Solomon Seminar – the RAReFall system: 1st place awarded activity recognition system at the EvAAL 2013 competition

The presentation was about the EvAAL’s 2013 1st place awarded system – RAReFall. It is a real-time activity recognition and fall detection system developed at our department by the Ambient Intelligence group, i.e., Simon Kozina, Hristijan Gjoreski, Mitja Luštrek and Matjaž Gams.

About the 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.

RAReFall activity recognition and fall detection system at the EvAAL competition
Hristijan Gjoreski, Simon Kozina