RESCU System for Robust Upper Limb Prosthesis Control

NCT04043234 | Completed Results

• 1 other identifier: U44NS108894
• Study Type: interventional
• Target: 4
• Locations: 1 country
• Sites: 1

Brief Summary

This study will compare the use of RESCU \[Experimental\] Prosthesis with a \[Standard\] pattern recognition prosthesis in a clinical setting and in unsupervised daily activity. The protocol will follow a single case experimental design (SCED) to compensate for the limited size of the patient population. Each of the participants will use the Standard and Experimental and systems over a 35-day period. The Standard system will include at least two controllable DoFs (hand, wrist, multi-articulated hand, etc) and a commercially-available pattern recognition controller. The RESCU system will use the same components as the Standard system but will differ with respect to incorporating eight IBT Element Electrodes (as required for pattern recognition control) and the RESCU control software. The hypothesis is that pattern recognition will outperform the commercially-available control strategy for most participants on in-clinic, at-home usage, and subjective measures.

Conditions

Amputation; Upper Limb

Keywords

upper limb; amputation; prosthesis; myoelectric; pattern recognition

Outcome Measures

Primary Outcomes (1)

• Mean Daily Prosthesis Use Duration

  Prosthesis usage time was monitored as a proxy for user satisfaction, under the assumption that when an individual is more satisfied with their prosthetic solution, they will use it more in their daily lives. For the experimental intervention, the mean daily prosthesis use duration is reported as the average number of hours the prosthesis was used daily over the evaluation period (i.e., four weeks). For the control intervention, the mean daily prosthesis use duration is reported as the average number of hours the prosthesis was used daily before the evaluation period (i.e., at baseline).

  Baseline, 4 weeks

Secondary Outcomes (7)

• Activities Measure for Upper Limb Amputees (AM-ULA)

  Baseline, Post-Fitting, Post-Intervention

• Orthotics and Prosthetics User's Survey Upper Extremity Functional Status (OPUS UEFS)

  Baseline, Post-Intervention

• Trinity Amputation and Prosthesis Experience Survey for Upper Limb Amputation (TAPES-ULA)

  Baseline, Post-Intervention

• PROMIS Satisfaction Short Form 8a

  Baseline, Post-Intervention

• Pain Scale

  Baseline, Post-Fitting, Post-Intervention

Study Arms (1)

Single-Case Experimental Design

EXPERIMENTAL

Participants act as their own controls. They first use the Control device, which includes the pattern recognition controller, 8 electrodes, batteries, socket, frame, and prosthesis terminal device (hand/wrist/elbow). Participants are then transitioned to the Experimental device, which includes the RESCU controller, Apple iPad, 8 electrodes, batteries, socket, frame, and prosthesis terminal device (hand/wrist/elbow).

Device: RESCU; Device: Pattern Recognition

Interventions

RESCU DEVICE

Retrospectively Supervised Classification Updating (RESCU) is founded on two innovations that promise significant improvement in performance and outcome. The first is a highly robust machine intelligence algorithm, an Extreme Learning Machine with Adaptive Sparse Representation (EASRC), and the second is a novel adaptive learning algorithm and communication interface we call Nessa. We contend that these two technologies allow the prosthetic device to adapt to its user from the initial fitting through continuing, long-term use in the activities of daily living, shifting the paradigm of training from the current prospective data gathering methods to a more dynamic retrospective application.

Single-Case Experimental Design

Pattern Recognition DEVICE

Pattern recognition prostheses associate the patterns of activity of multiple EMG sites to the action of a prosthesis. Such strategies have historically required prospective calibration of the EMG activation patterns.

Single-Case Experimental Design

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)

You may qualify if:

• Trans-radial limb difference.
• Candidate for a 2+ degree-of-freedom (DoF) myoelectric pattern recognition prosthesis as determined by the study prosthetist
• Active pattern recognition myoelectric prosthesis user
• Fluent in English
• Age of 18 years or greater

You may not qualify if:

• Patients with a residual limb that is unhealed from the amputation surgery
• Patients with easily damaged or sensitive skin who would not tolerate EMG electrodes
• Unhealed wounds
• Significant cognitive deficits as determined upon clinical evaluation
• Significant neurological deficits as determined upon clinical evaluation
• Significant physical deficits of the residual limb impacting full participation in the study as determined upon clinical evaluation
• Uncontrolled pain or phantom pain impacting full participation in the study as determined upon clinical evaluation
• Serious uncontrolled medical problems as judged by the project therapist

Sponsors & Collaborators

• Infinite Biomedical Technologies: lead

Study Sites (1)

Medical Center O&P

Silver Spring, Maryland, 20910, United States

Location

Results Point of Contact

• Title: Chief Executive Officer
• Organization: Infinite Biomedical Technologies, LLC

rahul@i-biomed.com

(443) 451-7177

Publication Agreements

• PI is Sponsor Employee: No
• Restrictive Agreement: No

Study Design

• Study Type: interventional
• Allocation: NA
• Masking: NONE
• Masking Details: The occupational therapist who graded the AM-ULA functional assessment was masked to participant IDs and intervention
• Purpose: SUPPORTIVE CARE
• Intervention Model: SINGLE GROUP
• Sponsor Type: INDUSTRY
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Chief Executive Officer

Model Details: Single-Case Experimental Design (SCED)

Study Record Dates

• First Submitted: July 31, 2019
• First Posted: August 2, 2019
• Study Start: November 7, 2023
• Primary Completion: December 19, 2023
• Study Completion: December 19, 2023
• Last Updated: April 24, 2024
• Results First Posted: April 24, 2024

Record last verified: 2024-04

Data Sharing

• IPD Sharing: Will not share

Locations

US (1)