A Study on Human Fall Detection Systems: Daily Activity Classification and Sensing Techniques

Abstract

Fall detection for elderly is a major topic as far as assistive technologies are concerned. This is due to the high demand for the products and technologies related to fall detection with the ageing population around the globe. This paper gives a review of previous works on human fall detection devices and a preliminary results from a developing depth sensor based device. The three main approaches used in fall detection devices such as wearable based devices, ambient based devices and vision based devices are identified along with the sensors employed.  The frameworks and algorithms applied in each of the approaches and their uniqueness is also illustrated. After studying the performance and the shortcoming of the available systems a future solution using depth sensor is also proposed with preliminary results.