In the biomedical field, the design of human-machine interfaces is oriented towards wearable solutions, to restore daily life activities in injured people. One of the most employed sensing techniques is surface ElectroMyoGraphy (sEMG), which allows technicians to easily apply electrodes on the skin.

Leveraging our knowledge of low-power embedded systems for real-time bio-inspired sEMG acquisition, we focus on the design of wearable systems for hand gestures and facial expressions recognition.