AI Fall Prevention - 24/7 Early Warning Alert
KnowFalls is developing an AI Fall Prevention System (AI-System). It will be available in the first half of 2020. The AI-System interfaces to the KnowFalls and other industry VPOs. The AI-System will automatically identify the location of the bed and the patient, monitor the patient's bed activities 24/7, and generate an early warning of a bed exit attempt. Two alerts, both generating a video and audio alarm, are generated for patient observer confirmation:
- Yellow Alerts - if the patient is undertaking “risky” behavior that precedes a bed exit attempt. Examples include a patient violently shaking bed rails, rapidly throwing-off bed covers, and forcibly pushing off a food tray.
- Red Alerts - if the patient is undertaking a bed exit. Examples include a patient’s leg hanging off the bed and the patient moving over the edge of the bed.
No False Alarms and More Time for Patient Intervention
Saves Patient Observer Time
As compared to other patient monitoring systems, the KnowFalls App does not require patient observers to identify the bed or patient within the camera’s field of view, to designate areas of interest for monitoring or be concerned with background activities. More importantly, the App's underlying artificial intelligence model, enables the system to improve its detection capability. The model learns just as a human learns.
Interfacing to any Virtual Patient Observation Systems
As shown below, the KnowFalls AI-System can be efficiently added to the KnowFalls Patient Observation System or other virtual patient observation systems. The AI-System runs on an separated AI Processor and notifies the Virtual Patient Observer System when an alert condition exists.
Our development of the AI-System is data driven. We have developed and trained the AI Model with diverse data. We would like to work with you in integrating the AI-System into your patient monitoring system and provide you with a robust fall prediction system. If you are interested in evaluating the AI-System call 941.724.9700 or complete the following form.