MedTrace Logo

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

NCT04354623 · Status: COMPLETED · Type: OBSERVATIONAL · Enrollment: 100

Last updated 2026-05-01

No results posted yet for this study

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.

Conditions

  • Fall Injury Prevention

Interventions

OTHER

A 6-minute walk test

Each subject will perform a 6-minute walk test during which gait assessment will be obtained from the APDM system (Portland, OR). In addition there will be four video cameras (on the front, back and sides) that will measure raw video data for our gait analysis. The camera does not record any facial data (in fact, 'deepfake' software in the system deletes all facial details) and the patient's movements are converted to a 'stick figure' prior to being saved in the system.

Sponsors & Collaborators

  • University of British Columbia

    lead OTHER

Principal Investigators

  • Kenneth Madden, MD · UBC

Eligibility

Min Age
65 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2025-04-15
Primary Completion
2026-04-15
Completion
2026-04-22

Countries

  • Canada

Study Locations

More Related Trials

Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT04354623 on ClinicalTrials.gov