CompletedNot Applicable

Developing a Falls Prediction Tool Using Both Accelerometer and Video Gait Analysis Data in Older Adults

Canada100 participantsStarted 2025-04-15

Plain-language summary

Our group, consisting of academic clinicians and research engineers, seeks to create a database of stability measures (accelerometers, gyroscopes and altitude sensor data) in older adults monitored longitudinally. This Stability Measures (SM) database will allow us to use new machine learning methods to develop and then validate algorithms that predict future falls, allowing for better targeting of vulnerable patients.

Who can participate

Age range65 Years

SexALL

See this in plain English?

AI-rewrites the medical criteria so a patient or caregiver can understand them. Always confirm with the trial site.

Inclusion Criteria: * All subjects must be aged 65 years and older • All subjects must have had at least one fall in the last year and have been referred to the falls clinic (High Risk Subjects) OR have had no falls on the last year and have responded to our newspaper advertisement (Low Risk Subjects) Exclusion Criteria: * Subjects age less than 65 years old

What they're measuring

Classification of accuracy of the algorithm on the validation dataset

Timeframe: 60 min

Trial details

NCT IDNCT04354623

SponsorUniversity of British Columbia

Sponsor typeOTHER

Study typeOBSERVATIONAL

Primary completion2026-04-15

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