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  1. 1
    Eeg-Based Person Identification Using Multi-Levelwavelet Decomposition With Multi-Objective Flower Pollination Algorithm

    Eeg-Based Person Identification Using Multi-Levelwavelet Decomposition With Multi-Objective Flower Pollination Algorithm by Yahya Alyasseri, Zaid Abdi Alkareem

    Published 2020
    “…The proposed method is tested using two standard EEG datasets, namely, Kiern’s and Motor Movement/Imagery.…”
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  2. 2
    Single-trial visual evoked potential extraction using partial least-squares-based approach

    Single-trial visual evoked potential extraction using partial least-squares-based approach by Yanti, D.K., Yusoff, M.Z., Asirvadam, V.S.

    Published 2016
    “…For P100, the proposed PLS algorithm is able to provide comparable results to the generalized eigenvalue decomposition (GEVD) algorithm, which alters (prewhitens) the EEG input signal using the prestimulation EEG signal. …”
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  3. 3
    Single-trial visual evoked potential extraction using partial least-squares-based approach

    Single-trial visual evoked potential extraction using partial least-squares-based approach by Yanti, D.K., Yusoff, M.Z., Asirvadam, V.S.

    Published 2016
    “…For P100, the proposed PLS algorithm is able to provide comparable results to the generalized eigenvalue decomposition (GEVD) algorithm, which alters (prewhitens) the EEG input signal using the prestimulation EEG signal. …”
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  4. 4
    Classification of labour pain using electroencephalogram signal based on wavelet method / Sai Chong Yeh

    Classification of labour pain using electroencephalogram signal based on wavelet method / Sai Chong Yeh by Sai , Chong Yeh

    Published 2020
    “…The training and parameters selection of the machine learning algorithms are conducted using EEG data collected from ten subjects in the laboratory. …”
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  5. 5
    Dingle's Model-based EEG Peak Detection using a Rule-based Classifier

    Dingle's Model-based EEG Peak Detection using a Rule-based Classifier by Asrul, Adam, Norrima, Mokhtar, Marizan, Mubin, Zuwairie, Ibrahim, Mohd Ibrahim, Shapiai

    Published 2015
    “…In this study, the performances of four different peak models of time domain approach which are Dumpala's, Acir's, Liu's, and Dingle's peak models are evaluated for electroencephalogram (EEG) signal peak detection algorithm. The algorithm is developed into three stages: peak candidate detection, feature extraction, and classification. …”
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  6. 6
    Adaptive filtering of EEG/ERP through bounded range artificial Bee Colony (BR-ABC) algorithm

    Adaptive filtering of EEG/ERP through bounded range artificial Bee Colony (BR-ABC) algorithm by Ahirwal, M.K., Kumar, A., Singh, G.K.

    Published 2014
    “…A comparative study of the performance of conventional gradient based methods like LMS, RLS, and ABC algorithm is also made which reveals that ABC algorithm gives better performance in highly noisy environment.…”
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  7. 7
    Detection of the onset of epileptic seizure signal from scalp EEG using blind signal separation

    Detection of the onset of epileptic seizure signal from scalp EEG using blind signal separation by Moghavvemi, M., Mehrkanoon, S.

    Published 2009
    “…BSS algorithm is used to demix the EEG signal into signals with independent features. …”
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  8. 8
    An enhanced computational model based on social spider optimisation algorithm for EEG- based emotion recognition

    An enhanced computational model based on social spider optimisation algorithm for EEG- based emotion recognition by Al-Qammaz, Abdullah Yousef Awwad

    Published 2019
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  9. 9
    The classification of wink-based eeg signals by means of transfer learning models

    The classification of wink-based eeg signals by means of transfer learning models by Jothi Letchumy, Mahendra Kumar

    Published 2021
    “…It is non-trivial to note that EEG-based signals for instance, winking could mitigate the aforesaid issue. …”
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  10. 10
    Evaluation of different peak models of eye blink EEG for signal peak detection using artificial neural network

    Evaluation of different peak models of eye blink EEG for signal peak detection using artificial neural network by Adam, A., Ibrahim, Z., Mokhtar, N., Shapiai, M.I., Mubin, M.

    Published 2016
    “…In general, there are various peak models available in literature, which have been tested in several peak detection algorithms. In this study, performance evaluation of the existing peak models is conducted based on Artificial Neural Network (ANN) with particle swarm optimization (PSO) as learning algorithm. …”
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  11. 11
    Electroencephalogram-based decoding cognitive states using convolutional neural network and likelihood ratio based score fusion

    Electroencephalogram-based decoding cognitive states using convolutional neural network and likelihood ratio based score fusion by Zafar, R., Dass, S.C., Malik, A.S.

