Wearables can be used your young children or elderly persons to monitoring their locations or health, and one use case, especially for old age persons, is to detect falls. However, it’s quite possible they don’t like it and/or not always wear it, so the Center for Eldercare and Technology of the University of Missouri designed a system based on Microsoft Kinect, two webcams, and microphones in order to detect falls, and even predict falls by analyzing gait, i.e. the pattern of movement of the limbs. The picture above shows at least part of the hardware setup with the Kinect, a webcam, and a PC tower doing the processing stored in a cupboard. Fall detection algorithms are relying on the microphone array, Microsoft Kinect depth camera, and a two-webcam system used to extract silhouettes from orthogonal views and construct a 3D voxel model for analysis. Passive gait analysis algorithms are for […]
Sensors Predicting The Future – Elderly Persons Fall Prediction and Detection with Kinect, Webcams and Microphones
