A synergy-driven approach to a myoelectric hand

Area of Science:

• Robotics
• Biomedical Engineering
• Neuroscience

Background:

• Commercially available myoelectric prosthetic hands are often expensive, heavy, and less robust than body-powered options.
• Synergy-driven control simplifies the complex motor patterns of the human hand into distinct, manageable patterns.
• The Pisa/IIT SoftHand utilizes this synergy principle for grasping, allowing adaptability with a single motor.

Purpose of the Study:

• To evaluate four different myoelectric control strategies for the Pisa/IIT SoftHand.
• To assess the feasibility of a synergy-driven prosthetic hand as a low-cost, robust alternative.
• To compare user experience and cognitive load across different control methods.

Main Methods:

• Developed and tested four myoelectric controllers: standard, impedance, vibrotactile feedback, and combined vibrotactile-impedance (VI).
• Utilized surface electromyography (EMG) signals for control.
• Four healthy subjects performed object grasping tasks with the prosthetic hand using each controller.

Main Results:

• All tested controllers enabled basic grasping.
• Impedance and vibrotactile feedback controllers reduced user's physical and cognitive load.
• The combined VI controller was perceived as the easiest to use among the four methods.

Conclusions:

• The Pisa/IIT SoftHand, with its synergy-driven approach, shows promise as a viable prosthetic hand.
• Hardware-based synergies offer a potentially low-cost and robust solution.
• Further validation with amputee users is necessary to confirm these findings.