Fall Detection and Prevention for Memory Care Through Real-time Artificial Intelligence Applied to Video
1 other identifier
interventional
460
1 country
1
Brief Summary
The purpose of the research is to study a new safety monitoring system developed by SafelyYou to help care for a loved one with dementia. The goal is to provide better support for unwitnessed falls. The SafelyYou system is based on AI-enabled cameras which detect fall related events and upload video only when these events are detected. The addition of a Human in the Loop (HIL) will alert the facility staff when an event is detected by the system.
Trial Health
Trial Health Score
Automated assessment based on enrollment pace, timeline, and geographic reach
participants targeted
Target at P75+ for not_applicable
Started Oct 2023
Shorter than P25 for not_applicable
1 active site
Health score is calculated from publicly available data and should be used for screening purposes only.
Trial Relationships
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Study Timeline
Key milestones and dates
First Submitted
Initial submission to the registry
September 19, 2018
CompletedFirst Posted
Study publicly available on registry
September 26, 2018
CompletedStudy Start
First participant enrolled
October 31, 2023
CompletedPrimary Completion
Last participant's last visit for primary outcome
December 31, 2023
CompletedStudy Completion
Last participant's last visit for all outcomes
December 31, 2023
CompletedMay 9, 2022
May 1, 2022
2 months
September 19, 2018
May 5, 2022
Conditions
Outcome Measures
Primary Outcomes (3)
Enrollment rate
Detection of falls will be performed with blurred video, hence with increased privacy. Expected outcome will be the change in enrollment rate compared to previous feasibility studies (i.e. impacted rate of positive responses to recruitment efforts within facilities).
Data on enrollment will be recorded during recruitment in year 1 and assessed at the end of year 1
Fall rate due to sit to stand transition detection
Care staff will be alerted as soon as the transition is detected (intervention of the front line staff). This may produce an immediate reduction in falls due to this type of transition.
Data will be collected during year 1 and assessed at the end of year 1.
Fall rate due to gait change detection
As the system learns to may produce an immediate impact on the fall rate by intervention of the front-line staff when the change is detected.
Data will be collected through year 1 and assessed at the end of year 1.
Study Arms (2)
Intervention
EXPERIMENTALAI-enabled camera fall detection with Human-in-the-Loop (HIP) review
Control
NO INTERVENTIONNo camera detection
Interventions
Technology + Quality Assurance Services Provided by SafelyYou
Eligibility Criteria
You may not qualify if:
- \- 18 years old or younger
Contact the study team to confirm eligibility.
Sponsors & Collaborators
- SafelyYoulead
- National Institute on Aging (NIA)collaborator
Study Sites (1)
SafelyYou
San Francisco, California, 94107, United States
MeSH Terms
Conditions
Condition Hierarchy (Ancestors)
Central Study Contacts
Study Design
- Study Type
- interventional
- Phase
- not applicable
- Allocation
- RANDOMIZED
- Masking
- DOUBLE
- Who Masked
- PARTICIPANT, CARE PROVIDER
- Purpose
- SUPPORTIVE CARE
- Intervention Model
- PARALLEL
- Sponsor Type
- INDUSTRY
- Responsible Party
- SPONSOR
Study Record Dates
First Submitted
September 19, 2018
First Posted
September 26, 2018
Study Start
October 31, 2023
Primary Completion
December 31, 2023
Study Completion
December 31, 2023
Last Updated
May 9, 2022
Record last verified: 2022-05
Data Sharing
- IPD Sharing
- Will not share