Fuzzy inference-based reliable fall detection using kinect and accelerometer

Authors:
Michal Kepski;Bogdan Kwolek;Ivar Austvoll
Affiliations:
Rzeszów University of Technology, Rzeszów, Poland;Rzeszów University of Technology, Rzeszów, Poland;University of Stavanger, Stavanger, Norway
Venue:
ICAISC'12 Proceedings of the 11th international conference on Artificial Intelligence and Soft Computing - Volume Part I
Year:
2012

Citing 1
Cited 1

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BSN '09 Proceedings of the 2009 Sixth International Workshop on Wearable and Implantable Body Sensor Networks

Fall detection on embedded platform using kinect and wireless accelerometer

ICCHP'12 Proceedings of the 13th international conference on Computers Helping People with Special Needs - Volume Part II

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Abstract

Falls are major causes of mortality and morbidity in the elderly. However, prevalent methods only utilize accelerometers or both accelerometers and gyroscopes to separate falls from activities of daily living. This makes it not easy to distinguish real falls from fall-like activities. The existing CCD-camera based solutions require time for installation, camera calibration and are not generally cheap. In this paper we show how to achieve reliable fall detection. The detection is done by a fuzzy inference system using low-cost Kinect and a device consisting of an accelerometer and a gyroscope. The experimental results indicate high accuracy of the detection and effectiveness of the system.