Feasibility Study of using MyoBand for Learning Electronic Keyboard

Abstract

Learning musical instruments like piano or electronic keyboard on average takes a decade. Currently, learning an instrument requires continuous supervision from a tutor, and it often becomes unrealistic to stay connected with the music tutor for a long time. Online music learning platforms remain unscalable as there is no way for these platforms to verify whether user pressed a key note with the intended finger, which is significant for learning finger based musical instruments. To overcome this, an autonomous system to evaluate and guide in the learning process by continuously tracking finger movements via a non-camera based solution is proposed. Finger press triggers the muscle movements which are detected at the surface of the forearm in the form of surface Electromyography (sEMG) signals. The paper proposes tracking of finger press for 10 seconds on an electronic keyboard using MyoBand [1] wearable device that provided 8 channels of sEMG signals. Eleven time and frequency domain features of sEMG signals were extracted from sEMG signals to classify musical note played by the instrument on corresponding finger press. The feature set was standardized using standard scaler approach, and vector dimensions were reduced by Linear Discriminant Analysis (LDA) method. The resulting reduced dimension data was applied on Random Forest (RF) classifier to report best classification accuracy for our application. Experiments involved single finger press to render a note in the musical instrument, and multiple finger press to define chord sequence on an electronic musical keyboard. Further analysis was performed to maximize the classification accuracy over the number of trials and optimize the position of electrodes for successful identification of musical note played. The proposed method achieves a classification accuracy of 74.25% for 5 musical note played on an electronic keyboard instrument with 4 MyoBand electrodes, and an accuracy of 95.83% with one electrode for identifying between four musical events including two major chords sequence and two musical notes.