Fall detection on embedded platform using kinect and wireless accelerometer

Authors:
Michal Kepski;Bogdan Kwolek
Affiliations:
Rzeszów University of Technology, Rzeszów, Poland;Rzeszów University of Technology, Rzeszów, Poland
Venue:
ICCHP'12 Proceedings of the 13th international conference on Computers Helping People with Special Needs - Volume Part II
Year:
2012

Citing 2
Cited 2

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Abstract

In this paper we demonstrate how to accomplish reliable fall detection on a low-cost embedded platform. The detection is achieved by a fuzzy inference system using Kinect and a wearable motion-sensing device that consists of accelerometer and gyroscope. The foreground objects are detected using depth images obtained by Kinect, which is able to extract such images in a room that is dark to our eyes. The system has been implemented on the PandaBoard ES and runs in real-time. It permits unobtrusive fall detection as well as preserves privacy of the user. The experimental results indicate high effectiveness of fall detection.