Facial Expression Recognition with sEMG Method

Facial expression recognition has broad application prospects in the fields of psychological study, nursing care, Human Computer Interaction as well as affective computing. The method with surface Electromyogram (sEMG), which is one of vital bio-signals, has its superiority in several aspects such as high temporal resolution and data processing efficiency over other methods. Researches regarding EMG signal to study emotional expression have started since the second half of last century. Meanwhile, studies on myoelectrical control systems focusing on the computation of bio-signal processing and data analysis have been blooming in the recent twenty years. To have a comprehensive view of utilizing facial sEMG method, a systematic review is presented in this paper for facial expression recognition from experiment design to measurement systems, and data analysis steps.