Classification of internal carotid artery Doppler signals using fuzzy discrete hidden Markov model

Authors:
Harun UğUz;Halife Kodaz
Affiliations:
Department of Computer Engineering, Selçuk University, Konya, Turkey;Department of Computer Engineering, Selçuk University, Konya, Turkey
Venue:
Expert Systems with Applications: An International Journal
Year:
2011

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Abstract

We developed a biomedical system based on Discrete Hidden Markov Model (DHMM). The aim of our system is to classify the internal carotid artery Doppler signals. We applied a fuzzy approach to DHMM. Thus we decreased information loss and increased the classification performance. Our system reached 97.38% of classification accuracy with 5 fold cross validation. These results showed that the Fuzzy Discrete Hidden Markov Model (FDHMM) method is effective for classification of internal carotid artery Doppler signals.