Methodologies and Application

Soft Computing

, Volume 17, Issue 9, pp 1659-1671

First online:

Description, analysis, and classification of biomedical signals: a computational intelligence approach

  • Adam GacekAffiliated withInstitute of Medical Technology and Equipment (ITAM) Email author 
  • , Witold PedryczAffiliated withDepartment of Electrical and Computer Engineering, University of AlbertaDepartment of Electrical and Computer Engineering, Faculty of Engineering, King Abdulaziz University

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This study provides a general introduction to the principles, algorithms and practice of computational intelligence (CI) and elaborates on those facets with relation to biomedical signal analysis, especially ECG signals. We discuss the main technologies of computational intelligence (namely, neural networks, fuzzy sets or granular computing, and evolutionary optimization), identify their focal points and stress an overall synergistic character, which ultimately gives rise to the highly symbiotic CI environment. Furthermore, the main advantages and limitations of the CI technologies are discussed. In the sequel, we present CI-oriented constructs in signal modeling, classification, and interpretation. Examples of the CI-based ECG signal processing problems are presented.


Computational intelligence Biomedical signals Neurocomputing Fuzzy sets Information granules Granular computing Interpretation Classification Synergy