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Remote Monitoring and Analysis of Gait and Falls Within an Elderly Population

NCT03680014 · Status: UNKNOWN · Type: OBSERVATIONAL · Enrollment: 40

Last updated 2018-09-21

No results posted yet for this study

Summary

The investigators aim to do this initial pilot study as an observational prospective cohort study, evaluating elderly patients who have capacity in National Health Service (NHS) rehabilitation and community hospitals. The patients will each be recorded doing simple activities of daily living in two 2 hour sessions using a discrete wireless device. This will generate anonymous data set that can be used to train and refine our machine learning algorithm.

Conditions

  • Accidental Fall
  • Fall
  • Fall Injury
  • Hip Fractures

Interventions

DIAGNOSTIC_TEST

CUSH

Machine learning assisted remote monitoring/ telehealth platform to predict and prevent falls

Sponsors & Collaborators

  • CUSH Health Ltd.

    lead INDUSTRY

Principal Investigators

  • Sam Fosker, BMBS · CUSH Health

  • Kalon Hewage, MBBS BSc · CUSH Health

Eligibility

Min Age
65 Years
Sex
ALL
Healthy Volunteers
Yes

Timeline & Regulatory

Start
2018-09-12
Primary Completion
2018-10-31
Completion
2019-09-30

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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 NCT03680014 on ClinicalTrials.gov