HD sEMG

High-density surface electromyography (HD-sEMG) uses numerous electrodes to record muscle activity, aiming for more accurate and robust gesture recognition compared to traditional sEMG. Current research focuses on improving the robustness of HD-sEMG systems to noise, electrode shift, and individual variations, employing deep learning architectures like transformers, U-Nets, and Vision Transformers to process the high-dimensional data. These advancements hold significant promise for improving the control of prosthetic limbs, human-computer interfaces, and neurorobotics by enabling more reliable and responsive systems.