Automatic estimation of the optimal AR order for epilepsy analysis using EEG signals

Evangelia Pippa; Iosif Mporas; Vasileios Megalooikonomou

doi:10.1109/BIBE.2015.7367709

Automatic estimation of the optimal AR order for epilepsy analysis using EEG signals

Evangelia Pippa, Iosif Mporas, Vasileios Megalooikonomou

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

5 Citations (Scopus)

Abstract

In this paper, we propose a computationally efficient method to estimate the optimal order of the autoregressive (AR) modeling of electroencephalographic (EEG) signals in order to use the AR coefficients as features for the analysis of EEG signals and the automatic detection of epileptic seizures. The estimation of the optimal AR-order is made using regression analysis of statistical features extracted from the samples of the EEG signals. The proposed method was evaluated in both background and ictal EEG segments using recordings from 10 epileptic patients. The experimental evaluation showed that the mean absolute error of the estimated optimal AR order is approximately 4 units.

Original language	English
Title of host publication	2015 IEEE 15th International Conference on Bioinformatics and Bioengineering, BIBE 2015
Publisher	Institute of Electrical and Electronics Engineers (IEEE)
ISBN (Electronic)	9781467379830
DOIs	https://doi.org/10.1109/BIBE.2015.7367709
Publication status	Published - 28 Dec 2015
Externally published	Yes
Event	15th IEEE International Conference on Bioinformatics and Bioengineering, BIBE 2015 - Belgrade, Serbia Duration: 2 Nov 2015 → 4 Nov 2015

Publication series

Name	2015 IEEE 15th International Conference on Bioinformatics and Bioengineering, BIBE 2015

Conference

Conference	15th IEEE International Conference on Bioinformatics and Bioengineering, BIBE 2015
Country/Territory	Serbia
City	Belgrade
Period	2/11/15 → 4/11/15

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10.1109/BIBE.2015.7367709

Cite this

Pippa, E., Mporas, I., & Megalooikonomou, V. (2015). Automatic estimation of the optimal AR order for epilepsy analysis using EEG signals. In 2015 IEEE 15th International Conference on Bioinformatics and Bioengineering, BIBE 2015 Article 7367709 (2015 IEEE 15th International Conference on Bioinformatics and Bioengineering, BIBE 2015). Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/BIBE.2015.7367709

Pippa, Evangelia ; Mporas, Iosif ; Megalooikonomou, Vasileios. / Automatic estimation of the optimal AR order for epilepsy analysis using EEG signals. 2015 IEEE 15th International Conference on Bioinformatics and Bioengineering, BIBE 2015. Institute of Electrical and Electronics Engineers (IEEE), 2015. (2015 IEEE 15th International Conference on Bioinformatics and Bioengineering, BIBE 2015).

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title = "Automatic estimation of the optimal AR order for epilepsy analysis using EEG signals",

abstract = "In this paper, we propose a computationally efficient method to estimate the optimal order of the autoregressive (AR) modeling of electroencephalographic (EEG) signals in order to use the AR coefficients as features for the analysis of EEG signals and the automatic detection of epileptic seizures. The estimation of the optimal AR-order is made using regression analysis of statistical features extracted from the samples of the EEG signals. The proposed method was evaluated in both background and ictal EEG segments using recordings from 10 epileptic patients. The experimental evaluation showed that the mean absolute error of the estimated optimal AR order is approximately 4 units.",

author = "Evangelia Pippa and Iosif Mporas and Vasileios Megalooikonomou",

year = "2015",

month = dec,

day = "28",

doi = "10.1109/BIBE.2015.7367709",

language = "English",

series = "2015 IEEE 15th International Conference on Bioinformatics and Bioengineering, BIBE 2015",

publisher = "Institute of Electrical and Electronics Engineers (IEEE)",

booktitle = "2015 IEEE 15th International Conference on Bioinformatics and Bioengineering, BIBE 2015",

address = "United States",

note = "15th IEEE International Conference on Bioinformatics and Bioengineering, BIBE 2015 ; Conference date: 02-11-2015 Through 04-11-2015",

}

Pippa, E, Mporas, I & Megalooikonomou, V 2015, Automatic estimation of the optimal AR order for epilepsy analysis using EEG signals. in 2015 IEEE 15th International Conference on Bioinformatics and Bioengineering, BIBE 2015., 7367709, 2015 IEEE 15th International Conference on Bioinformatics and Bioengineering, BIBE 2015, Institute of Electrical and Electronics Engineers (IEEE), 15th IEEE International Conference on Bioinformatics and Bioengineering, BIBE 2015, Belgrade, Serbia, 2/11/15. https://doi.org/10.1109/BIBE.2015.7367709

Automatic estimation of the optimal AR order for epilepsy analysis using EEG signals. / Pippa, Evangelia; Mporas, Iosif; Megalooikonomou, Vasileios.
2015 IEEE 15th International Conference on Bioinformatics and Bioengineering, BIBE 2015. Institute of Electrical and Electronics Engineers (IEEE), 2015. 7367709 (2015 IEEE 15th International Conference on Bioinformatics and Bioengineering, BIBE 2015).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Automatic estimation of the optimal AR order for epilepsy analysis using EEG signals

AU - Pippa, Evangelia

AU - Mporas, Iosif

AU - Megalooikonomou, Vasileios

PY - 2015/12/28

Y1 - 2015/12/28

N2 - In this paper, we propose a computationally efficient method to estimate the optimal order of the autoregressive (AR) modeling of electroencephalographic (EEG) signals in order to use the AR coefficients as features for the analysis of EEG signals and the automatic detection of epileptic seizures. The estimation of the optimal AR-order is made using regression analysis of statistical features extracted from the samples of the EEG signals. The proposed method was evaluated in both background and ictal EEG segments using recordings from 10 epileptic patients. The experimental evaluation showed that the mean absolute error of the estimated optimal AR order is approximately 4 units.

AB - In this paper, we propose a computationally efficient method to estimate the optimal order of the autoregressive (AR) modeling of electroencephalographic (EEG) signals in order to use the AR coefficients as features for the analysis of EEG signals and the automatic detection of epileptic seizures. The estimation of the optimal AR-order is made using regression analysis of statistical features extracted from the samples of the EEG signals. The proposed method was evaluated in both background and ictal EEG segments using recordings from 10 epileptic patients. The experimental evaluation showed that the mean absolute error of the estimated optimal AR order is approximately 4 units.

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U2 - 10.1109/BIBE.2015.7367709

DO - 10.1109/BIBE.2015.7367709

M3 - Conference contribution

AN - SCOPUS:84962786723

T3 - 2015 IEEE 15th International Conference on Bioinformatics and Bioengineering, BIBE 2015

BT - 2015 IEEE 15th International Conference on Bioinformatics and Bioengineering, BIBE 2015

PB - Institute of Electrical and Electronics Engineers (IEEE)

T2 - 15th IEEE International Conference on Bioinformatics and Bioengineering, BIBE 2015

Y2 - 2 November 2015 through 4 November 2015

ER -

Pippa E, Mporas I, Megalooikonomou V. Automatic estimation of the optimal AR order for epilepsy analysis using EEG signals. In 2015 IEEE 15th International Conference on Bioinformatics and Bioengineering, BIBE 2015. Institute of Electrical and Electronics Engineers (IEEE). 2015. 7367709. (2015 IEEE 15th International Conference on Bioinformatics and Bioengineering, BIBE 2015). doi: 10.1109/BIBE.2015.7367709

Automatic estimation of the optimal AR order for epilepsy analysis using EEG signals

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