An electroencephalogram (EEG) is an electrical activity which is
recorded from the scalp over the sensorimotor cortex during vigilance or
sleeping conditions of subjects. It can
be used to detect potential problems associated with brain disorders. The aim of this study is assessing the
clinical usefulness of EEG which is recorded from slow cortical potentials
(SCP) training in stroke patients using Deep belief network (DBN) which has a
greedy layer wise training using Restricted Boltzmann Machines based
unsupervised weight and bias evaluation and neural network based supervised
training. EEGs are recorded during eight SCP neurofeedback sessions from two
stroke patients with a sampling rate of 256 Hz. All EEGs are filtered with a
low pass filter. Hilbert-Huang Transform is applied to the trails and various
numbers of Instinct Mode Functions (IMFs) are obtained. High order statistics
and standard statistics are extracted from IMFs to create the dataset. The
proposed DBN-based brain activity classification has discriminated positivity
and negativity tasks in stroke patients and has achieved high rates of 90.30%,
96.58%, and 91.15%, for sensitivity, selectivity, and accuracy, respectively.
Subjects | Engineering |
---|---|
Journal Section | Research Article |
Authors |
|
Dates |
Publication Date : December 1, 2016 |
Bibtex | @research article { ijamec270307,
journal = {International Journal of Applied Mathematics Electronics and Computers},
issn = {2147-8228},
eissn = {2147-8228},
address = {},
publisher = {Selcuk University},
year = {2016},
volume = {},
pages = {205 - 210},
doi = {10.18100/ijamec.270307},
title = {Deep Belief Networks Based Brain Activity Classification Using EEG from Slow Cortical Potentials in Stroke},
key = {cite},
author = {Altan, Gokhan and Kutlu, Yakup and Allahverdi̇, Novruz}
} |
APA | Altan, G , Kutlu, Y , Allahverdi̇, N . (2016). Deep Belief Networks Based Brain Activity Classification Using EEG from Slow Cortical Potentials in Stroke . International Journal of Applied Mathematics Electronics and Computers , Special Issue (2016) , 205-210 . DOI: 10.18100/ijamec.270307 |
MLA | Altan, G , Kutlu, Y , Allahverdi̇, N . "Deep Belief Networks Based Brain Activity Classification Using EEG from Slow Cortical Potentials in Stroke" . International Journal of Applied Mathematics Electronics and Computers (2016 ): 205-210 <https://dergipark.org.tr/en/pub/ijamec/issue/25619/270307> |
Chicago | Altan, G , Kutlu, Y , Allahverdi̇, N . "Deep Belief Networks Based Brain Activity Classification Using EEG from Slow Cortical Potentials in Stroke". International Journal of Applied Mathematics Electronics and Computers (2016 ): 205-210 |
RIS | TY - JOUR T1 - Deep Belief Networks Based Brain Activity Classification Using EEG from Slow Cortical Potentials in Stroke AU - Gokhan Altan , Yakup Kutlu , Novruz Allahverdi̇ Y1 - 2016 PY - 2016 N1 - doi: 10.18100/ijamec.270307 DO - 10.18100/ijamec.270307 T2 - International Journal of Applied Mathematics Electronics and Computers JF - Journal JO - JOR SP - 205 EP - 210 VL - IS - Special Issue-1 SN - 2147-8228-2147-8228 M3 - doi: 10.18100/ijamec.270307 UR - https://doi.org/10.18100/ijamec.270307 Y2 - 2016 ER - |
EndNote | %0 International Journal of Applied Mathematics Electronics and Computers Deep Belief Networks Based Brain Activity Classification Using EEG from Slow Cortical Potentials in Stroke %A Gokhan Altan , Yakup Kutlu , Novruz Allahverdi̇ %T Deep Belief Networks Based Brain Activity Classification Using EEG from Slow Cortical Potentials in Stroke %D 2016 %J International Journal of Applied Mathematics Electronics and Computers %P 2147-8228-2147-8228 %V %N Special Issue-1 %R doi: 10.18100/ijamec.270307 %U 10.18100/ijamec.270307 |
ISNAD | Altan, Gokhan , Kutlu, Yakup , Allahverdi̇, Novruz . "Deep Belief Networks Based Brain Activity Classification Using EEG from Slow Cortical Potentials in Stroke". International Journal of Applied Mathematics Electronics and Computers / Special Issue-1 (December 2016): 205-210 . https://doi.org/10.18100/ijamec.270307 |
AMA | Altan G , Kutlu Y , Allahverdi̇ N . Deep Belief Networks Based Brain Activity Classification Using EEG from Slow Cortical Potentials in Stroke. International Journal of Applied Mathematics Electronics and Computers. 2016; (Special Issue-1): 205-210. |
Vancouver | Altan G , Kutlu Y , Allahverdi̇ N . Deep Belief Networks Based Brain Activity Classification Using EEG from Slow Cortical Potentials in Stroke. International Journal of Applied Mathematics Electronics and Computers. 2016; (Special Issue-1): 205-210. |
IEEE | G. Altan , Y. Kutlu and N. Allahverdi̇ , "Deep Belief Networks Based Brain Activity Classification Using EEG from Slow Cortical Potentials in Stroke", International Journal of Applied Mathematics Electronics and Computers, no. Special Issue-1, pp. 205-210, Dec. 2016, doi:10.18100/ijamec.270307 |