Authors:
Lenka Lhotska
1
;
Vaclav Gerla
1
;
Jiri Bukartyk
1
;
Vladimir Krajca
2
and
Svojmil Petranek
2
Affiliations:
1
Gerstner Laboratory, Czech Technical University in Prague, Czech Republic
;
2
University Hospital Bulovka, Czech Republic
Keyword(s):
EEG processing, wavelet transform, feature extraction.
Related
Ontology
Subjects/Areas/Topics:
Applications and Services
;
Artificial Intelligence
;
Biomedical Engineering
;
Biomedical Signal Processing
;
Computational Intelligence
;
Computer Vision, Visualization and Computer Graphics
;
Medical Image Detection, Acquisition, Analysis and Processing
;
Soft Computing
Abstract:
Manual evaluation of long-term EEG recordings is very tedious, time consuming, and subjective process. The aims of automated processing are on one side to ease the work of medical doctors and on the other side to make the evaluation more objective. This paper addresses the problem of computer-assisted sleep staging. It describes ongoing research in this area. The proposed solution comprises several consecutive steps, namely EEG signal pre-processing, feature extraction, feature normalization, and application of decision trees for classification. The work is focused on the feature extraction step that is regarded as the most important one in the classification process.