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Vol. 228, Issue 12, December 2018, pp. 79-83




The Novel Fall Detection and Prevention Algorithm for Elderly People

Jong-Ha Lee

Department of Biomedical Engineering, School of Medicine, Keimyung University, Daegu, South Korea

E-mail: segeberg@kmu.ac.kr


Received: 2 May 2018 /Accepted: 1 October 2018 /Published: 31 December 2018

Digital Sensors and Sensor Sysstems


Abstract: Falls are dangerous for the elderly population; therefore, many fall detection systems have been developed. However, previous methods are bulky for elderly people or only use a single sensor to isolate falls from daily living activities, which makes a fall difficult to distinguish. In this paper, we present a cost-effective and easy-to-use portable fall-detection sensor and algorithm. Specifically, to detect human falls, we used a three-axis accelerator and a three-axis gyroscope in a mobile phone. We used the Fourier descriptor-based frequency analysis method to classify both normal and falling status. From the experimental results, the proposed method detects falling status with 96.14 % accuracy.


Keywords: u-health, Fall detection, Wearable device, Mobile phone, Accelerometer, Gyroscope.


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