Search Results - (( using eeg method algorithm ) OR ( using optimization method algorithm ))
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Selection and optimization of peak features for event-related eeg signals classification / Asrul bin Adam
Published 2017“…In the preliminary study, the algorithm is evaluated on the four different peak models of the three EEG signals using the artificial neural network (ANN) with particle swarm optimization (PSO) as learning algorithm. …”
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Multichannel optimization with hybrid spectral- entropy markers for gender identification enhancement of emotional-based EEGs
Published 2021“…Moreover, the results show significant enhancement in the overall accuracy of classification achieved by using the BGSA optimization algorithm with the proposed hybrid SEA set when compared to individual features. …”
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Classification of labour pain using electroencephalogram signal based on wavelet method / Sai Chong Yeh
Published 2020“…All in all, this study aims to design, develop, optimize and test the method of pain assessment using the EEG signal during the active contraction phase of the first stage of labour. …”
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Optimal input features selection of wavelet-based EEG signals using GA
Published 2004“…We present a method of selecting optimal input features from wavelet coefficients of electroencephalogram (EEG) signals. …”
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P300 detection of brain signals using a combination of wavelet transform techniques
Published 2012“…In this research the BCI competition data-set has been processed through 5 optimized detection methods. Wavelet transform (WT), student’s two-sample t-statistic (T-Test) and support vector machines (SVM) used in designing the algorithms. …”
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Social spider optimisation algorithm for dimension reduction of electroencephalogram signals in human emotion recognition
Published 2018“…Due to some limitations of current heuristics and evolutionary algorithms, this paper proposed a new swarm based algorithm for feature selection method called Social Spider Optimization (SSO-FS). …”
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Bayesian Framework based Brain Source Localization Using High SNR EEG Data
Published 2019“…These sources can be localized using different optimization algorithms. This localization information is usable for diagnoses of brain disorders such as epilepsy, Schizophrenia, depression and Alzheimer. …”
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Reference-free Reduction of Ballistocardiogram Artifact from EEG Data Using EMD-PCA
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Feature Selection and Classifier Parameter Estimation for Egg Signal Peak Detection using Gravitational Search Algorithm
Published 2014“…This study focuses on using GSA method, a new computational intelligence algorithm. …”
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Reference-free reduction of ballistocardiogram artifact from EEG data using EMD-PCA
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Discrete wavelet packet transform for electroencephalogram based valence-arousal emotion recognition
Published 2015“…However, the challenging issues regarding EEG-based emotional state recognition is that it requires well-designed methods and algorithms to extract necessary features from the complex, chaotic, and multichannel EEG signal in order to achieve optimum classification performance. …”
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Random subspace K-NN based ensemble classifier for driver fatigue detection utilizing selected EEG channels
Published 2021“…Moreover, power spectral density (PSD) was used to extract the feature, confirming the presented method's robustness. …”
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Removal of BCG artefact from concurrent fMRI-EEG recordings based on EMD and PCA
Published 2017“…Results The method was tested with both simulated and real EEG data of 11 participants. …”
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Electroencephalogram signal interpretation system for mobile robot
Published 2013“…The most popular approach is a non-invasive method, using Electroencephalogram (EEG) analysis which acquires signals from the brain. …”
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Early explorations of EEG as a method for interactive evolutionary design of 3-dimensional objects
Published 2015“…This paper introduces an automatic method for generation of 3D artforms using electroencephalogram (EEG). …”
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The classification of wink-based eeg signals by means of transfer learning models
Published 2021“…The implementation of pre-processing algorithms has been demonstrated to be able to mitigate the signal noises that arises from the winking signals without the need for the use signal filtering algorithms. …”
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Drowsiness Detection Using Ocular Indices from EEG Signal
Published 2022“…In this study, we used the BLINKER algorithm to extract 25 blink-related features from a public dataset comprising raw EEG signals collected from 12 participants. …”
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