An attention monitoring system for high demanding operational tasks

Author

Apolloni, Bruno ; Malchiodi, Dario ; Mesiano, Cristian

Author_Institution

Dipt. di Sci. dell´´Informazione, Universita degli Studi di Milano, Italy

fYear

2004

fDate

21-22 July 2004

Firstpage

23

Lastpage

29

Abstract

We infer symbolic rules for deciding the awareness state of a driver on the basis of physiological signals traced on his body through noninvasive techniques. We use a standard device for collecting signals and a three-level procedure for: 1) extracting features from them, 2) computing Boolean independent components of the features acting as propositional variables, and 3) inferring Boolean normal forms on these variables deciding the driver awareness.

Keywords

Boolean functions; feature extraction; inference mechanisms; medical signal detection; medical signal processing; psychology; ubiquitous computing; Boolean independent components; Boolean normal form inference; attention monitoring system; awareness detector; biosignal-driven man-machine interface; driver awareness state; driving monitoring; feature extraction; noninvasive techniques; pervasive computing; physiological signal tracing; propositional variables; signal collection; subsymbolic-symbolic learning; symbolic rule inference; Biology computing; Biomedical computing; Biomedical monitoring; Computerized monitoring; Detectors; Feature extraction; Hardware; Inference algorithms; Pervasive computing; Quantum computing;

fLanguage

English

Publisher

ieee

Conference_Titel

Computational Intelligence for Homeland Security and Personal Safety, 2004. CIHSPS 2004. Proceedings of the 2004 IEEE International Conference on

Print_ISBN

0-7803-8381-8

Type

conf

DOI

10.1109/CIHSPS.2004.1360202

Filename

1360202