The study of music Skill Acquisition through a Multi-Sensing Approach (SAMuSe)
SAMuSe pioneers an integrative framework combining motion, muscle, brain, physiological, and experiential data to model how musical performance skills develop across five expertise levels.
By identifying psychophysiological embodiment indicators linked to skill levels, the project aims to develop data-informed teaching strategies that support both performance quality and musician well-being.
​Uniting music education, engineering, and computer science, SAMUSE advances embodied music cognition, wearable sensor technology, and multimodal AI, with outcomes relevant beyond music to sports, health, and human–computer interaction
