# Deep Residual Shrinkage Networks for EMG-based Gesture Identification

arXiv: https://arxiv.org/abs/2202.02984 · HTML: https://mlsanity.com/paper/2202.02984/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
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- First posted on arXiv 7 Feb 2022.

## Abstract (arXiv)

This work introduces a method for high-accuracy EMG based gesture identification. A newly developed deep learning method, namely, deep residual shrinkage network is applied to perform gesture identification. Based on the feature of EMG signal resulting from gestures, optimizations are made to improve the identification accuracy. Finally, three different algorithms are applied to compare the accuracy of EMG signal recognition with that of DRSN. The result shows that DRSN excel traditional neural networks in terms of EMG recognition accuracy. This paper provides a reliable way to classify EMG signals, as well as exploring possible applications of DRSN.