Adaptive Interface for sEMG Control of Vocal Expression

This project examines how individuals learn to control a surface electromyography (sEMG)-driven interface during early-stage motor training. By studying how users progressively stabilize and refine control strategies within a high-dimensional system, the research aims to improve the design of adaptive neurotechnology and human–machine interfaces. Findings may contribute to advancements in motor learning research and inform future applications in neurological rehabilitation and assistive technologies.

Faculty Supervisor:

Lara Boyd

Student:

Partner:

Polytechnic of Porto

Discipline:

Life Sciences

Sector:

Health and Related Sciences & Technology

University:

The University of British Columbia

Program:

Globalink Research Award

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