Patient Monitoring & Fall Detection

The Problem

Patient falls are the most common adverse event in hospitals and care facilities. Traditional fall prevention relies on bed alarms and call buttons — reactive systems that alert after the fall has occurred. Nursing staff cannot continuously observe all patients, and high-risk patients often don't use call buttons. Every fall risks fractures, head injuries, extended hospital stays, and liability.

How Computer Vision Solves It

Computer vision monitors patient rooms from ceiling cameras, detecting pre-fall behaviors — bed exit attempts, unsteady standing, wheelchair transfers — and alerting staff before or during the event. The system works continuously without requiring patient compliance or wearable devices.

The Challenge with Current Solutions

Patient rooms have variable lighting including nighttime low-light conditions. Blankets and medical equipment create occlusion. Privacy is paramount — clinical use requires careful data handling. Different patient populations have different mobility patterns and risk profiles.

What vfrog Brings That's Different

vfrog trains on your facility's specific room layouts and camera positions. Models detect pre-fall behaviors, not just falls. Privacy-preserving processing keeps video data on-premise with no cloud transmission. Risk-level-specific alert thresholds reduce alarm fatigue for nursing staff.

Key Benefits

• Pre-fall detection enabling proactive intervention
• Continuous monitoring without wearable devices
• Reduced fall-related injuries and extended stays
• Privacy-preserving on-premise processing
• Risk-stratified alerting to reduce alarm fatigue
• Fall event documentation for quality improvement