Deep Learning in EMG-based Gesture Recognition
Host Publication: Proceedings of the fifth international conference on physiological computing systems
Authors: P. Tsinganos, B. Cornelis, J. Cornelis, B. Jansen and A. Skodras
Publication Date: Sep. 2018
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 engineer- ing 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 perfor- mance.