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: Learning a Hand Model from Dynamic Movements Using High-Density EMG and Convolutional Neural Networks

Learning a Hand Model from Dynamic Movements Using High-Density EMG and Convolutional Neural Networks
Learning a Hand Model from Dynamic Movements Using High-Density EMG and Convolutional Neural Networks 750 422 IEEE Transactions on Biomedical Engineering (TBME)
Deep learning model decodes surface electromyographic signals into proportional hand movements, accurately controlling both individual finger and compound movements, with potential to enhance intuitive interfaces for assistive hand devices. read more
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