Detection of motor changes in violin playing by EMG signals

Playing a music instrument relies on the harmonious body movements. Motor sequences are trained to achieve the perfect performances in musicians. Thus, the information from audio signal is not enough to understand the sensorimotor programming in players. Recently, the investigation of muscular activities of players during performance has attracted our interests. In this work, we propose a multi-channel system that records the audio sounds and electromyography (EMG) signal simultaneously and also develop algorithms to analyze the music performance and discover its relation to player’s motor sequences. The movement segment was first identified by the information of audio sounds, and the direction of violin bowing was detected by the EMG signal. Six features were introduced to reveal the variations of muscular activities during violin playing. With the additional information of the audio signal, the proposed work could efficiently extract the period and detect the direction of motor changes in violin bowing. Therefore, the proposed work could provide a better understanding of how players activate the muscles to organize the multi-joint movement during violin performance.