RESCU System for Robust Upper Limb Prosthesis Control

NCT ID: NCT04043234

Last Updated: 2024-04-24

Basic Information

• Recruitment Status: COMPLETED
• Total Enrollment: 4 participants
• Study Classification: INTERVENTIONAL
• Study Start Date: 2023-11-07
• Study Completion Date: 2023-12-19

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.

Detailed Description

The AB sequence for the study protocol is described below, where control type A is the Standard prosthesis and control type B is the Experimental prosthesis.

On Day 0, the participant will be evaluated with the Standard prosthesis. A series of Measures (as defined in the next paragraph) will then be recorded. The participant will then take the prosthesis home for one week, and daily use data will be recorded. The participant will return to the clinic for Day 7 Measures and download of the daily use data. During this session, the participant will be fit with the second system, undergo occupational therapy in the clinic, and Measures will be recorded. There will be no washout period as the prosthesis is expected to be in daily use. The participants will go home for a four-week period and return on Day 35 for a third set of Measures. At this time, the participant will be asked which prosthesis he/she prefers.

There are limited functional outcome assessment options for the planned comparison. However, the investigators will test functional measures at the clinic appointments, examine daily use data, and administer several qualitative surveys to assess participant outcomes.

Conditions

Amputation; Upper Limb

Study Design

• Allocation Method: NA
• Intervention Model: SINGLE_GROUP
• Primary Study Purpose: SUPPORTIVE_CARE
• Blinding Strategy: NONE

Study Groups

Single-Case Experimental Design

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).

Group Type: EXPERIMENTAL

RESCU

Intervention Type: 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.

Pattern Recognition

Intervention Type: 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.

Interventions

RESCU

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.

Intervention Type: DEVICE

Pattern Recognition

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.

Intervention Type: DEVICE

Eligibility Criteria

Inclusion Criteria

• 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

Exclusion Criteria

• 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

• Minimum Eligible Age: 18 Years
• Eligible Sex: ALL
• Accepts Healthy Volunteers: No

Sponsors

Infinite Biomedical Technologies

INDUSTRY

Sponsor Role: lead

Responsible Party

Rahul Kaliki

Chief Executive Officer

Responsibility Role: PRINCIPAL_INVESTIGATOR

Locations

Medical Center O&P

Silver Spring, Maryland, United States

Countries

United States

Provided Documents

Document Type: Study Protocol and Statistical Analysis Plan

View Document

Document Type: Informed Consent Form

View Document

Other Identifiers

U44NS108894

Identifier Type: NIH

Identifier Source: org_study_id

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