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Publication

A Pilot Study on Using Wearables to Identify Difficulties for Ensemble Musicians

Christian Brinkhaus; Tenka Naka; Andrew Vargo; Ko Watanabe; Koichi Kise (Hrsg.)
International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp-2026), October 11-15, Shanghai, China, ISBN 979-8-4007-2533-3/2026/10, Association for Computing Machinery, 2026.

Abstract

Through a self-observation approach, this 24-day study investigates whether physiological signals from wearable sensors differ by session context and repertoire in orchestral settings, and whether self-rated piece difficulty can be predicted from these signals. The participant wore an EmbracePlus during the study period, collecting physiological data during home practice, group rehearsals, and two concerts. An analysis with generalized linear models found that the session type and the piece played could be used to explain the physiological changes captured by the EmbracePlus wristband. These findings inform a research arc that can enable us to identify demanding repertoire that needs more practice and could help with the identification and prevention of performance anxiety