Cognitive-based Prosthetics to Improve Grasp and Reaching After SCI

Cognitive-based Rehabilitation Platform of Hand Grasp After Spinal Cord Injury Using Virtual Reality and Instrumented Wearables

Rehabilitation of functional movements after spinal cord injury (SCI) requires commitment and engagement to the processes of physical therapy. Outcomes may be improved by techniques that strengthen cognitive connections between users and physical therapy exercises.

The investigators will investigate combinations of virtual reality and innovative wearable technology to accelerate rehabilitation of hand grasp and reach. These devices use multi-sensory feedback to enhance the sense of agency, or feelings of control, and better train movements during physical rehabilitation exercises. The investigators will measure the effect of these devices on improving the speed, efficiency, and accuracy of performed movements in Veterans with SCI.

Study Overview

• Status: Completed
• Conditions: Spinal Cord Injuries; Hand Weakness
• Intervention / Treatment: Device: Cognition glove; Device: Sensory brace

Detailed Description

Spinal cord injury (SCI) at the cervical level impairs hand function severely compromises performance of activities of daily living. The physical rehabilitation process requires commitment by the participant to achieve meaningful gains in function. Rehabilitation approaches that are cognitively engaging can facilitate greater commitment to practice and improved movement learning.

The investigators propose to develop innovative platforms that utilize virtual reality (VR) and instrumented wearables that enhance cognitive factors during motor learning of hand grasp and reach after SCI. These factors include greater sense of agency, or perception of control, and multi-sensory feedback. Sense of agency is implicated with greater movement control, and various sensory feedback modalities (visual, audio, and haptic) are proven effective in movement training. However, these factors are not well considered in traditional physical therapy approaches.

The investigators have developed two novel cognitive-based platforms for rehabilitating grasp and reach function and propose to test each platform in Veterans with chronic SCI at the cervical level.

Aim 1 will investigate how the "cognition" glove may improve functional grasp. This glove includes force and flex sensors that provide inputs to a machine learning algorithm trained to predict when secure grasp is achieved. The glove alerts the user of secure grasp through onboard sensory modules providing visual (LED), audio (beeper), and tactile (vibrator) feedback. During training, feedback is provided at gradually shorter time-intervals to progressively induce agency based on the neuroscience principle of 'intentional binding'. This principle suggests that with greater agency, one perceives their action (i.e., secure grasp) is more coupled in time to a sensory consequence (i.e., glove feedback). The glove is user-ready, and now has compatibility with customized VR applications to provide enhanced sensory feedback through engaging and customized visual and sound alerts. The investigators hypothesize that enhanced feedback in VR will produce even greater improvements in grasp performance than onboard feedback alone.

Aim 2 will investigate how Veterans with SCI may learn greater arm muscle control during virtual reaching while using a "sensory" brace that provides isometric resistance to one arm to elicit electromyography (EMG) patterns that can drive a virtual arm. The person receives visual feedback from VR and muscle tendon haptic feedback from the brace during training. Tendon stimulation can elicit movement sensations that modulate muscle activation patterns. The VR feedback will provide conscious movement training cues while vibration feedback will subconsciously elicit more distinct EMG patterns based on cluster analysis. The investigators hypothesize that the promotion of distinct EMG patterns, achieved by maximizing inter-cluster distances, will improve performance of a reach-to-touch task.

Importantly, the concept of strengthening cognitive agency and learning of movement using wearable technology, multi-sensory feedback, and virtual reality during physical training will be applicable to all forms of neuromuscular impairment, including stroke and traumatic brain injury in addition to SCI.

• Study Type: Interventional
• Enrollment (Actual): 13
• Phase: Not Applicable

Contacts and Locations

Study Locations

• United States
  • New York
    • Bronx, New York, United States, 10468-3904
      • James J. Peters VA Medical Center, Bronx, NY

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: 18 years to 65 years (Adult, Older Adult)
• Accepts Healthy Volunteers: Yes

Description

Inclusion Criteria:

• SCI occurred greater than 12 months ago
• SCI occurred between levels C1-T1
• Hand weakness: score of 2, 3, or 4 out of 5 on manual muscle testing of finger extension, finger flexion, or finger abduction in either hand

Exclusion Criteria:

• History of other serious brain or spinal cord injuries
• History of seizures
• Ventilator dependence; open tracheostomy
• Use of medications that significantly lower seizure threshold
• History of significant cognitive deficits
• Open skin lesions over the face, neck, shoulders, arms, or hands
• Pregnancy

Study Plan

How is the study designed?

Design Details

• Primary Purpose: Device Feasibility
• Allocation: Non-Randomized
• Interventional Model: Crossover Assignment
• Masking: Single

