Intelligenta proposes to prove feasibility of a user-adaptive myoelectric (muscle electric field) controller based on advanced programming technology for a below-elbow prosthetic arm. Today's prosthetic hands are typically either body-powered (actuated with shoulder motion against a cable-moving harness) or electric-powered (motordriven prosthesis controlled with myoelectric activity from muscle contractions) providing only a single motion, open and close of a pliers-like gripper. Our proposed myoelectric controller, combined with a prosthetic hand and wrist with multiple joints, will give the user a multitude of functions which are controlled by visualizing motion of the lost limb. The functions controlled can vary from user to user, depending on their needs. Our preliminary results indicate that this controller is a realistic possibility -- we have already demonstrated 100 percent accuracy discriminating three different thumb motions on one subject's normal arm, and 95 percent accuracy discriminating phantom limb motions on two limb-deficient subjects. In this Phase I, we join with a prestigious rehabilitation hospital to test the approach on five additional limb-deficient subjects, including two with prosthetic-type and myoelectric measurement equipment and sockets.
The immediate commercial result from this effort is an advanced controller for upper extremity prostheses. This multi-function, user- adaptive, easy-to-use controller will appeal to over 100,000 Americans with upper limb deficiencies. In the proposed project, we focus on a hand and wrist product for the largest subset (below-elbow) of upper limb-deficient people, but we can easily expand it for additional motions, amputation levels, and congenital as well as traumatic limb loss. With minor modifications, the system proposed here for myoelectric control can create individualized neuroelectric prosthesis controllers when microelectrode nerve connections mature to long-term, routine use in humans. The proposed research will open powerful new options to tap directly into the nervous system for prosthesis control signals. The technology developed in the effort can also control powered orthotics to help people with paralysis (e.g., myoelectrically- controlled grasping helpers for those with spinal injuries compromising hand dexterity and strength). It can be adapted to automate diagnostics (e.g., assist physicians in finding neuro-muscular pathologies).
