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Authors: P. Tsinganos 1 ; B. Cornelis 2 ; J. Cornelis 2 ; B. Jansen 2 and A. Skodras 1

Affiliations: 1 University of Patras, Department of Electrical and Computer Engineering, 26504 Patras and Greece ; 2 Vrije Universiteit Brussel, Department of Electronics and Informatics, 1050 Brussels and Belgium

Keyword(s): sEMG, Gesture Recognition, Deep Learning, CNN.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Biomedical Engineering ; Biomedical Signal Processing ; Biosignal Acquisition, Analysis and Processing ; Computational Intelligence ; Data Manipulation ; Health Engineering and Technology Applications ; Human-Computer Interaction ; Methodologies and Methods ; Neural Networks ; Neurocomputing ; Neurotechnology, Electronics and Informatics ; Pattern Recognition ; Physiological Computing Systems ; Sensor Networks ; Signal Processing ; Soft Computing ; Theory and Methods

Abstract: In recent years, Deep Learning methods have been successfully applied to a wide range of image and speech recognition problems highly impacting other research fields. As a result, new works in biomedical engineering are directed towards the application of these methods to electromyography-based gesture recognition. In this paper, we present a brief overview of Deep Learning methods for electromyography-based hand gesture recognition along with an analysis of a modified simple model based on Convolutional Neural Networks. The proposed network yields a 3% improvement on the classification accuracy of the basic model, whereas the analysis helps in understanding the limitations of the model and exploring new ways to improve the performance.

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Paper citation in several formats:
Tsinganos, P.; Cornelis, B.; Cornelis, J.; Jansen, B. and Skodras, A. (2018). Deep Learning in EMG-based Gesture Recognition. In Proceedings of the 5th International Conference on Physiological Computing Systems - PhyCS; ISBN 978-989-758-329-2; ISSN 2184-321X, SciTePress, pages 107-114. DOI: 10.5220/0006960201070114

@conference{phycs18,
author={P. Tsinganos. and B. Cornelis. and J. Cornelis. and B. Jansen. and A. Skodras.},
title={Deep Learning in EMG-based Gesture Recognition},
booktitle={Proceedings of the 5th International Conference on Physiological Computing Systems - PhyCS},
year={2018},
pages={107-114},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006960201070114},
isbn={978-989-758-329-2},
issn={2184-321X},
}

TY - CONF

JO - Proceedings of the 5th International Conference on Physiological Computing Systems - PhyCS
TI - Deep Learning in EMG-based Gesture Recognition
SN - 978-989-758-329-2
IS - 2184-321X
AU - Tsinganos, P.
AU - Cornelis, B.
AU - Cornelis, J.
AU - Jansen, B.
AU - Skodras, A.
PY - 2018
SP - 107
EP - 114
DO - 10.5220/0006960201070114
PB - SciTePress