Abstract

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 evaluations. Experimental evaluation shows the effectiveness of the implemented solution, especially analyzing the performances related to the detection of anomalies varying sensing technology.

Autore Pugliese

• Leone Alessandro , Rescio Gabriele , Diraco Giovanni , Siciliano Pietro Aleardo

Tutti gli autori

• Caroppo A.; Diraco G.; Rescio G.; Leone A.; Siciliano P.

Titolo volume/Rivista

Non Disponibile

Anno di pubblicazione

2015

ISSN

Non Disponibile

ISBN

9781479989805

Numero di citazioni Wos

Nessuna citazione

Ultimo Aggiornamento Citazioni

Non Disponibile

Numero di citazioni Scopus

Non Disponibile

Ultimo Aggiornamento Citazioni

Non Disponibile

Settori ERC

Non Disponibile

Codici ASJC

Non Disponibile