Monitoring arm recovery after stroke with a smartphone camera
Developing an Accessible, Cost-Effective Motion Analysis Tool for Arm Movement After Stroke
King's College London · NCT07016295
This project tests a smartphone app that uses the phone camera and pose-estimation AI to measure arm movement in people with mild-to-moderate arm weakness after stroke.
Quick facts
| Study type | Observational |
|---|---|
| Enrollment | 30 (estimated) |
| Ages | 18 Years and up |
| Sex | All |
| Sponsor | King's College London (other) |
| Locations | 1 site (London) |
| Trial ID | NCT07016295 on ClinicalTrials.gov |
What this trial studies
The investigators will recruit 12 stroke survivors with mild-to-moderate upper limb impairment for a single 2–3 hour in-person session at King's College London, Guy's Campus. Participants will perform a range of upper-limb tasks while video is captured and simultaneously recorded with gold-standard 3-D motion capture for comparison. Open-source pose-estimation models will be applied to the phone video to extract kinematic measures, and models will be optimized if discrepancies with the gold standard are found. A smartphone front-end and software back-end will be developed to record, analyse, and integrate movement metrics into clinical records for clinician and patient feedback.
Who should consider this trial
Good fit: Adults with a history of stroke and mild-to-moderate upper limb impairment (Fugl-Meyer Upper Limb score 9–60/66) who can sit independently, consent, understand instructions, and transfer to the lab chair as needed.
Not a fit: People with severe cognitive or language deficits, marked shoulder pain (>3/10), inability to sit independently, or who cannot transfer from their wheelchair (or have a non-collapsible wheelchair backrest) are unlikely to benefit or be eligible.
Why it matters
Potential benefit: If successful, the app could provide a low-cost, easy way for clinicians to monitor arm recovery and tailor rehabilitation without needing expensive motion-capture labs.
How similar studies have performed: Pose-estimation approaches have shown promising agreement with lab motion-capture in healthy and some clinical populations, but direct validation against gold-standard kinematics in stroke survivors remains limited.
Eligibility criteria
Show full inclusion / exclusion criteria
Stroke survivors Inclusion Criteria: * History of stroke * Arm impairment evidenced by Fugl-Meyer Upper Limb Assessment between 9-60/66. Exclusion Criteria: * Severe cognitive impairment preventing ability to consent to treatment and understand and follow research protocol * Severe language deficit preventing ability to consent to treatment and understand and follow research protocol * Shoulder pain \>3/10 on visual analog scale * Unable to maintain independent sitting balance without a high back support. * Wheelchair users that are unable to transfer with assistance of 1 to lab chair or whose wheelchair backrest cannot colapse.
Where this trial is running
London
- Centre for Human and Applied Physiological Sciences — London, United Kingdom (RECRUITING)
Study contacts
- Study coordinator: Ulrike Hammerbeck, PhD
- Email: ulrike.hammerbeck@kcl.ac.uk
- Phone: +44 (0) 20 7888 6292
How to participate
- Review the eligibility criteria above with your treating physician.
- Visit the official trial page on ClinicalTrials.gov for the most current contact information and recruitment status.
- Contact the listed study coordinator or principal investigator to request pre-screening. Pre-screening is free and never obligates you to enroll.
Conditions: Stroke, biomechanics, pose estimation models, upper limb