Maximizing the information transfer rate of a textile-based myoelectric interface

The electrical activity of muscles can be recorded from the skin and used to control external devices. Advances in this technology have the potential to allow a broad range of users with disabilities to control assistive technologies. This project will develop a system that uses sensors embedded in garments to measure muscle signals, and artificial intelligence to personalize how those signals can best be used to control assistive technologies for a given person’s pattern of muscle weakness after spinal cord injury. The intern will be responsible for developing and testing artificial intelligence algorithms, while the partner organization will develop the textile sensors. The activities undertaken in this project will result in sensors that can be used in a variety of applications and thus have broad benefits for the partner organization’s activities.

Faculty Supervisor:

Jose Zariffa

Student:

Partner:

Vee Canada Inc

Discipline:

Engineering

Sector:

Professional, scientific and technical services

University:

University of Toronto

Program: