost inertial sensors

Ahmadi, Amin, Destelle, Francois, Monaghan, David orcid logoORCID: 0000-0002-5169-9902, O'Connor, Noel E. orcid logoORCID: 0000-0002-4033-9135, Richter, Chris and Moran, Kieran orcid logoORCID: 0000-0003-2015-8967 (2014) A framework for comprehensive analysis of a swing in sports using low-cost inertial sensors. In: IEEE SENSORS 2014, 2-5 Nov 2014, Valencia, Spain.

Abstract
We present a novel framework to monitor the three- dimensional trajectory (orientation and position) of a golf swing using miniaturized inertial sensors. Firstly we employed a highly accurate and computationally efficient revised gradient descent algorithm to obtain the orientation of a golf club. Secondly, we designed a series of digital filters to determine the backward and forward segments of the swing, enabling us to calculate drift-free linear velocity along with the relative 3D position of the golf club during the entire swing. Finally, the calculated motion trajectory was verified against a ground truth VICON system using Iterative Closest Point (ICP) in conjunction with Principal Component Analysis (PCA). The computationally efficient framework present here achieves a high level of accuracy (r = 0.9885, p < 0.0001) for such a low-cost system. This framework can be utilized for reliable movement technique evaluation and can provide near real-time feedback for athletes in various unconstrained environments. It is envisaged that the proposed framework is applicable to other racket based sports (e.g. tennis, cricket and hurling).
Metadata
Item Type:Conference or Workshop Item (Paper)
Event Type:Conference
Refereed:Yes
Subjects:Engineering > Signal processing
Medical Sciences > Sports sciences
DCU Faculties and Centres:DCU Faculties and Schools > Faculty of Science and Health > School of Health and Human Performance
Research Initiatives and Centres > INSIGHT Centre for Data Analytics
Use License:This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License
Funders:SFI Grant Number 12/RC/2289
ID Code:20594
Deposited On:27 May 2015 12:56 by Kevin Fraser . Last Modified 19 Oct 2018 12:31
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