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Deep Learning in EMG-based Gesture Recognition Host Publication: Proceedings of the 5th International Conference on Physiological Computing Systems - Volume 1: PhyCS Authors: P. Tsinganos, B. Cornelis, J. Cornelis, B. Jansen and A. Skodras Publisher: Scitepress Publication Date: Sep. 2018 Number of Pages: 8 ISBN: 978-989-758-329-2
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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