Myoelectric Control

Myoelectric control uses electromyography (EMG) signals from muscles to control prosthetic limbs or other devices, aiming to restore lost function and improve human-computer interaction. Current research emphasizes improving the accuracy and robustness of these systems, focusing on advanced machine learning techniques like vision transformers and recurrent neural networks, as well as incorporating multimodal feedback (e.g., haptic and visual) to enhance control and user experience. These advancements are crucial for creating more intuitive and reliable prosthetic devices, expanding the capabilities of assistive technologies, and potentially revolutionizing human-machine interfaces beyond prosthetics.