Classification of aorta insufficiency and stenosis using neuro-fuzzy system

BARIŞÇI N., Topal E., Hardalaç F., GÜLER İ.

Journal of Medical Systems, cilt.29, sa.2, ss.155-165, 2005 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 29 Sayı: 2
  • Basım Tarihi: 2005
  • Doi Numarası: 10.1007/s10916-005-3003-9
  • Dergi Adı: Journal of Medical Systems
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.155-165
  • Gazi Üniversitesi Adresli: Evet

Özet

Cardiac Doppler signals recorded from aorta valve of 60 patients were transferred to a personal computer by using a 16 bit sound card. The fast Fourier transform (FFT) method was applied to the recorded signal from each patient. Since FFT method inherently cannot offer a good spectral resolution at jet blood flows such as cardiac Doppler signals, it sometimes causes wrong interpretation. In order to do a good interpretation and rapid diagnosis, cardiac Doppler blood flow signals were statistically arranged and then classified using neuro-fuzzy system. The NEFCLASS model, which is used to create a fuzzy classification system from data, was used. The classification results show that neuro-fuzzy system offers best results in the case of diagnosis. © 2005 Springer Science+Business Media, Inc.