Digital twin to predict stroke recovery and enable personalized care
A Study for the Development of Prognosis Predictive Precision Medicine Based on a Digital Twin Reflexing the Motor Patterns in Stroke Patients: a Prospective Study
The study collects clinical, daily movement, and genetic data from adults with recent stroke to see if personalized digital models can predict their recovery.
Quick facts
| Study type | Observational |
|---|---|
| Enrollment | 70 (estimated) |
| Ages | 20 Years and up |
| Sex | All |
| Sponsor | CHA University Academic / other |
| Locations | 1 site (Gyeonggi-do, Gyeonggi-do) |
| Trial ID | NCT07482579 on ClinicalTrials.gov |
What this trial studies
This is a longitudinal, observational effort enrolling adults within one month of stroke to capture recovery from the subacute into the chronic stage. Researchers will collect high-quality clinical information, continuous daily activity and movement patterns (likely via wearable or monitoring devices), and genomic data to create a multidimensional patient dataset. The combined data will be used to develop visual, data-driven representations and predictive models—sometimes described as a "digital twin"—to characterize individual recovery trajectories. All participation is non-interventional and conducted at a single center with serial follow-up to track outcomes over time.
Who should consider this trial
Good fit: Adults aged 20 or older with a confirmed stroke within one month of onset, limited ambulatory ability (FAC score 0–3), and the ability to give informed consent (or with a representative) are the intended participants.
Not a fit: People beyond the one-month post-stroke window, those with better ambulatory function (FAC >3), or those with severe cognitive impairment without a caregiver are less likely to benefit from this protocol.
Why it matters
Potential benefit: If successful, the project could help clinicians give more personalized prognosis and guide tailored rehabilitation strategies for people after stroke.
How similar studies have performed: Previous research has used wearables, registries, and genomic data separately to study stroke outcomes, but integrating these streams into a clinical "digital twin" is relatively novel and not yet widely proven.
Eligibility criteria
Show full inclusion / exclusion criteria
Inclusion Criteria: * Adults aged 20 years or older with a confirmed diagnosis of stroke. * Within 1 month after stroke onset. * Patients scoring between 0 and 3 points on the Functional Ambulatory Category (FAC) test. * Patients or their legally authorized representatives who have fully understood the details of this study, voluntarily decided to participate, and provided written informed consent to comply with the study instructions. Exclusion Criteria: * Patients with impaired ability to provide consent (MMSE score less than 10) who are not accompanied by a caregiver. * Any other cases deemed inappropriate for participation by the investigator. (This study is non-interventional; therefore, patients who are currently participating in or have participated in another clinical study or research within the past 30 days may still be included.)
Where this trial is running
Gyeonggi-do, Gyeonggi-do
- Bundang CHA Medical Center — Gyeonggi-do, Gyeonggi-do, South Korea (Recruiting)
Study contacts
- Principal investigator: Seyoung Shin, MD — CHA University
- Study coordinator: Seyoung Shin, MD
- Email: seyoung0706@chamc.co.kr
- Phone: +82437505000
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.