Number of Arms

3

Arms and Interventions

Participant Group / Arm	Intervention / Treatment
Active Comparator: No cognitive feedback; Perform task without cognitive feedback.	Device: Cognition glove; The investigators have developed and tested a functional prototype of an instrumented glove to alert the user about secure grasp of objects. Onboard force and flex sensors provide inputs to a machine learning algorithm (artificial neural network, ANN) to estimate secure grasp based on previously collected training data. The glove enhances agency by alerting the user to secure grasp through sensory feedback modules (visual - LED, audio - beeper, tactile - vibrator).; Device: Sensory brace; A a size- and position-adjustable arm brace with weight-support capability and housing for vibration motors and EMG sensors. Position adjustment allows for physical therapists to find and recommend arm postures that are clinically relevant to each person. The participant can then isometrically push/resist against the brace to strengthen target muscles while performing VR reach-to-touch. The person will receive visual feedback from the virtual environment to train movement performance and vibrotactile feedback at tendons to subconsciously adjust their muscle activation patterns
Active Comparator: Intermediate feedback.; Perform task with intermediate feedback.	Device: Cognition glove; The investigators have developed and tested a functional prototype of an instrumented glove to alert the user about secure grasp of objects. Onboard force and flex sensors provide inputs to a machine learning algorithm (artificial neural network, ANN) to estimate secure grasp based on previously collected training data. The glove enhances agency by alerting the user to secure grasp through sensory feedback modules (visual - LED, audio - beeper, tactile - vibrator).; Device: Sensory brace; A a size- and position-adjustable arm brace with weight-support capability and housing for vibration motors and EMG sensors. Position adjustment allows for physical therapists to find and recommend arm postures that are clinically relevant to each person. The participant can then isometrically push/resist against the brace to strengthen target muscles while performing VR reach-to-touch. The person will receive visual feedback from the virtual environment to train movement performance and vibrotactile feedback at tendons to subconsciously adjust their muscle activation patterns
Experimental: Enhanced feedback; Perform task with virtual reality and/or haptic feedback.	Device: Cognition glove; The investigators have developed and tested a functional prototype of an instrumented glove to alert the user about secure grasp of objects. Onboard force and flex sensors provide inputs to a machine learning algorithm (artificial neural network, ANN) to estimate secure grasp based on previously collected training data. The glove enhances agency by alerting the user to secure grasp through sensory feedback modules (visual - LED, audio - beeper, tactile - vibrator).; Device: Sensory brace; A a size- and position-adjustable arm brace with weight-support capability and housing for vibration motors and EMG sensors. Position adjustment allows for physical therapists to find and recommend arm postures that are clinically relevant to each person. The participant can then isometrically push/resist against the brace to strengthen target muscles while performing VR reach-to-touch. The person will receive visual feedback from the virtual environment to train movement performance and vibrotactile feedback at tendons to subconsciously adjust their muscle activation patterns

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Percent Change in Time to Achieve Secure Grasp (Cognition Glove Only)	Percent change in time (seconds) to achieve secure grasp. Lower time is better.	Baseline and Following the 6 hour lab session, assessed while performing the task
Percent Change in Time to Complete Pick-up and Placement of Object-Cognition Glove	Percent change in time (seconds) to pick up and re-place object. Lower time is better.	Baseline and Following the 6 hour lab session, assessed while performing the task
Percent Change in Time to Complete Trial-Sensory Brace	Percent change in time (seconds) to complete target reaching trials in VR environment. Lower time is better.	Baseline and Following the 6 hour lab session, assessed while performing the task

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Percent Change in Motion Pathlength in Moving Object-Cognition Glove	Percent change in pathlength during reaching/grasping/moving. Shorter is better.	Baseline and Following the 6 hour lab session, assessed while performing the task
Percent Change in Motion Pathlength Toward Virtual Targets-Sensory Brace	Percent change in pathlength during reaching virtual targets. Shorter is better.	Baseline and Following the 6 hour lab session, assessed while performing the task
Error in Placing Object Onto Target (Cognition Glove Only)	Error in completing placement of object onto target.	Baseline and Following the 6 hour lab session, assessed while performing the task

Collaborators and Investigators

• Sponsor: VA Office of Research and Development
• Collaborators: Stevens Institute of Technology
• Investigators: Principal Investigator: Noam Y. Harel, MD PhD, James J. Peters Veterans Affairs Medical Center

Publications and helpful links

General Publications

• Liu M, Wilder S, Sanford S, Saleh S, Harel NY, Nataraj R. Training with Agency-Inspired Feedback from an Instrumented Glove to Improve Functional Grasp Performance. Sensors (Basel). 2021 Feb 7;21(4):1173. doi: 10.3390/s21041173.

Study record dates

Study Major Dates

• Study Start (Actual): May 17, 2021
• Primary Completion (Actual): October 17, 2023
• Study Completion (Actual): November 30, 2023

Study Registration Dates

• First Submitted: September 14, 2020
• First Submitted That Met QC Criteria: October 5, 2020
• First Posted (Actual): October 8, 2020

Study Record Updates

• Last Update Posted (Actual): April 25, 2025
• Last Update Submitted That Met QC Criteria: April 7, 2025
• Last Verified: April 1, 2025

More Information

Terms related to this study

• Additional Relevant MeSH Terms: Central Nervous System Diseases; Nervous System Diseases; Wounds and Injuries; Trauma, Nervous System; Spinal Cord Diseases; Spinal Cord Injuries
• Other Study ID Numbers: B3582-P

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: YES

IPD Plan Description

A Limited Dataset (LDS) will be shared in electronic format pursuant to a VA-approved Data Use Agreement.

This will include all outcomes data and deidentified demographics.

Individually Identifiable Data will be shared pursuant to valid HIPAA Authorization, Informed Consent, and an appropriate written agreement limiting use of the data to the conditions as described in the authorization and consent, and a written assurance from the recipient that the information will be maintained in accordance with the security requirements of 38 CFR Part 1.466.

• IPD Sharing Time Frame: Upon publication.
• IPD Sharing Access Criteria: Individually Identifiable Data will be shared pursuant to valid HIPAA Authorization, Informed Consent, and an appropriate written agreement limiting use of the data to the conditions as described in the authorization and consent, and a written assurance from the recipient that the information will be maintained in accordance with the security requirements of 38 CFR Part 1.466.
• IPD Sharing Supporting Information Type: STUDY_PROTOCOL

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: Yes
• product manufactured in and exported from the U.S.: No