Clinical Trials Directory

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UnknownNCT03685240

Fall Detection and Prevention for Memory Care Through Real-time Artificial Intelligence Applied to Video

Fall Detection and Prevention for Memory Care Through Real-time Artificial Intelligence Applied to Video: A Randomized Control Trial

Status
Unknown
Phase
N/A
Study type
Interventional
Enrollment
460 (estimated)
Sponsor
SafelyYou · Industry
Sex
All
Age
18 Years
Healthy volunteers
Accepted

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.

Detailed description

This process enables staff to know about falls without requiring residents wear a device and to see how falls occur for residents that cannot advocate for themselves while still protecting resident privacy by only uploading video when safety critical events are detected. Seeing how the resident went to the ground (1) prevents the need for emergency room visits when residents intentionally moved to the ground without risk and (2) allows the care team to determine what caused an event like a fall and what changes can be made to reduce risk. PRELIMINARY EVIDENCE. The proposed study follows a series of pilots. In pilot 1, we showed the technical feasibility of detecting falls from video with 200 falls acted out by healthy subjects. In pilot 2, in a 40-resident facility, we demonstrated the acceptance of privacy-safety tradeoffs and showed a reduction of total facility falls by 80% by providing the system for 10 repeat fallers. In pilot 3, we addressed repeatability of fall reduction in a cohort of 87 residents with ADRD in 11 facilities of three partner networks. In pilot 4 (NIH SBIR Phase I), we demonstrated that falls can be detected reliably in real-time within the partner facilities. We detected 93% of the falls; reduced the time on the ground by 42%; showed that when video was available, the likelihood of EMS visit was reduced by 50%; and reduced total facility falls by 38%.

Conditions

Interventions

TypeNameDescription
BEHAVIORALSafelyYou Fall Prevention SystemTechnology + Quality Assurance Services Provided by SafelyYou

Timeline

Start date
2023-10-31
Primary completion
2023-12-31
Completion
2023-12-31
First posted
2018-09-26
Last updated
2022-05-09

Locations

1 site across 1 country: United States

Source: ClinicalTrials.gov record NCT03685240. Inclusion in this directory is not an endorsement.