Bidirectional Real-time Control of An Upper-limb Prosthetic Hand

The human hand is a sensation-rich body part, and the loss of hand significantly influences the quality of life. Prosthetics are designed as artificial limbs to replace or substitute the missing part. For providing a natural and intuitive perception of grasp or pressure, a bidirectional prosthetic hand should be able to detect action intentions and sending feedback to the central nervous system at the same time.

To achieve this real-time control, our project will investigate in decoding the movement of fingers from Electromyograph (EMG) signals. By tracking the neuromuscular signals corresponding to various hand movements, a generic muscular-skeletal model could be developed by analyzing, visualizing and decoding from EEG and EMG. Also, different sensory feedback experiments of hand encoding will be conducted.

This project aims to analyze the biological signals of hand movements, and generate a neural interface for prosthetic hands. The main outcomes of this project will be to improve the efficiency and quality of hand prosthetics and support future near-natural hand replacement.

Faculty Supervisor:

Purang Abolmaesumi

Student:

Partner:

Technical University of Munich

Discipline:

Engineering

Sector:

Technology; Biotechnology; Health and Related Sciences & Technology

University:

The University of British Columbia

Program: