Optimal EEG channel selection for vascular dementia identification using improved binary gravitation search algorithm

Noor Kamal Al-Qazzaz, Sawal Hamid Md Ali, Siti Anom Ahmad, Javier Escudero

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

Abstract

The aim of the present study was to select optimal channels that may help in detecting the abnormalities in the electroencephalogram (EEG) of vascular dementia (VaD) patients. Spectral entropy (SpecEn), approximation entropy (ApEn) and permutation entropy (PerEn) have been extracted from the EEG background activity of 5 VaD, 15 patients with stroke-related mild cognitive impairment (MCI) and 15 healthy control subjects during a working memory (WM) task. EEG artifacts were removed using automatic independent component analysis and wavelet denoising technique (AICA-WT). In order to reduce the computational time, improved binary gravitation search algorithm (IBGSA) channel selection was used to find the most effective EEG channels for VaD patients’ detection. Eight channels were found suitable to extract EEG markers that help to detect dementia in the early stages. Moreover, k-nearest neighbors (kNN) was used after the IBGSA technique. The IBGSA technique increased the kNN classification accuracy from 86.67 to 90.52%. These results suggest that IBGSA consistently improves the discrimination of VaD, MCI patients and control normal subjects and it could be a useful feature selection to help the identification of patients with VaD and MCI.

Original languageEnglish
Title of host publication2nd International Conference for Innovation in Biomedical Engineering and Life Sciences - ICIBEL 2017 in conjunction with APCMBE 2017
PublisherSpringer Verlag
Pages125-130
Number of pages6
Volume67
ISBN (Print)9789811075537
DOIs
Publication statusPublished - 1 Jan 2018
Event2nd International Conference for Innovation in Biomedical Engineering and Life Sciences, ICIBEL 2017, held in conjunction with the 10th Asia Pacific Conference on Medical and Biological Engineering, APCMBE 2017 - Penang, Malaysia
Duration: 10 Dec 201713 Dec 2017

Other

Other2nd International Conference for Innovation in Biomedical Engineering and Life Sciences, ICIBEL 2017, held in conjunction with the 10th Asia Pacific Conference on Medical and Biological Engineering, APCMBE 2017
CountryMalaysia
CityPenang
Period10/12/1713/12/17

Fingerprint

Electroencephalography
Gravitation
Entropy
Independent component analysis
Feature extraction
Data storage equipment

Keywords

  • Channels selection
  • Dementia
  • Electroencephalography
  • Improved binary gravitation search algorithm

ASJC Scopus subject areas

  • Bioengineering
  • Biomedical Engineering

Cite this

Al-Qazzaz, N. K., Md Ali, S. H., Ahmad, S. A., & Escudero, J. (2018). Optimal EEG channel selection for vascular dementia identification using improved binary gravitation search algorithm. In 2nd International Conference for Innovation in Biomedical Engineering and Life Sciences - ICIBEL 2017 in conjunction with APCMBE 2017 (Vol. 67, pp. 125-130). Springer Verlag. https://doi.org/10.1007/978-981-10-7554-4_21

Optimal EEG channel selection for vascular dementia identification using improved binary gravitation search algorithm. / Al-Qazzaz, Noor Kamal; Md Ali, Sawal Hamid; Ahmad, Siti Anom; Escudero, Javier.

2nd International Conference for Innovation in Biomedical Engineering and Life Sciences - ICIBEL 2017 in conjunction with APCMBE 2017. Vol. 67 Springer Verlag, 2018. p. 125-130.

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

Al-Qazzaz, NK, Md Ali, SH, Ahmad, SA & Escudero, J 2018, Optimal EEG channel selection for vascular dementia identification using improved binary gravitation search algorithm. in 2nd International Conference for Innovation in Biomedical Engineering and Life Sciences - ICIBEL 2017 in conjunction with APCMBE 2017. vol. 67, Springer Verlag, pp. 125-130, 2nd International Conference for Innovation in Biomedical Engineering and Life Sciences, ICIBEL 2017, held in conjunction with the 10th Asia Pacific Conference on Medical and Biological Engineering, APCMBE 2017, Penang, Malaysia, 10/12/17. https://doi.org/10.1007/978-981-10-7554-4_21
Al-Qazzaz NK, Md Ali SH, Ahmad SA, Escudero J. Optimal EEG channel selection for vascular dementia identification using improved binary gravitation search algorithm. In 2nd International Conference for Innovation in Biomedical Engineering and Life Sciences - ICIBEL 2017 in conjunction with APCMBE 2017. Vol. 67. Springer Verlag. 2018. p. 125-130 https://doi.org/10.1007/978-981-10-7554-4_21
Al-Qazzaz, Noor Kamal ; Md Ali, Sawal Hamid ; Ahmad, Siti Anom ; Escudero, Javier. / Optimal EEG channel selection for vascular dementia identification using improved binary gravitation search algorithm. 2nd International Conference for Innovation in Biomedical Engineering and Life Sciences - ICIBEL 2017 in conjunction with APCMBE 2017. Vol. 67 Springer Verlag, 2018. pp. 125-130
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