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An Adaptive Task-Related Component Analysis Method for SSVEP Recognition

Sensors (Basel, Switzerland), 2022-10, Vol.22 (20), p.7715

Oikonomou, Vangelis P.

2022

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Human Recognition Using Deep Neural Networks and Spatial Patterns of SSVEP Signals

Sensors (Basel, Switzerland), 2023-02, Vol.23 (5), p.2425

Oikonomou, Vangelis P

2023

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A Sparse Representation Classification Scheme for the Recognition of Affective and Cognitive Brain Processes in Neuromarketing

Sensors (Basel, Switzerland), 2023-02, Vol.23 (5), p.2480

2023

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NeuMa - the absolute Neuromarketing dataset en route to an holistic understanding of consumer behaviour

Scientific data, 2023-08, Vol.10 (1), p.508-508, Article 508

2023

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Eliciting brain waves of people with cognitive impairment during meditation exercises using portable electroencephalography in a smart-home environment: a pilot study

Frontiers in aging neuroscience, 2023-05, Vol.15, p.1167410-1167410

2023

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Robust Motor Imagery Classification Using Sparse Representations and Grouping Structures

IEEE access, 2020, Vol.8, p.98572-98583

2020

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Assessing the cognitive decline of people in the spectrum of AD by monitoring their activities of daily living in an IoT-enabled smart home environment: a cross-sectional pilot study

Frontiers in aging neuroscience, 2024-03, Vol.16, p.1375131-1375131

2024

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Corrections to "Robust Motor Imagery Classification Using Sparse Representations and Grouping Structures"

IEEE access, 2021, Vol.9, p.150213-150213

2021

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A Bayesian Multiple Kernel Learning Algorithm for SSVEP BCI Detection

IEEE journal of biomedical and health informatics, 2019-09, Vol.23 (5), p.1990-2001

2019

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Exploring the Connection of Brain Computer Interfaces and Multimedia Use With the Social Integration of People With Various Motor Disabilities: A Questionnaire-Based Usability Study

Frontiers in digital health, 2022-08, Vol.4, p.846963-846963

2022

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RNeuMark: A Riemannian EEG Analysis Framework for Neuromarketing

Brain informatics, 2022-09, Vol.9 (1), p.22-12, Article 22

2022

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A Novel Connectome-based Electrophysiological Study of Subjective Cognitive Decline Related to Alzheimer’s Disease by Using Resting-state High-density EEG EGI GES 300

Brain sciences, 2020-06, Vol.10 (6), p.392

2020

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Identification of Brain Functional Networks Using a Model-Based Approach

International journal of pattern recognition and artificial intelligence, 2020-07, Vol.34 (8), p.2057004

2020

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A Novel Bayesian Approach for EEG Source Localization

Computational intelligence and neuroscience, 2020, Vol.2020 (2020), p.1-12

2020

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Revisiting Riemannian geometry-based EEG decoding through approximate joint diagonalization

Journal of neural engineering, 2022-12, Vol.19 (6), p.66030

2022

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Exploring Network Properties Across Preclinical Stages of Alzheimer's Disease Using a Visual Short-Term Memory and Attention Task with High-Density Electroencephalography: A Brain-Connectome Neurophysiological Study

Journal of Alzheimer's disease, 2022-01, Vol.87 (2), p.643-664

2022

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An Adaptive Regression Mixture Model for fMRI Cluster Analysis

IEEE transactions on medical imaging, 2013-04, Vol.32 (4), p.649-659

2013

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A Sparse and Spatially Constrained Generative Regression Model for fMRI Data Analysis

IEEE transactions on biomedical engineering, 2012-01, Vol.59 (1), p.58-67

2012

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Unlocking the Subconscious Consumer Bias: A Survey on the Past, Present, and Future of Hybrid EEG Schemes in Neuromarketing

Frontiers in neuroergonomics, 2021-05, Vol.2, p.672982-672982

2021

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Exploiting Approximate Joint Diagonalization for Covariance Estimation in Imagined Speech Decoding

Brain Informatics, p.409-419

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Harneshing the Potential of EEG in Neuromarketing with Deep Learning and Riemannian Geometry

Brain Informatics, p.21-32

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Bayesian Methods for fMRI Time-Series Analysis Using a Nonstationary Model for the Noise

IEEE transactions on information technology in biomedicine, 2010-05, Vol.14 (3), p.664-674

2010

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Discrimination of SSVEP responses using a kernel based approach

2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2019, Vol.2019, p.762-766

2019

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Sparse Kernel Machines for motor imagery EEG classification

2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2018, Vol.2018, p.207-210

2018

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An Adaptive Task-Related Component Analysis Method for SSVEP Recognition

Human Recognition Using Deep Neural Networks and Spatial Patterns of SSVEP Signals

A Sparse Representation Classification Scheme for the Recognition of Affective and Cognitive Brain Processes in Neuromarketing

NeuMa - the absolute Neuromarketing dataset en route to an holistic understanding of consumer behaviour

Eliciting brain waves of people with cognitive impairment during meditation exercises using portable electroencephalography in a smart-home environment: a pilot study

Robust Motor Imagery Classification Using Sparse Representations and Grouping Structures

Assessing the cognitive decline of people in the spectrum of AD by monitoring their activities of daily living in an IoT-enabled smart home environment: a cross-sectional pilot study

Corrections to "Robust Motor Imagery Classification Using Sparse Representations and Grouping Structures"

A Bayesian Multiple Kernel Learning Algorithm for SSVEP BCI Detection

Exploring the Connection of Brain Computer Interfaces and Multimedia Use With the Social Integration of People With Various Motor Disabilities: A Questionnaire-Based Usability Study

RNeuMark: A Riemannian EEG Analysis Framework for Neuromarketing

A Novel Connectome-based Electrophysiological Study of Subjective Cognitive Decline Related to Alzheimer’s Disease by Using Resting-state High-density EEG EGI GES 300

Identification of Brain Functional Networks Using a Model-Based Approach

A Novel Bayesian Approach for EEG Source Localization

Revisiting Riemannian geometry-based EEG decoding through approximate joint diagonalization

Exploring Network Properties Across Preclinical Stages of Alzheimer's Disease Using a Visual Short-Term Memory and Attention Task with High-Density Electroencephalography: A Brain-Connectome Neurophysiological Study

An Adaptive Regression Mixture Model for fMRI Cluster Analysis

A Sparse and Spatially Constrained Generative Regression Model for fMRI Data Analysis

Unlocking the Subconscious Consumer Bias: A Survey on the Past, Present, and Future of Hybrid EEG Schemes in Neuromarketing

Exploiting Approximate Joint Diagonalization for Covariance Estimation in Imagined Speech Decoding

Harneshing the Potential of EEG in Neuromarketing with Deep Learning and Riemannian Geometry

Bayesian Methods for fMRI Time-Series Analysis Using a Nonstationary Model for the Noise

A multimodal dataset for authoring and editing multimedia content: The MAMEM project

Discrimination of SSVEP responses using a kernel based approach

Sparse Kernel Machines for motor imagery EEG classification

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