Authors:
Miroslav Bursa
;
Michal Huptych
and
Lenka Lhotska
Affiliation:
Czech Technical University in Prague, Czech Republic
Keyword(s):
Electrocardiogram Signal Processing, Evolutionary Algorithm, Ant Colony Optimization, Electroencephalogram Processing, Biological Signal Processing.
Related
Ontology
Subjects/Areas/Topics:
Applications and Services
;
Biomedical Engineering
;
Biomedical Signal Processing
;
Computer Vision, Visualization and Computer Graphics
;
Evolutionary Systems
;
Medical Image Detection, Acquisition, Analysis and Processing
Abstract:
Nature inspired metaheuristics have interesting stochastic properties which make them suitable for use in data mining, data clustering and other application areas, because they often produce more robust solutions. This paper presents an application of clustering method inspired by the behavior of real ants in the nature to biomedical signal processing. The main aim of our study was to design and develop a combination of feature extraction and classification methods for automatic recognition of significant structure in biological signal recordings. The method targets the speed-up and the increase in objectivity of identification of important classes and may be used for online classification, so it can be used as a hint in the expert classification process. We have obtained significant results in electrocardiogram and electroencephalogram recordings, which justify the use of such kind of methods.