2020
DOI: 10.48550/arxiv.2007.10879
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A temporal-to-spatial deep convolutional neural network for classification of hand movements from multichannel electromyography data

Abstract: Deep convolutional neural networks (CNNs) are appealing for the purpose of classification of hand movements from surface electromyography (sEMG) data because they have the ability to perform automated person-specific feature extraction from raw data. In this paper, we make the novel contribution of proposing and evaluating a design for the early processing layers in the deep CNN for multichannel sEMG. Specifically, we propose a novel temporal-to-spatial (TtS) CNN architecture, where the first layer performs co… Show more

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