Usability and Performance Assessment of Semiautonomous Hand-Wrist Prosthetic Control

Semiautonomous control strategies (SCS) could significantly enhance the reliability and naturalness of prosthetic hand control. Integrating a Computer Vision System (CVS) endows the prosthetic hand with the ability to recognize objects and autonomously select the omost suitable hand gesture configuration, while maintaining the user in the loop. In this paper, we present a SCS combining electromyographic (EMG) signals with a CVS. The system was tested on three able-bodied participants during Pick & Place tasks, achieving a 100% success rate, a mean usability score above 82/100, and a low cognitive burden with an average "Mental Demand" of 31.65/100.