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Clinical Trial Summary

This is a proof-of-concept study aimed at contributing evidence towards the need, usability and efficacy potential of the GoHandTM sensor in people with reduced hand function post-stroke. A two group, randomized, proof-of-concept, trial. The outcome is change over a one-month period in movement quality as measured by the GoHand sensor. The intervention period is one month. The intervention to be tested is the GoHand sensor, specifically the auditory feedback provided for an optimal wrist and hand movement during everyday tasks. To standardize the practice sessions, all persons will be taught the GRASP (Graded Repetitive Arm Supplementary Program) which has been shown to be of benefit to people recovering from stroke. The intervention group will practice the GRASP program with the sensor in feedback mode and the control group will practice with the sensor without feedback. The total sample size is 12, 6 per group. The study will be used to create movement metric algorithms and provide preliminary data for extent of change and usability.


Clinical Trial Description

Abstract One of the most frustrating and persistent motor sequelae of stroke is poor arm and hand function. There are many therapies for arm function post-stroke. The most effective strategies use repetitive, meaningful movement to promote neuroplasticity to support long lasting improvements in arm function. However, at best, the interventions are only moderately effective in improving impairment related outcomes with little or no carry over into everyday, real-world, activities. There are two gaps in this area, one is for effective interventions and the second is for methods of measuring outcomes that reflect real-world use of the arm. This study is designed to fill both these gaps with technology. GoHandTM is conceived to be a therapeutic wearable to provide auditory feedback for any voluntary wrist and finger movement. This type of positive auditory feedback is known to stimulate neural connections and, through the process of neural plasticity, imprint the learned movement pattern. The sensor also provides performance feedback that is motivating allowing patients to set and accomplish movement and practice goals and track progress. The global aim of this project is to develop and validate a sensing and feedback device to the detect disassociated wrist and arm movements and provide auditory feedback for hand movement over a range of starting capacities. The focus is on wrist movement because one of the strongest prognostic indicators for recovery of arm function post-stroke is 20o of active wrist extension and any degree of active finger movement.20 This is a proof-of-concept study aimed at contributing evidence towards the need, usability and efficacy potential of the GoHandTM sensor in people with reduced hand function post-stroke. People with stroke who have arm and hand movement deficits will be invited into a two group, randomized, proof-of-concept, trial. The outcome is change over a one-month period in movement quality as measured by the GoHand sensor. The intervention period is one month. The intervention to be tested is the GoHand sensor, specifically the auditory feedback provided for an optimal wrist and hand movement during everyday tasks. To standardize the practice sessions, all persons will be taught the GRASP (Graded Repetitive Arm Supplementary Program) which has been shown to be of benefit to people recovering from stroke. The intervention group will practice the GRASP program with the sensor in feedback mode and the control group will practice with the sensor without feedback. The total sample size is 12, 6 per group. The study will be used to create movement metric algorithms and provide preliminary data for extent of change and usability. ;


Study Design


Related Conditions & MeSH terms


NCT number NCT05321446
Study type Interventional
Source McGill University
Contact Nancy Mayo, PhD
Phone 15143862711
Email nancy.mayo@mcgill.ca
Status Not yet recruiting
Phase N/A
Start date July 1, 2022
Completion date October 31, 2022

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