Improved High-density Myoelectric Pattern Recognition Control Against Electrode Shift Using Data Augmentation and Dilated Convolutional Neural Network
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society, 2020.
This work demonstrated feasibility and usability of combining data augmentation and DCNN in predict-ing myoelectric patterns in the context of electrode shifts. Signifi-cance: The proposed method is a practical solution for robust my-oelectric control against electrode array shifts.
Full Text (Upload PDF)
PPT (Upload PPT)