Fall Guard: Computer Vision Based Fall Detection

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The World Health Organization (WHO) reported that the yearly occurrence of falls in people aged 65 and above is projected to range from 28% to 35%. Over 50% of those who sustain injuries exhibit a significant fatality rate within six months following the fall. Proactive fall detection isn’t just a clinical need, but rather a strategic imperative in today’s care delivery environment.
It was found that real‑time video‑based monitoring reduced residents’ time on the floor by an average of 29.6 minutes, while advanced sensor algorithms cut false alarms by nearly 50%. Fall Guard enables optimal resource allocation, lower liability, and greater confidence for both staff and residents, making it an essential for modern care providers

All-in-One Solution for Fall Detection & Prevention Using Computer Vision

Real‑Time Fall Detection & Alert No More Delays in Care

Advanced Dashboard & Reporting No More Data Patient Reporting and Data discomment

Comprehensive Event Logs & Video Playback

Secure, Role‑Based Access

Seamless API & Third‑Party Integrations

Continuous Learning & Model Updates

Fall Guard Across the Care Continuum

Disability Support Centers

Fall Guard helps reduce fall risks by detecting critical movements in real-time, offering dependable support for individuals with physical limitations.

Post-Surgical Recovery

Hospitals can rely on Fall Guard to monitor patients under mobility restrictions, ensuring timely alerts for unauthorized movement and minimizing post-op complications.

Disability Support Centers

Fall Guard helps reduce fall risks by detecting critical movements in real-time, offering dependable support for individuals with physical limitations.

Home-Based Care

With remote monitoring and instant alerts, Fall Guard supports independent living at home while keeping caregivers informed and ready to respond.

Precise Motion Tracking to Prevent Falls

Fall Guard uses AI fall detection to monitor motion and trigger real-time fall detection alarms. An SOS pop-up appears with location and timestamp.This fall detection app minimizes false alerts using accurate fall detection sensors and only notifies staff when a real event occurs. Below is a list of the notifications that can be sent. These notifications can be customized as per the requirements of your care facility.

Patient Down

Fall Guard detects within 10 seconds if a patient falls.

Going into the room

Fall Guard detects when the patient enters the room.

Sitting on the edge of the bed

Computer vision detects when the patient sits on the edge of the bed.

In bathroom

Tracks when patients go to the bathroom and sends a message if they stay there too long for timely hard fall detection.

In bed

Fall Guard captures a patient who is in bed, regardless of where the bed is in the room.

Sitting on the floor

Computer Vision detects when a patient is on the floor.

Out of bed

Indicates when the patient is out of bed but still in the room.

Lying position

Our fall detection software detects how long someone lies on their left side, right side, or back.

Out of the room

Smart tracking detects when the patient leaves the room.

Uniform detection

Fall Guard detects when someone on staff wearing a uniform is in the room.

Why Folio3 Digital Health's Fall Detection Solution

We’re offering fall detection solutions designed to bring advanced detection and monitoring to healthcare settings. Here’s why healthcare professionals trust Fall Guard for medical alert fall detection and hospital injury prevention:

Key Benefits of Fall Guard's AI Fall Detection Capabilities

Fall Guard goes beyond traditional motion sensors by using computer vision enhanced with artificial intelligence. These AI capabilities improve accuracy, adaptability, and proactive care.

Pose Estimation & Movement Recognition

The system uses AI models trained on real-world fall scenarios to distinguish between normal activities and high-risk movements like stumbling, collapsing, or sudden drops.

Adaptive Learning

Fall Guard continuously re-trains itself using anonymized data collected across care environments. This helps our system to improve detection accuracy over time, even in changing room layouts and lighting conditions.

Reduced False Alarms

AI-driven algorithms filter out non-fall activities, like sitting abruptly or dropping objects, resulting in fewer disruptions and no false alarms for caregivers.

Early Risk Prediction

Fall Guard learns from previous fall events to predict high-risk behavior patterns, giving staff the chance to intervene before an accident happens.

Visual Intelligence

AI helps the system track body posture with precision like lying down, slumping, crawling. Enabling faster and more accurate alerts that are specific to the situation.

Django

PostgreSQL

Flutter

Reddis

Tensorflow

OpenCv

MediaPipe

S3

AWS EC2

Getting Started with Fall Guard for Your Facility

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