Sonomyographic Upper Limb Prosthetics: A New Paradigm

Part of paid clinical trials in Fairfax, Virginia.

Sponsor
George Mason University
Study ID
NCT05376332
Status
Enrolling By Invitation

Conditions

  • Amputation
  • Prosthesis User

Eligibility Criteria

Sex
ALL
Age
18 Years - 65 Years
Healthy Volunteers
Not accepted

Interventions

  • Sonomyographic Prosthesis — DEVICE
    The sonomyographic system will include a custom-fitted test socket incorporating ultrasound transducers and controlling a TASKA prosthetic hand. All socket fittings will be performed by a board-certified prosthetist as part of this study.
  • Myoelectric direct control prosthesis — DEVICE
    The direct control system will include a custom-fitted test socket incorporating dual-site electrodes and controlling a TASKA prosthetic hand. All socket fittings will be performed by a board-certified prosthetist as part of this study.
  • Myoelectric pattern recognition prosthesis — DEVICE
    The pattern recognition system will include the subject's clinically-prescribed socket and commercially-available pattern recognition technology (IBT Sense). The pattern recognition system will not be fitted as part of this study, as subjects will already be trained users prior to enrolling in the study.

Study Details

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.

Key Dates

Start date
Nov 2, 2023
Status verified
Jan 2026
Primary completion
Jul 31, 2026
Completion
Jul 31, 2026

Study Design

Enrollment
16 participants (estimated)
Allocation
RANDOMIZED
Intervention model
CROSSOVER
Primary purpose
TREATMENT

Arms

  • Experimental: Sonomyographic control
    Sonomyographic control involves the use of ultrasound signals from muscle deformation to control a prosthetic hand.
  • Active Comparator: Myoelectric control
    Myoelectric control involves the use of surface electromyography signals from muscle activation to control a prosthetic hand.

Primary Outcome Measure

Fitt's Law Throughput [ Time Frame: at one week ]

Locations (1)

FacilityCityStateZIPSite coordinators
Peterson Health Sciences HallFairfaxVirginia22030-

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