부산대학교 도서관

Falls can be one of the most damaging events that elders may experience in their lives, especially when they live alone. The impact of a fall can vary from minor bruises, to life altering fractures and even become fatal. The purpose of this study is to establish a novel non-contact radar method of detecting an elderly fall when occurred in home staying. The novelty of the proposed detection technique is the exploitation of a 1D effective acceleration derived from Short Time Fourier Transform (STFT). This technique was tested utilizing a 2.45 GHz Continuous Wave (CW) Radar implemented with a Software Defined Radio (SDR) and low-cost, off-the-shelf components. Herein, we present test results that classify incidents as either falls or non-falls in line-of-sight cases. Firstly, the results are compared with the corresponding values measured with a commercial marker-based optoelectronic motion capture multi-camera system (VICON) showing high similarity. Furthermore, real-time scenarios were conducted to estimate the accuracy and the number of false alarms of the proposed method. The proposed algorithm is proved capable of exploiting the Power Burst Curve (PBC) as a preliminary factor to yield an efficient fall incident classifier based on the effective acceleration, while minimizing the required processing resources.