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Erschienen in:
2012 | OriginalPaper | Buchkapitel
Fuzzy Inference-Based Reliable Fall Detection Using Kinect and Accelerometer
verfasst von : Michal Kepski, Bogdan Kwolek, Ivar Austvoll
Erschienen in: Artificial Intelligence and Soft Computing
Verlag: Springer Berlin Heidelberg
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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.