On using wearable tri-axial accelerometers to examine the striking phase kinematics of expert specialist drag flickers on-field |
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| Authors: | Simon M Rosalie Weng I Tang Andrew S McIntyre Stacey Stockman Craig King Cameron Watkins |
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| Institution: | 1. School of Physiotherapy and Exercise Science, Curtin University, Perth, Australia;2. Dipartimento di Ingegneria Industriale, Università degli Studi di Firenze, Firenze, Italysimon.rosalie@curtin.edu.au;4. Medicina Física e Reabilita??o, Centro Hospitalar Conde de S?o Januário, Macau, China;5. Applecross Physiotherapy, Applecross, Australia;6. Ascend Physiotherapy, Mt Claremont, Australia;7. Darch Physio, Darch, Australia;8. Bayswater Physiotherapy, Bayswater, Australia |
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| Abstract: | Analysing player kinematics during a match using “gold-standard” 3D video-based motion analysis techniques is a difficult prospect indeed. The development of small, wireless, wearable sensors offers the potential to reduce the challenges of measuring kinematics during match-play without hindering performance. The present study examined the viability of using wireless tri-axial accelerometers to examine whether key performance measures of drag flicks executed by expert specialist drag-flickers are predicted by the kinematics of the striking phase. Linear mixed models were used to examine whether the speed and accuracy of players’ drag flicks were predicted by the duration of stick-ball contact, and the kinematics of the lead lower limb at stick-ball contact and ball release. Results revealed that stick and lead lower limb kinematics significantly predicted shot accuracy but not shot speed. Shorter drag-time predicted more accurate flicks (p = 0.03) as did a more vertical leg at stick-ball contact (p = 0.016) and a more horizontal thigh at ball release (p = 0.001). This may indicate that there are more ways to produce fast drag flicks than accurate ones. This study illustrates that wireless tri-axial accelerometers can be used on-field to measure the effects of kinematics on key performance measures. |
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| Keywords: | Wearable sensors Expert performance Motor skill Striking sports Field data |
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