EMG-based biofeedback tool for augmenting manual fabrication and improved exchange of empirical knowledge

Abstract

It can be time-consuming and frustrating to acquire any new skill, and for one that relies on muscle memory developed through observation and repetition it may require hours of supervised training to reach even minimal proficiency. This paper explores whether real-time feedback that compares data from bio-signals and physical movements of a novice learner and an expert can shorten the learning process via a wearable device. These signals include measurements of muscle activity using electromyography (EMG) and from sensors that include accelerometers, gyroscopes, and magnetometers. The signals are in the form of sets of illuminated RGB LEDs; the learner receives instantaneous performance evaluation that enables immediate realization of an error and allows for rapid and easy adjustment of movement. Preliminary tests using the wearable device in pottery making show effectiveness at aiding students to master movements more quickly than on average. Hence, the wearable device aids the user in acquiring muscle memory.