Soft robotic glove for wrist and hand recovery after stroke
Official title: Design and Development of a Soft Robotic Glove for Enhanced Task-Oriented Training in Stroke Rehabilitation: Incorporating Dual-Chamber Actuators and Flexible Magnetoelastic Force Sensors
Run by Chinese University of Hong Kong · NCT07329075 · Data updated 2026-11-12
This study will try a soft robotic glove that uses EMG (muscle) signals to help people with chronic stroke regain wrist and hand movement.
Quick facts
| Study type | Interventional |
|---|---|
| Ages | 18 Years and up |
| Sex | All |
| Enrollment | 60 (estimated) |
| Sponsor | Chinese University of Hong Kong Academic / other |
| Locations | 1 site (Hong Kong) |
| Status | Recruiting |
| Started | January 2026 |
| Main results expected | December 2028 |
| Study ends | December 2028 |
| Registry record updated | January 9, 2026 |
| Trial ID | NCT07329075 on ClinicalTrials.gov |
Is this trial a fit for you?
✓Likely a good fit
Ideal candidates are adults at least six months after stroke with adequate cognition, the ability to sit for 30 minutes, detectable residual EMG signals in specified forearm and thumb muscles, and finger spasticity within Modified Ashworth Scale levels 0–3.
✕Probably not a fit
People with acute stroke (<6 months), no detectable EMG signals in the target muscles, severe communication or cognitive impairment, active substance abuse, or other medical conditions that prevent participation are unlikely to benefit.
A plain-English reading of the study's rules. Only the study team can confirm whether you qualify.
What this trial studies
This randomized controlled trial will enroll 60 people with chronic stroke and divide them into three groups to compare a new EMG‑controlled soft forearm robot to conventional rehabilitation. Participants will attend 20 training sessions and three assessment visits, with the device using residual EMG from forearm and thumb muscles to detect movement intention and adapt assistance for various tasks. Outcomes will include standardized motor function measures and objective performance on wrist and hand tasks to compare recovery between groups. The study is designed to provide controlled evidence on whether this adaptive soft-robotic approach improves upper-limb rehabilitation beyond usual therapy.
Why it matters
Potential benefit: If successful, the device could improve hand and wrist recovery by providing intention-driven, adaptive assistance during therapy.
How similar studies have gone: Previous small pilot studies of soft robotic gloves and EMG‑controlled upper-limb devices have shown promising results, but large randomized trials are still limited.
Who can join: the full rules
Show full inclusion / exclusion criteria
Inclusion Criteria: * chronic stage (6 months post-onset); * adequate cognition to follow study instructions; * being able to sit for 30 minutes; * having detectable residual EMG signals from the affected side's flexor digitorum (FD) and extensor digitorum (ED) muscles, as well as the abductor pollicis brevis (APB) and flexor pollicis longus (FPL); and * Modified Ashworth Scale (MAS) score indicating levels of finger spasticity of 0, 1, 1+, 2, and 3 (i.e., 0 = no muscle tone to 3 = increase in tone, difficult in passive movement). Exclusion Criteria: * severe dysphasia, * conditions that could hinder study compliance, and * certain medical or psychological disorders, such as alcoholism and substance abuse
Where it's running
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Department of Biomedical Engineering, The Chinese University of Hong Kong
Hong Kong, Hong Kong Recruiting
Study contacts
- Principal investigator: Raymond Tong, PhD — Chinese University of Hong Kong
- Study coordinator: Raymond Tong, PhD
- Email: kytong@cuhk.edu.hk
- Phone: 39438454
Similar studies
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How to take part
- Review the eligibility criteria above with your treating physician.
- Check the official listing on ClinicalTrials.gov for the latest contact details and recruitment status.
- Contact the study coordinator or principal investigator to ask for pre-screening. Pre-screening is free and never obligates you to enroll.