Although the above videos were published in 2012, patient falls remain a major problem. Patient falls occur at a rate of 3-5 per 1000 bed-days and within nursing homes half of the 1.6 million patients fall each year - Patient Safety Network, Agency for Healthcare Quality and Reseach. HHS.  

AI Platform Predicts Falls and Alerts Caregivers

The KnowFalls Behavior Recognition Platform's artificial intelligence engine predicts patient activities to help caregvers make more real-time data informed patient safety decisions.  
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The Platform via a camera, half the size of an iPhone, captures all room activity.  Concurrently,  the artificial intelligence system locates the patient's bed, analyzes all patient activities, recognizes room/bed conditions, and determines the precursor's to a bed exist attempt or a bed exit in progress.  Based on the hospital units best practices, an alert and real-time patient video is generated directly to a predesignated caregiver.. ​

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Expanded Features and FDA & HIPAA Compliance 

Additional Analytics
Enables automation of routine tasks like face mask and distancing compliance and patient wandering detection.   

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Scalable
Supports 1000's of cameras within a single or multiple hospitals, and intergration with command centers.

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Adapts to Unit Needs
Addresses specialized unit requirements by rapidly learning new behaviors, such as catherter pull.
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Compliant 
​KnowFalls has and continues to invest in patient privacy and adhering to FDA Medical Device requirements.

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Technology Partners

KnowFalls was launched with the support of experienced healthcare professionals and leading AI, video acquisition and processing companies.  Some are..