Using AI to Measure Physical Activity After a Stroke
Validation and Testing of Artificial Intelligence Models to Measure Physical Activity in Patients Admitted to Hospital Following a Stroke
This study is testing if new AI technology can accurately track the movements and positions of people recovering from a stroke using sensors placed on their bodies.
Quick facts
| Study type | Observational |
|---|---|
| Enrollment | 34 (estimated) |
| Ages | 18 Years and up |
| Sex | All |
| Sponsor | Cambridge University Hospitals NHS Foundation Trust Academic / other |
| Locations | 1 site (Cambridge, Cambridgeshire) |
| Trial ID | NCT06030323 on ClinicalTrials.gov |
What this trial studies
This research focuses on developing artificial intelligence algorithms that utilize data from accelerometers to accurately detect the physical positions and movements of individuals recovering from a stroke. The study aims to assess the effectiveness of these algorithms in recognizing various positions, such as lying, sitting, or standing, and movements like walking or standing up. Participants will be recruited from a hospital setting, where they will undergo a one-time assessment to gather data for the algorithm development. The study will explore the impact of sensor placement on the accuracy of the measurements.
Who should consider this trial
Good fit: Ideal candidates for this study are individuals who have been admitted to the hospital with an acute stroke diagnosis.
Not a fit: Patients who are unable to provide informed consent or are receiving end-of-life care may not benefit from this study.
Why it matters
Potential benefit: If successful, this study could enhance the monitoring of physical activity in stroke patients, leading to improved rehabilitation strategies.
How similar studies have performed: While the use of AI in monitoring physical activity is a growing field, this specific approach to measuring activity post-stroke is relatively novel and has not been extensively tested.
Eligibility criteria
Show full inclusion / exclusion criteria
Inclusion Criteria: * admitted to hospital with a diagnosis of an acute stroke. Exclusion Criteria: * unable to provide informed consent; * receiving end-of-life care; * the consultant in charge of their care disagrees with their inclusion
Where this trial is running
Cambridge, Cambridgeshire
- Cambridge University Hospital NHS Foundation Trust — Cambridge, Cambridgeshire, United Kingdom (Recruiting)
Study contacts
- Study coordinator: Peter Hartley, PhD
- Email: peter.hartley@nhs.net
- Phone: 441223596317
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.