The vast majority of all trauma-related amputations in the United States involve the upper limbs. Approximately half of those individuals who receive a upper extremity myoelectric prosthesis eventually abandon use of the system, primarily because of their limited functionality. Thus, there continues to be a need for a significant improvement in prosthetic control strategies. The objective of this bioengineering research program is to develop and clinically evaluate a prototype prosthetic control system that uses imaging to sense residual muscle activity, rather than electromyography. This novel approach can better distinguish between different functional compartments in the forearm muscles, and provide robust control signals that are proportional to muscle activity. This improved sensing strategy has the potential to significantly improve functionality of upper extremity prostheses, and provide dexterous intuitive control that is a significant improvement over current state of the art noninvasive control methods. This interdisciplinary project brings together investigators at George Mason University, commercial partners at Infinite Biomedical Technologies as well as clinicians at MedStar National Rehabilitation Hospital. The investigators will optimize and implement algorithms for real-time classification and control with multiple degrees of freedom (DOF) using a miniaturized ultrasound system incorporated into a prosthetic socket. The investigators will then compare control performance between and sonomyography and myoelectric control (both direct control and pattern recognition) using a virtual environment as well as for performance of tasks related to activities of daily living. The investigators have two specific aims. Specific Aim 1: Compare between sonomyography and myoelectric direct control Specific Aim 2: Compare between sonomyography and pattern recognition with velocity control The successful completion of this project will lead to the first in human evaluation of an integrated prototype that uses low-power portable imaging sensors and real-time image analysis to sense residual muscle activity for prosthetic control. In the long term, the investigators anticipate that the improvements in functionality and intuitiveness of control will increase acceptance by amputees.
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Fitt's Law Throughput
Timeframe: at one week
Southampton Hand Assessment Procedure (SHAP)
Timeframe: at two weeks