Research Project
8831819
DESCRIPTION (provided by applicant): Pattern recognition (PR) myoelectric control systems can dramatically improve an amputee patient's control of a powered prosthesis, but they have not been made commercially available. Coapt, LLC, is a start-up stage company that has initiated a controlled commercial release of PR myoelectric control for the benefit of upper- limb amputees. The controller is based on research completed by the Center for Bionic Medicine at the Rehabilitation Institute of Chicago (RIC) and has been widely developed and tested with transradial and higher-level amputees. Coapt has previously licensed valuable PR controller technology and intellectual property from the RIC. Upper-limb amputees are faced with significant impairment and have not previously benefitted from the advances in PR control technology. Conveniently, commercially available multifunction prostheses are now available that offer users multiple powered options but these are not presently enabled with PR control. The long-term goal is to provide upper-limb amputees with a more intuitive option for controlling their externally powered prostheses. The objective of this application is to make the initially released commercial product intuitive enough that it can reliably work across a variety of sites and manufactures with minimal on-site engineering time. Coapt's first product is an advanced PR microcontroller system that can 'drive' any existing or future prosthetic arm system by interpreting electromyographic (EMG) signal patterns. An important factor in the development of such a broad reaching approach is reaching as many amputee patients as possible. To achieve consumer acceptance, the product offering must be realized according to the needs and practices of the prosthetic practitioner. This application comprises the following three specific aims: (1) develop a clinically focused software package; (2) complete in laboratory testing of commercially available multifunction arm systems; and (3) evaluate quantitative data regarding the fitting process and resulting prosthesis usage in take- home settings across multiple sites. Under the first aim the clinician-facing elements of the system's configuration software will be implemented with iterative clinical evaluations. Under the second aim, the PR controller system will be configured to enhance the control of commercially available multifunction hand prostheses on amputee subjects. The third aim will provide valuable information that we can compare against bench-mark data from conventional control usage, which in turn will inform future design decisions. The proposed research is significant because it enables a pathway to connect pattern recognition-based myoelectric control with commercially available multifunction prostheses from being adopted. Ultimately, this research will help upper-limb amputees to dramatically improve the control of their prostheses, allowing for an improved quality of life and promote return to work in many cases.
