RAReFall activity recognition and fall detection system at the EvAAL competition

author: Simon Kozina, Department of Intelligent Systems, Jožef Stefan Institute
author: Hristijan Gjoreski, Department of Intelligent Systems, Jožef Stefan Institute
published: Feb. 4, 2014,   recorded: January 2014,   views: 3571


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The talk will present the RAReFall system, which is a real-time activity recognition and fall detection system. It is tuned for robustness and real-time performance by combining human-understandable rules and classifiers trained with machine learning algorithms. The system consists of two wearable accelerometers sewn into elastic sports-wear, placed on the abdomen and the right thigh. The recognition of the user's activities and detection of falls is performed on a laptop using the raw sensors' data acquired through Bluetooth. The system was evaluated at the EvAAL-2013 activity recognition competition and awarded the first place, achieving the score of 83.6%, which was for 14.2 percentage points better than the second-place system. The evaluation was performed in a living lab using several criteria: recognition performance, user-acceptance, recognition delay, system installation complexity and interoperability with other systems.

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Download slides icon Download slides: solomon_gjoreski_kozina_rarefall_01.pdf (2.1 MB)

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