Validation of AI Models to Measure Physical Activity After a Stroke
- Conditions
- Stroke
- Registration Number
- NCT06030323
- Brief Summary
The research team are developing algorithms using artificial intelligence that use information collected by accelerometers to detect a person's position, such as whether an individual is lying, sitting, or standing, and the individual's movements, such as whether they are taking steps or standing up.
Sensor location will affect the accuracy of the model and acceptability of the method. The research team are therefore developing algorithms for four different locations.
The purpose of the research is for the development of the algorithms and check whether they accurately recognise different positions and movements in people whose movement is affected by a stroke, and by being in a hospital environment (e.g. using a profiling bed).
The research team plan to recruit between 34 and 50 participants who are admitted hospital due to having a stroke. After providing informed consent, participants will be asked to complete a one-off assessment with a member of the research team and a ward physiotherapist. Participants will be asked to wear the four sensors, and move through a series of postures, walk for up to six minutes, and stand as many times as they feel able in one minute.
- Detailed Description
Not available
Recruitment & Eligibility
- Status
- RECRUITING
- Sex
- All
- Target Recruitment
- 34
- admitted to hospital with a diagnosis of an acute stroke.
- unable to provide informed consent;
- receiving end-of-life care;
- the consultant in charge of their care disagrees with their inclusion
Study & Design
- Study Type
- OBSERVATIONAL
- Study Design
- Not specified
- Primary Outcome Measures
Name Time Method Sensitivity and specificity of AI models Collected during hospitalisation (up to 12 weeks)
- Secondary Outcome Measures
Name Time Method
Trial Locations
- Locations (1)
Cambridge University Hospital NHS Foundation Trust
🇬🇧Cambridge, Cambridgeshire, United Kingdom