First KnowFalls Platform Application: Patient Fall Prevention
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Persistent Problem
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Patient & Family Impact
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Total US Cost > $50 Billion
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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.
Through Artificial Intelligence Bed Exit Attempts are Predicted and Nurses Alerted
The KnowFalls Behavior Recognition Platform predicts a patient's bed exit attempt to help caregivers successfully intervene and reduce falls. The Platform via a camera, half the size of an iPhone, captures all room activity. Simultaneously, the Platform's artificial intelligence engine locates the patient's bed, analyzes all patient movements, recognizes room/bed conditions, and determines if a bed exit attempt is in progress. Immediately, an alert and real-time patient video is transmitted to a predesignated caregiver's smart phone and/or a nursing station display.
Expanded Features, FDA Registration & HIPAA Compliance
Additional Analytics
Enables automation of routine tasks like face mask and distancing compliance, and patient wandering detection. 
Scalable
Supports 1000's of cameras within a single or multiple hospitals, and eaily integrates into command centers. |
Adapts to Unit Needs
Addresses specialized unit requirements by rapidly learning new behaviors, such as a catheter pull. 
Compliant
KnowFalls continues to invest in patient privacy and adhering to FDA Medical Device requirements. |
Technology Partners
KnowFalls was launched by experienced healthcare professionals partnering with the support of leading video and articifial intelligence processing partners.
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