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Classification enhancement for post-stroke dementia using fuzzy neighborhood preserving analysis with QR-decomposition


Citation

Al-Qazzaz, Noor Kamal and Md. Ali, Sawal Hamid and Ahmad, Siti Anom and Rodriguez, Javier Escudero (2017) Classification enhancement for post-stroke dementia using fuzzy neighborhood preserving analysis with QR-decomposition. In: 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC'17), 11-15 July 2017, Jeju Island, Korea. (pp. 3174-3177).

Abstract / Synopsis

The aim of the present study was to discriminate the electroencephalogram (EEG) of 5 patients with vascular dementia (VaD), 15 patients with stroke-related mild cognitive impairment (MCI), and 15 control normal subjects during a working memory (WM) task. We used independent component analysis (ICA) and wavelet transform (WT) as a hybrid preprocessing approach for EEG artifact removal. Three different features were extracted from the cleaned EEG signals: spectral entropy (SpecEn), permutation entropy (PerEn) and Tsallis entropy (TsEn). Two classification schemes were applied - support vector machine (SVM) and k-nearest neighbors (kNN) - with fuzzy neighborhood preserving analysis with QR-decomposition (FNPAQR) as a dimensionality reduction technique. The FNPAQR dimensionality reduction technique increased the SVM classification accuracy from 82.22% to 90.37% and from 82.6% to 86.67% for kNN. These results suggest that FNPAQR 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.


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Additional Metadata

Item Type: Conference or Workshop Item (Paper)
Divisions: Faculty of Engineering
DOI Number: https://doi.org/10.1109/EMBC.2017.8037531
Publisher: IEEE
Keywords: Dementia; Fuzzy neighborhood preserving analysis with QR-decomposition; Electroencephalogram
Depositing User: Nabilah Mustapa
Date Deposited: 06 Mar 2018 04:09
Last Modified: 06 Mar 2018 04:09
Altmetrics: http://www.altmetric.com/details.php?domain=psasir.upm.edu.my&doi=10.1109/EMBC.2017.8037531
URI: http://psasir.upm.edu.my/id/eprint/59464
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