    Published 2017
    “…Electroencephalogram (EEG)-based decoding human brain activity is challenging, owing to the low spatial resolution of EEG. …”
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  12. 12
    Embedded fuzzy classifier for detection and classification of preseizure state using real EEG data

    Embedded fuzzy classifier for detection and classification of preseizure state using real EEG data by Qidwai, U., Malik, A.S., Shakir, M.

    Published 2014
    “…Electroencephalography (EEG) plays an important role, especially EEG based health diagnosis of brain disorder. …”
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  13. 13
    Task-state EEG feature extraction for spatial cognition analysis: a power spectral density and permutation conditional mutual information approach

    Task-state EEG feature extraction for spatial cognition analysis: a power spectral density and permutation conditional mutual information approach by Liu, Yijun, Mustafa, Mohd Shafie, Saripan, M Iqbal, Kamel Ariffin, Muhammad Rezal, Wan, Xianglong, Dong, Xianling, Lan, Xifa, Wen, Dong

    Published 2025
    “…In this study, the performance of the PSDPCMI algorithm was employed for a VR spatial cognitive training experiment based on a Virtual Community training game and a Virtual City Walking testing game as carriers for subjects’ training and evaluation. …”
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  14. 14
    Evaluation Of Different Peak Models Of Eye Blink Eeg For Signal Peak Detection Using Artificial Neural Network

    Evaluation Of Different Peak Models Of Eye Blink Eeg For Signal Peak Detection Using Artificial Neural Network by Asrul, Adam, Zuwairie, Ibrahim, Mohd Ibrahim, Shapiai, Marizan, Mubin

    Published 2016
    “…In general, there are various peak models available in literature, which have been tested in several peak detection algorithms. In this study, performance evaluation of the existing peak models is conducted based on Artificial Neural Network (ANN) with particle swarm optimization (PSO) as learning algorithm. …”
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  15. 15
    EEG-based emotion recognition using machine learning algorithms

    EEG-based emotion recognition using machine learning algorithms by Lam, Yee Wei

    Published 2024
    “…Thus, this project proposed an optimised machine learning algorithms to classify emotion by analysing brain activity using Electroencephalogram (EEG) signals. …”
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  16. 16
    Embedded Fuzzy Classifier for Detection and Classification of Preseizure state using Real EEG data

    Embedded Fuzzy Classifier for Detection and Classification of Preseizure state using Real EEG data by Qidwai, Uvais, Malik, Aamir Saeed, Shakir, Mohamed

    Published 2014
    “…Electroencephalography (EEG) plays an important role, especially EEG based health diagnosis of brain disorder. …”
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  17. 17
    P300 detection of brain signals using a combination of wavelet transform techniques

    P300 detection of brain signals using a combination of wavelet transform techniques by Motlagh, Farid Esmaeili

    Published 2012
    “…By reduction of recording EEG channels in the single trial based algorithms, the processing time of P300 detection decrease dramatically. …”
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  18. 18
    EEG Simulation Hardware for Realistic Seizure, Preseizure and Normal Mode Signal Generation

    EEG Simulation Hardware for Realistic Seizure, Preseizure and Normal Mode Signal Generation by Shakir, Mohamed, Qidwai, Uvais, Malik, Aamir Saeed, Kamel, Nidal

    Published 2015
    “…Such a simulator will be very helpful in EEG related research since all the initial algorithms can be tuned to the controlled data first before going to the actual human subjects. …”
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  19. 19
    Classification of EEG Spectrogram Using ANN for IQ Application

    Classification of EEG Spectrogram Using ANN for IQ Application by Mahfuzah, Mustafa, Norizam, Sulaiman

    Published 2013
    “…The results will be validated based on the concept of Raven's Standard Progressive Matrices (RPM) IQ test. …”
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  20. 20
    Empirical Analysis of Intra vs. Inter-Subject Variability in VR EEG-Based Emotion Modelling

    Empirical Analysis of Intra vs. Inter-Subject Variability in VR EEG-Based Emotion Modelling by N.S. Suhaimi, J. Teo, J. Mountstephens

    Published 2018
    “…Secondly, the data will then be tested and trained with KNN and SVM algorithms. We conduct subject-dependent as well as subject-independent classifications in order to compare intra-against inter-subject variability, respectively in VR EEG-based emotion modeling. …”
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