Fundamental changes over time of surface EMG signal characteristics are a challenge for
myocontrol algorithms controlling prosthetic devices. These changes are generally caused …

Objective. Recent studies have reported that the classification performance of
electromyographic (EMG) signals degrades over time without proper classification …

Electromyography (EMG) is the process of measuring the electrical activity produced by
muscles throughout the body using electrodes on the surface of the skin or inserted in the …

Myoelectric control of a prosthetic hand with more than one degree of freedom (DoF) is
challenging, and clinically available techniques require a sequential actuation of the DoFs …

Wrist electromyography (EMG) signals have been explored for incorporation into subtle wrist-
worn wearable devices for decoding hand gestures. Previous studies have now shown that …

The time-varying character of myoelectric signal usually causes a low classification accuracy
in traditional supervised pattern recognition method. In this work, an unsupervised …

Intent inferral on a hand orthosis for stroke patients is challenging due to the difficulty of data
collection. Additionally, EMG signals exhibit significant variations across different conditions …

With the availability of high-density (HD) electrodes technology, the electrodes used in
myoelectric control can have much higher density than the current practice. In this study, we …

We propose MetaEMG, a meta-learning approach for fast adaptation in intent inferral on a
robotic hand orthosis for stroke. One key challenge in machine learning for assistive and …

Surface electromyogram pattern recognition (EMG-PR) requires time-consuming training
and retraining procedures for long-term use, hindering the usability of myoelectric control. In …