Visualization of Multichannel Surface Electromyography as a Map of Muscle Component Activation

The study of muscle activation patterns using surface electromyography (sEMG) provides critical insights into muscle coordination, enabling advancements in prosthetics, robotics, and rehabilitation by improving intuitive control, replicating human movements, and developing targeted therapeutic strategies. The study involved 15 healthy participants aged 20–27, using Trigno Avanti sensors to record sEMG signals from forearm muscles during specific gestures, with data processed into activation maps to analyze muscle activity and coordination for applications in rehabilitation and prosthetics. The results revealed distinct muscle activation patterns for each gesture, highlighting precise muscle coordination, with specific muscles like m. flexor carpi ulnaris and m. extensor digitorum showing varying levels of involvement depending on the movement, while m. brachioradialis remained inactive across all gestures. The study’s findings enhance our understanding of motor control by revealing specific muscle activation patterns for different hand gestures, highlighting the selectivity of muscle coordination, and suggesting avenues for future research to improve prosthetic design and rehabilitation strategies.