Author/Authors :
Rabbani, Hossein Biomedical Engineering Department - Medical Image and Signal Processing Research Center, Isfahan University of Medical Sciences , Mahjoob, Mohammad Parsa School of Medicine - Shahid Beheshti University of Medical Sciences, Tehran , Farahabadi, Eiman Department, Medical Image and Signal Processing Research Center, Isfahan University of Medical Sciences, Isfahan , Farahabadi, Amin Department, Medical Image and Signal Processing Research Center, Isfahan University of Medical Sciences, Isfahan , Mehri Dehnavi, Alireza Biomedical Engineering Department, Medical Image and Signal Processing Research Center, Isfahan University of Medical Sciences
Abstract :
BACKGROUND: Ischemic heart disease is one of the common fatal diseases in advanced countries. Because signal perturbation
in healthy people is less than signal perturbation in patients, entropy measure can be used as an appropriate
feature for ischemia detection.
METHODS: Four entropy-based methods comprising of using electrocardiogram (ECG) signal directly, wavelet subbands
of ECG signals, extracted ST segments and reconstructed signal from time-frequency feature of ST segments in
wavelet domain were investigated to distinguish between ECG signal of healthy individuals and patients. We used exercise
treadmill test as a gold standard, with a sample of 40 patients who had ischemic signs based on initial diagnosis of
medical practitioner
