GEGLU-Transformer reconstructs EMG signals from IMU data with r=0.706 cross-subject and improves to r=0.761 after minimal adaptation under leave-one-subject-out testing.
A novel dual-model adaptive con- tinuous learning strategy for wrist-semg real-time gesture recognition
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GEGLU-Transformer for IMU-to-EMG Estimation with Few-Shot Adaptation
GEGLU-Transformer reconstructs EMG signals from IMU data with r=0.706 cross-subject and improves to r=0.761 after minimal adaptation under leave-one-subject-out testing.