Energy based feature extraction for classification of sleep apnea syndrome


SEZGİN N., TAĞLUK M. E.

COMPUTERS IN BIOLOGY AND MEDICINE, cilt.39, ss.1043-1050, 2009 (SCI İndekslerine Giren Dergi) identifier identifier identifier

  • Cilt numarası: 39 Konu: 11
  • Basım Tarihi: 2009
  • Doi Numarası: 10.1016/j.compbiomed.2009.08.005
  • Dergi Adı: COMPUTERS IN BIOLOGY AND MEDICINE
  • Sayfa Sayıları: ss.1043-1050

Özet

In this paper it is aimed to classify sleep apnea syndrome (SAS) by using discrete wavelet transforms (DWT) and an artificial neural network (ANN). The abdominal and thoracic respiration signals are separated into spectral components by using multi-resolution DWT. Then the energy of these spectral components are applied to the inputs of the ANN. The neural network was configured to give three outputs to classify the SAS situation of the subject.