The scenario
In elder care, falls are a persistent and often unavoidable problem: The majority of people over 65 experience one or more falls each year. Falls in the elderly can often be severe, resulting in functional decline, reduced quality of life and, in severe cases, even death.
From motion detectors to AI-based system
October used motion detectors to track when patients had fallen in their rooms. Although the system gave alerts when clients fell, it could not distinguish between a fall and another movement (e.g. moving around in bed), so it gave many more alerts than staff could respond to.
October began implementing Kepler Vision Technologies‘ AI-based system – Kepler Night Nurse – which detects falls by analysing live camera footage in clients’ rooms and sends alerts to staff when a fall is detected. Kepler Night Nurse enables staff to respond to falls within seconds.
The system also eliminates the vast majority of false alarms. This leaves staff with much more time for other aspects of proactive care.
