Guo, Y, Sun, Y, Ren, Y et al. (3 more authors) (2019) Upper Limb Muscle Force Estimation During Table Tennis Strokes. In: 2019 IEEE 16th International Conference on Wearable and Implantable Body Sensor Networks (BSN). 2019 IEEE 16th International Conference on Wearable and Implantable Body Sensor Networks (BSN), 19-22 May 2019, Chicago USA. IEEE ISBN 978-1-5386-7477-2
Abstract
Based on an EMG-adjusted method in neuromusculoskeletal model, this study aims to predict the individual muscle force in shoulder and elbow during table tennis strokes. Muscle force estimation makes muscle activation analysis more physiological in sports. Twenty subjects, divided into professional group and amateur group, were adopted in this study. They were asked to do a basic stoke motion: backhand block. Surface electromyography (sEMG) of nine muscles was recorded, as well as the motion data collected by three inertial sensors. A Hill-type musculotendon model was then adopted to estimate individual muscle force by combining adjusted sEMG and motion data. The result shows that the method can estimate individual muscle force during table tennis strokes accurately, and the two groups show significant difference in muscle force of shoulders and elbows.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | Copyright © 2019, IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. |
Keywords: | table tennis, Hill-type musculotendon model, surface electromyography (sEMG), muscle force, upper limb |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Electronic & Electrical Engineering (Leeds) > Robotics, Autonomous Systems & Sensing (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 13 Feb 2020 15:28 |
Last Modified: | 13 Feb 2020 15:28 |
Status: | Published |
Publisher: | IEEE |
Identification Number: | 10.1109/BSN.2019.8771082 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:156487 |