ELECTROMYOGRAPHIC SIGNAL PROCESSING FOR PROSTHETICS

There are over 2 million amputees in the United States, all of whom face challenges that impact their quality of life. Innovations in myoelectric prosthetics are emerging that enable better prosthetic-amputee control and interaction, and displace passive, older prosthetics. Yet, current models of myoelectric prosthetics rely on low degree-of-freedom decoding methods that create obstacles to graded movements and require significant contractile force to stimulate.

Software designed using a Kalman filter enables individual digit, wrist, elbow, and shoulder control for transhumoral and above amputees. The algorithm allows real-time, proportional, intuitive control of the prosthetic, with no need for recalibration. This gives prosthetics capabilities more akin to natural limbs and improves users’ quality of life.