AI-Powered Fall Risk Prediction in Nursing Care

Launched by INONU UNIVERSITY · May 30, 2025

Keywords

ClinConnect Summary

This clinical trial is studying a new system that uses advanced technology to predict the risk of falls in patients. The goal is to create a method that can assess fall risk more effectively than traditional methods. By using machine learning and computer vision, this system aims to provide real-time monitoring and personalized evaluations of patients' movements. This could help keep patients safer and reduce the chances of complications from falls in healthcare settings.

To be eligible for this trial, participants need to be 18 years or older, able to read and write in Turkish, and able to walk with or without assistance. Participants will undergo a walking assessment where their movements will be recorded using a camera and a device that tracks their motion. This information will help researchers develop a reliable system that can quickly assess fall risk based on how a person walks. If you or a loved one meet these criteria and are interested in participating, you'll be contributing to important research that could improve patient safety in hospitals and clinics.

Gender

ALL

Eligibility criteria

• Inclusion Criteria:
• • 18 years of age or older
• • Accepting voluntary participation in the study
• • Be able to read and write Turkish
• • Being able to walk with or without support
• Exclusion Criteria:
• • Not being able to speak or understand Turkish adequately
• • Being intubated.
• • To be identified.
• • Being immobile
• • Having a mental disability.