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2018 IEEE International Conference on Pervasive Computing and Communications (PerCom) (2018)
Athens, Greece
March 19, 2018 to March 23, 2018
ISSN: 2474-249X
ISBN: 978-1-5386-3225-3
pp: 1-10
Christian Krupitzer , Chair of Information Systems II, University of Mannheim, Germany
Timo Sztyler , Data and Web Science Group, University of Mannheim, Germany
Janick Edinger , Chair of Information Systems II, University of Mannheim, Germany
Martin Breitbach , Chair of Information Systems II, University of Mannheim, Germany
Heiner Stuckenschmidt , Data and Web Science Group, University of Mannheim, Germany
Christian Becker , Chair of Information Systems II, University of Mannheim, Germany
ABSTRACT
Ambient Assisted Living using mobile device sensors is an active area of research in pervasive computing. Multiple approaches have shown that wearable sensors perform very well and distinguish falls reliably from Activities of Daily Living. However, these systems are tested in a controlled environment and are optimized for a given set of sensor types, sensor positions, and subjects. In this work, we propose a self-adaptive pervasive fall detection approach that is robust to the heterogeneity of real life situations. Therefore, we combine sensor data of four publicly available datasets, covering about 100 subjects, 5 devices, and 3 sensor placements. In a comprehensive evaluation, we show that our system is not only robust regarding the different dimensions of heterogeneity, but also adapts autonomously to spontaneous changes in the sensor’s position at runtime.
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CITATION

C. Krupitzer, T. Sztyler, J. Edinger, M. Breitbach, H. Stuckenschmidt and C. Becker, "Hips Do Lie! A Position-Aware Mobile Fall Detection System," 2018 IEEE International Conference on Pervasive Computing and Communications (PerCom)(PERCOM), Athens, Greece, 2018, pp. 1-10.
doi:10.1109/PERCOM.2018.8444583
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