Comparison of FFT and AR techniques for scalp EEG analysis

Rosniwati Ghafar, Aini Hussain, Salina Abdul Samad, N. M. Tahir

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)

Abstract

Scalp electroencephalogram (EEG) with bipolar montage is used in most infirmaries for monitoring epilepsy. However, scalp EEG is unpopular as compared to IEEG (intra-cranial EEG) in the research field. Most researchers used IEEG and scalp EEG with unipolar montage. Bipolar montage is also rarely used in the research in contrast to unipolar montage. The main aim of this paper is to investigate and determine a suitable method for processing EEG data using bipolar montage directly from the hospital archive. Two well-known methods namely, the Fast Fourier Transform (FFT) and the Autoregressive (AR) will be analyzed and compared based on their power spectrums. Results obtained based on monitored frequencies showed that the AR method is better than FFT in delineating the epilepsy region which can be visually observed and recognizable.

Original languageEnglish
Title of host publicationIFMBE Proceedings
Pages158-161
Number of pages4
Volume21 IFMBE
Edition1
DOIs
Publication statusPublished - 2008
Event4th Kuala Lumpur International Conference on Biomedical Engineering 2008, Biomed 2008 - Kuala Lumpur
Duration: 25 Jun 200828 Jun 2008

Other

Other4th Kuala Lumpur International Conference on Biomedical Engineering 2008, Biomed 2008
CityKuala Lumpur
Period25/6/0828/6/08

Fingerprint

Electroencephalography
Fast Fourier transforms
Power spectrum
Monitoring
Processing

Keywords

  • Autoregressive
  • Electroencephalogram
  • Fast Fourier Transform

ASJC Scopus subject areas

  • Biomedical Engineering
  • Bioengineering

Cite this

Ghafar, R., Hussain, A., Abdul Samad, S., & Tahir, N. M. (2008). Comparison of FFT and AR techniques for scalp EEG analysis. In IFMBE Proceedings (1 ed., Vol. 21 IFMBE, pp. 158-161) https://doi.org/10.1007/978-3-540-69139-6-43

Comparison of FFT and AR techniques for scalp EEG analysis. / Ghafar, Rosniwati; Hussain, Aini; Abdul Samad, Salina; Tahir, N. M.

IFMBE Proceedings. Vol. 21 IFMBE 1. ed. 2008. p. 158-161.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Ghafar, R, Hussain, A, Abdul Samad, S & Tahir, NM 2008, Comparison of FFT and AR techniques for scalp EEG analysis. in IFMBE Proceedings. 1 edn, vol. 21 IFMBE, pp. 158-161, 4th Kuala Lumpur International Conference on Biomedical Engineering 2008, Biomed 2008, Kuala Lumpur, 25/6/08. https://doi.org/10.1007/978-3-540-69139-6-43
Ghafar, Rosniwati ; Hussain, Aini ; Abdul Samad, Salina ; Tahir, N. M. / Comparison of FFT and AR techniques for scalp EEG analysis. IFMBE Proceedings. Vol. 21 IFMBE 1. ed. 2008. pp. 158-161
@inproceedings{9b6c5e6dee23481c9359e54f37e9b217,
title = "Comparison of FFT and AR techniques for scalp EEG analysis",
abstract = "Scalp electroencephalogram (EEG) with bipolar montage is used in most infirmaries for monitoring epilepsy. However, scalp EEG is unpopular as compared to IEEG (intra-cranial EEG) in the research field. Most researchers used IEEG and scalp EEG with unipolar montage. Bipolar montage is also rarely used in the research in contrast to unipolar montage. The main aim of this paper is to investigate and determine a suitable method for processing EEG data using bipolar montage directly from the hospital archive. Two well-known methods namely, the Fast Fourier Transform (FFT) and the Autoregressive (AR) will be analyzed and compared based on their power spectrums. Results obtained based on monitored frequencies showed that the AR method is better than FFT in delineating the epilepsy region which can be visually observed and recognizable.",
keywords = "Autoregressive, Electroencephalogram, Fast Fourier Transform",
author = "Rosniwati Ghafar and Aini Hussain and {Abdul Samad}, Salina and Tahir, {N. M.}",
year = "2008",
doi = "10.1007/978-3-540-69139-6-43",
language = "English",
isbn = "9783540691389",
volume = "21 IFMBE",
pages = "158--161",
booktitle = "IFMBE Proceedings",
edition = "1",

}

TY - GEN

T1 - Comparison of FFT and AR techniques for scalp EEG analysis

AU - Ghafar, Rosniwati

AU - Hussain, Aini

AU - Abdul Samad, Salina

AU - Tahir, N. M.

PY - 2008

Y1 - 2008

N2 - Scalp electroencephalogram (EEG) with bipolar montage is used in most infirmaries for monitoring epilepsy. However, scalp EEG is unpopular as compared to IEEG (intra-cranial EEG) in the research field. Most researchers used IEEG and scalp EEG with unipolar montage. Bipolar montage is also rarely used in the research in contrast to unipolar montage. The main aim of this paper is to investigate and determine a suitable method for processing EEG data using bipolar montage directly from the hospital archive. Two well-known methods namely, the Fast Fourier Transform (FFT) and the Autoregressive (AR) will be analyzed and compared based on their power spectrums. Results obtained based on monitored frequencies showed that the AR method is better than FFT in delineating the epilepsy region which can be visually observed and recognizable.

AB - Scalp electroencephalogram (EEG) with bipolar montage is used in most infirmaries for monitoring epilepsy. However, scalp EEG is unpopular as compared to IEEG (intra-cranial EEG) in the research field. Most researchers used IEEG and scalp EEG with unipolar montage. Bipolar montage is also rarely used in the research in contrast to unipolar montage. The main aim of this paper is to investigate and determine a suitable method for processing EEG data using bipolar montage directly from the hospital archive. Two well-known methods namely, the Fast Fourier Transform (FFT) and the Autoregressive (AR) will be analyzed and compared based on their power spectrums. Results obtained based on monitored frequencies showed that the AR method is better than FFT in delineating the epilepsy region which can be visually observed and recognizable.

KW - Autoregressive

KW - Electroencephalogram

KW - Fast Fourier Transform

UR - http://www.scopus.com/inward/record.url?scp=78349267490&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=78349267490&partnerID=8YFLogxK

U2 - 10.1007/978-3-540-69139-6-43

DO - 10.1007/978-3-540-69139-6-43

M3 - Conference contribution

SN - 9783540691389

VL - 21 IFMBE

SP - 158

EP - 161

BT - IFMBE Proceedings

ER -