New gesture recognition strategy advances prosthetic hand technology

The novel method can recognise hand gestures in prosthetic devices using electromyography (EMG) signals, a technique that captures the electrical activity produced by skeletal muscles.

Specifically, the researchers used a new strategy called ‘Virtual-Dimension Increase of EMG,’ which allows the EMG system to interpret the user's intent more accurately without the need for additional physical sensors.

Their approach increased the number of virtual EMG signal channels, enhancing the system's ability to discern subtle differences in muscle activity and thus predict a wider range of hand gestures.

The researchers said that while electromyography has long been a cornerstone in the development of intelligent bionic prostheses, by translating muscle activity into data that can drive the movements of a prosthetic hand, traditional systems require increasing the number of sensors to capture more data which can complicate the device without necessarily improving performance.

“By virtually increasing the number of EMG channels, we can enrich the motion intention information extracted, avoiding the pitfalls of system overcomplexity and maintaining user comfort," lead researcher Yuxuan Wang, from the School of Mechatronical Engineering, Beijing Institute of Technology, said in a statement.