Abstract
Patients falling in hospital and care house is very important issue. Each patient at risk of falling should receive multifaceted clinical and environmental interventions that could reduce the risk. However, it is difficult to predict falling from bed using sensor and video monitoring. Also, most of them are not able to use practically, because system is so large and high costs. We propose new falling analysis system using Intelligent Vision Sensor (IVS). The IVS is a CMOS sensor like as human retina. This sensor is able to protect the privacy of patients using image processing on the CMOS hardware. Also, the algorithm has developed to analyze patient's falling pattern. The test bed system is estimated using our proposed motion analysis algorithm for non-handicapped person. It is verified to predict falling in real time and to be able to predict before the accident.
