A Fuzzy Approach of the Kohonen's Maps Applied to the Analysis of Biomedical Signals

  • Authors:

  • Andrilene Maciel;Luis Coradine;Roberta Vieira;Manoel Lima

  • Affiliations:

  • Computer Institute, Federal University of Alagoas, Tabuleiro dos Martins, Maceió, Brazil Postal Code 57.072-970;Computer Institute, Federal University of Alagoas, Tabuleiro dos Martins, Maceió, Brazil Postal Code 57.072-970;Computer Institute, Federal University of Alagoas, Tabuleiro dos Martins, Maceió, Brazil Postal Code 57.072-970;Informatics Center, Federal University of Pernambuco, Recife, Brasil Postal Code 15.064 --- 91.501-970

  • Venue:
  • HAIS '09 Proceedings of the 4th International Conference on Hybrid Artificial Intelligence Systems
  • Year:
  • 2009

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Abstract

Self-organizing maps have been used successfully in pattern classification problems related to many areas of knowledge and also applied as a tool for statistical multivariate data analysis. Data classification via self-organizing maps deals specifically with relations between objects, meaning that there are limitations to define class limits when an object belonging to a particular class "migrates" to another one. To address this issue, a solution involving self-organizing maps and fuzzy logic is proposed with the objective of generating a neighborhood between these classes. The developed system receives the network output and automatically generates self-organizing maps. This unified vision of the model is used in the analyzing biomedical signals in diabetic patients for monitoring blood glucose stage. Early diagnosis and glucose signals monitoring can prevent or delay the initiation and development of clinical complications related to diabetes.