Literature DB >> 11057403

Application of periodogram and AR spectral analysis to EEG signals.

M Akin1, M K Kiymik.   

Abstract

In this study, in order to analyze the EEG signal, the conventional and modern spectral methods were investigated. Interpretation and performance of these methods were detected for clinical applications. For this purpose EEG data obtained from different persons were processed by PC computer using periodogram and AR model algorithms. Periodogram and AR modeling approaches were compared for their resolution and interpretation performance. It was determined that the AR approach is better for the use in clinical and research areas, because of the clear spectra that are obtained by it.

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Year:  2000        PMID: 11057403     DOI: 10.1023/a:1005553931564

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


  4 in total

1.  Seizure detection of newborn EEG using a model-based approach.

Authors:  M Roessgen; A M Zoubir; B Boashash
Journal:  IEEE Trans Biomed Eng       Date:  1998-06       Impact factor: 4.538

2.  Application of prewhitening to AR spectral estimation of EEG.

Authors:  G E Birch; P D Lawrence; J C Lind; R D Hare
Journal:  IEEE Trans Biomed Eng       Date:  1988-08       Impact factor: 4.538

3.  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

4.  Analysis of rapidly changing EEGs before generalized spike and wave complexes.

Authors:  T Inouye; H Sakamoto; K Shinosaki; S Toi; S Ukai
Journal:  Electroencephalogr Clin Neurophysiol       Date:  1990-09
  4 in total
  14 in total

1.  Comparison of wavelet transform and FFT methods in the analysis of EEG signals.

Authors:  M Akin
Journal:  J Med Syst       Date:  2002-06       Impact factor: 4.460

2.  Detection of carotid artery disease by using Learning Vector Quantization Neural Network.

Authors:  Harun Uğuz
Journal:  J Med Syst       Date:  2010-04-27       Impact factor: 4.460

3.  A biomedical system based on artificial neural network and principal component analysis for diagnosis of the heart valve diseases.

Authors:  Harun Uğuz
Journal:  J Med Syst       Date:  2010-02-26       Impact factor: 4.460

4.  Neural networks with periodogram and autoregressive spectral analysis methods in detection of epileptic seizure.

Authors:  M Kemal Kiymik; Abdulhamit Subasi; H Riza Ozcalik
Journal:  J Med Syst       Date:  2004-12       Impact factor: 4.460

5.  EEG-NIRS based assessment of neurovascular coupling during anodal transcranial direct current stimulation--a stroke case series.

Authors:  Anirban Dutta; Athira Jacob; Shubhajit Roy Chowdhury; Abhijit Das; Michael A Nitsche
Journal:  J Med Syst       Date:  2015-02-17       Impact factor: 4.460

6.  Power spectral density and coherence analysis of Alzheimer's EEG.

Authors:  Ruofan Wang; Jiang Wang; Haitao Yu; Xile Wei; Chen Yang; Bin Deng
Journal:  Cogn Neurodyn       Date:  2014-12-16       Impact factor: 5.082

7.  Real-time brain oscillation detection and phase-locked stimulation using autoregressive spectral estimation and time-series forward prediction.

Authors:  L Leon Chen; Radhika Madhavan; Benjamin I Rapoport; William S Anderson
Journal:  IEEE Trans Biomed Eng       Date:  2011-01-31       Impact factor: 4.538

8.  Comparison of AR and Welch methods in epileptic seizure detection.

Authors:  Ahmet Alkan; M Kemal Kiymik
Journal:  J Med Syst       Date:  2006-12       Impact factor: 4.460

9.  Investigation of EEG abnormalities in the early stage of Parkinson's disease.

Authors:  Chun-Xiao Han; Jiang Wang; Guo-Sheng Yi; Yan-Qiu Che
Journal:  Cogn Neurodyn       Date:  2013-02-10       Impact factor: 5.082

10.  Multiple characteristics analysis of Alzheimer's electroencephalogram by power spectral density and Lempel-Ziv complexity.

Authors:  Xiaokun Liu; Chunlai Zhang; Zheng Ji; Yi Ma; Xiaoming Shang; Qi Zhang; Wencheng Zheng; Xia Li; Jun Gao; Ruofan Wang; Jiang Wang; Haitao Yu
Journal:  Cogn Neurodyn       Date:  2015-11-12       Impact factor: 5.082

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