Human Distress Sound Analysis and Characterization Using Advanced Classification Techniques

Authors:
Charalampos Doukas;Ilias Maglogiannis
Affiliations:
Dep. of Information & Communication Systems Engineering, University of the Aegean, Samos, Greece;Dep. of Information & Communication Systems Engineering, University of the Aegean, Samos, Greece and Dep. of Biomedical Informatics, University of Central Greece, Lamia, Greece
Venue:
SETN '08 Proceedings of the 5th Hellenic conference on Artificial Intelligence: Theories, Models and Applications
Year:
2008

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Abstract

The analysis of sounds generated in close proximity of a subject can often indicate emergency events like falls, pain and other distress situations. This paper presents a system for collecting and analyzing sounds and speech expressions utilizing on-body sensors and advanced classification techniques for emergency events detection. A variety of popular classification and meta-classification algorithms have been evaluated and the corresponding results are presented.