A fall detection system based on infrared array sensors with tracking capability for the elderly at home

Abstract

In this paper, a low resolution privacy preserved infrared array sensor is adopted for the applications of the elderly tracking and fall detection. The sensor is composed of a 16 × 4 thermopile array with the corresponding 60° × 16.4° field of view. Each pixel or thermopile element of infrared sensor contains the temperature value. Two infrared sensors are attached to the wall at different places in our system for capturing the three dimensional image information. The foreground of human body is determined by subtracting the image with the background model using the temperature difference characteristic. Using the foreground temperature, the angle of arrival (AOA) from each sensor is obtained. The location is estimated by the AOA based positioning algorithm. The estimated position is passed to the regression model to reduce the positioning error. As a result, the mean error of our tracking algorithm is 13.39 cm. On the other hand, the fall detection algorithm is implemented by extracting the features from the falling action. Two sensors capture the action at the same time. The sensor with larger foreground region is chosen for the feature extraction process. The extracted features are applied to the k-nearest neighbor (k-NN) classification model for the fall detection. In experiment, 80 fall actions and 80 normal actions are collected. Finally, 95.25% sensitivity, 90.75% specificity and 93% accuracy are achieved.