Literature DB >> 12617354

Determination of coronary failure with the application of FFT and AR methods.

Selami Serhatlioğlu1, Oktay Burma, Firat Hardalaç, Inan Güler.   

Abstract

In this study, Doppler signals recorded from the output of carotid artery of 30 patients were transferred to a personal computer (PC) by using a 16-bit sound card. Doppler difference frequencies were recorded from each of the patients, and then analyzed using fast Fourier transform (FFT) and least squares autoregressive (AR) methods to obtain their sonograms. These sonograms are then used to compare with the applied methods in terms of medical evaluation.

Entities:  

Mesh：

Year:  2003        PMID： 12617354     DOI： 10.1023/a:1021856709947

Source DB:  PubMed          Journal:  J Med Syst        ISSN： 0148-5598            Impact factor:   4.460


  5 in total

1.  Determination of aorta failure with the application of FFT, AR and wavelet methods to Doppler technique.

Authors:  I Güler; F Hardalaç; S Müldür
Journal:  Comput Biol Med       Date:  2001-07       Impact factor: 4.589

2.  A real-time autoregressive spectrum analyzer for Doppler ultrasound signals.

Authors:  F S Schlindwein; D H Evans
Journal:  Ultrasound Med Biol       Date:  1989       Impact factor: 2.998

3.  Modern spectral analysis techniques for blood flow velocity and spectral measurements with pulsed Doppler ultrasound.

Authors:  J Y David; S A Jones; D P Giddens
Journal:  IEEE Trans Biomed Eng       Date:  1991-06       Impact factor: 4.538

4.  Comparison of FFT- and AR-based sonogram outputs of 20 MHz pulsed Doppler data in real time.

Authors:  N F Güler; M K Kiymik; I Güler
Journal:  Comput Biol Med       Date:  1995-07       Impact factor: 4.589

5.  Autoregressive-based sonogram outputs of 20 MHz pulsed Doppler data.

Authors:  N F Güler; M K Kiymik; I Güler
Journal:  Med Prog Technol       Date:  1995-05
  5 in total
  2 in total

1.  Prediction of minor head injured patients using logistic regression and MLP neural network.

Authors:  Fatih S Erol; Hadi Uysal; Uçman Ergün; Necaattin Barişçi; Selami Serhathoğlu; Firat Hardalaç
Journal:  J Med Syst       Date:  2005-06       Impact factor: 4.460

2.  Classification of MCA stenosis in diabetes by MLP and RBF neural network.

Authors:  Uyman Ergün; Necaattin Barýpçý; Ahmet Tevfik Ozan; Selami Serhatlýoğlu; Erkin Oğur; Firat Hardalaç; Inan Güler
Journal:  J Med Syst       Date:  2004-10       Impact factor: 4.460
  2 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.