Improved High-density Myoelectric Pattern Recognition Control Against Electrode Shift Using Data Augmentation and Dilated Convolutional Neural NetworkT
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Transactions on Neural Systems and Rehabilitation Engineering (TNSRE)
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The objective of this work is to develop a robust method for myoelectric control towards alleviating the in-terference of electrode shift. Methods: In the proposed method, a preprocessing approach was first performed to convert high-den-sity surface electromyogram (HD-sEMG) signals into a series of images, and the electrode shift appeared as pixel shift in these im-ages.
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