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This paper presents a heterogeneous sensor platform for the detection of anomalies in circadian rhythm. Three detectors with different sensing principles are considered: a 3D time-of-flight camera, a MEMS wearable wireless accelerometer and a Ultra-wideband radar. Starting from human postural information obtained by each detector, a simulator of activities and related postures has been designed and implemented within this work. The use of a simulator is motivated by the lack of datasets containing long-term data for the analyzed context. The simulator is able to generate posture sequences calibrated on real experiments performed by each detector involved in the platform. Finally, a reasoner layer infers knowledge by using a suitable activity recognition module. Moreover, with an unsupervised clustering technique, the reasoner is able to detect specific circadian anomalies, thereby providing a tool for clinical …
Publication date: 
18 Jun 2015
Biblio References: 
Pages: 187-192
2015 6th International Workshop on Advances in Sensors and Interfaces (IWASI)