Table A1.
Listing of Additional Publications from the Period of 31 October 2019 Until 26 June 2021.
| Author | Year Published |
Title |
|---|---|---|
| Choi et al. | 2019 | A multi-day and multi-band dataset for a steady-state visual-evoked potential-based brain–computer interface |
| Ganorkar and Raut | 2019 | Comparative analysis of mother wavelet selection for eeg signal application to motor imagery-based brain–computer interface |
| Hekmatmanesh et al. | 2019 | Combination of discrete wavelet packet transform with detrended fluctuation analysis using customized mother wavelet with the aim of an imagery-motor control interface for an exoskeleton |
| Khan et al. | 2019 | Multiclass EEG motor-imagery classification with sub-band common spatial patterns |
| Khoshnevis and Ghorshi | 2019 | Recovery of event-related potential signals using compressive sensing and kronecker technique |
| Liu et al. | 2019 | Fully Passive Flexible Wireless Neural Recorder for the Acquisition of Neuropotentials from a Rat Model |
| Mebarkia and Reffad | 2019 | Multi optimized SVM classifiers for motor imagery left and right hand movement identification |
| Nagabushan et al. | 2019 | A comparative study of motor imagery-based BCI classifiers on EEG and iEEG data |
| Onay and Kose | 2019 | Assessment of CSP-based two-stage channel selection approach and local transformation-based feature extraction for classification of motor imagery/movement EEG data |
| Oralhan | 2019 | 2 Stages-region-based P300 Speller in Brain–Computer Interface |
| Saikia and Paul | 2019 | EEG signal processing and its classification for rehabilitation device control |
| Taran and Bajaj | 2019 | Motor imagery tasks-based EEG signals classification using tunable-Q wavelet transform |
| Wu et al. | 2019 | A Parallel Multiscale Filter Bank Convolutional Neural Networks for Motor Imagery EEG Classification |
| Yao and Shoaran | 2019 | Enhanced Classification of Individual Finger Movements with ECoG |
| Yu Chen and Mehmood | 2019 | A critical review on state-of-the-art EEG-based emotion datasets |
| Zhang et al. | 2019 | A Graph-Based Hierarchical Attention Model for Movement Intention Detection from EEG Signals |
| Zhang et al. | 2019 | Deep Learning Decoding of Mental State in Non-invasive Brain Computer Interface |
| Aggarwal and Chugh | 2020 | A decade of EEG Analysis: Prospects & Challenges in Biometric System |
| Alakus and Turkoglu | 2020 | Emotion recognition with deep learning using GAMEEMO data set |
| Alhakeem et al. | 2020 | Wheelchair Free Hands Navigation Using Robust DWT-AR Features Extraction Method with Muscle Brain Signals |
| Ali et al. | 2020 | Classification of Motor Imagery Task by Using Novel Ensemble Pruning Approach |
| Al-Nafjan et al. | 2020 | Lightweight Building of an Electroencephalogram-Based Emotion Detection System |
| Andrade et al. | 2020 | An EEG Brain–Computer Interface to Classify Motor Imagery Signals |
| Angrisani et al. | 2020 | Instrumentation for motor imagery-based brain computer interfaces relying on dry electrodes: A functional analysis |
| Araki et al. | 2020 | Wireless Monitoring Using a Stretchable and Transparent Sensor Sheet Containing Metal Nanowires |
| Arico et al. | 2020 | Brain–Computer Interfaces: Toward a Daily Life Employment |
| Aroudi and Doclo | 2020 | Cognitive-Driven Binaural Beamforming Using EEG-Based Auditory Attention Decoding |
| Bablani et al. | 2020 | A multi stage EEG data classification using k-means and feed forward neural network |
| Bigirimana et al. | 2020 | Emotion-Inducing Imagery Versus Motor Imagery for a Brain–Computer Interface |
| Borra et al. | 2020 | Interpretable and lightweight convolutional neural network for EEG decoding: Application to movement execution and imagination |
| Borra et al. | 2020 | Convolutional Neural Network for a P300 Brain–Computer Interface to Improve Social Attention in Autistic Spectrum Disorder |
| Cao and Grover | 2020 | STIMULUS: Noninvasive Dynamic Patterns of Neurostimulation Using Spatio-Temporal Interference |
| Castro et al. | 2020 | Development of a Deep Learning-Based Brain–Computer Interface for Visual Imagery Recognition |
| Cha et al. | 2020 | Prediction of individual user’s dynamic ranges of EEG features from resting-state EEG data for evaluating their suitability for passive brain–computer interface applications |
| Chamola et al. | 2020 | Brain–computer interface-based humanoid control: A review |
| Chen et al. | 2020 | EEG-based biometric identification with convolutional neural network |
| Chen et al. | 2020 | Emotion recognition from spatiotemporal EEG representations with hybrid convolutional recurrent neural networks via wearable multi-channel headset |
| Cheng et al. | 2020 | Motion Imagery-BCI Based on EEG and Eye Movement Data Fusion |
| Cho et al. | 2020 | A Novel Approach to Classify Natural Grasp Actions by Estimating Muscle Activity Patterns from EEG Signals |
| Cho et al. | 2020 | Decoding of Grasp Motions from EEG Signals Based on a Novel Data Augmentation Strategy |
| Cortez et al. | 2020 | Improving Speller BCI performance using a cluster-based under-sampling method |
| Cortez et al. | 2020 | Under-sampling and Classification of P300 Single-Trials using Self-Organized Maps and Deep Neural Networks for a Speller BCI |
| Cozza et al. | 2020 | Dimension Reduction Techniques in a Brain–Computer Interface Application |
| Cudlenco et al. | 2020 | Reading into the mind’s eye: Boosting automatic visual recognition with EEG signals |
| de Melo et al. | 2020 | EEG Analysis in Coincident Timing Task Towards Motor Rehabilitation |
| Delvigne et al. | 2020 | Attention Estimation in Virtual Reality with EEG-based Image Regression |
| Deng et al. | 2020 | Self-adaptive shared control with brain state evaluation network for human-wheelchair cooperation |
| Deng et al. | 2020 | A Bayesian Shared Control Approach for Wheelchair Robot with Brain Machine Interface |
| Dimitrov et al. | 2020 | Increasing the Classification Accuracy of EEG-based Brain–computer Interface Signals |
| Dutta and Nandy | 2020 | An extensive analysis on deep neural architecture for classification of subject-independent cognitive states |
| Dutta et al. | 2020 | Development of a BCI-based gaming application to enhance cognitive control in psychiatric disorders |
| Elessawy et al. | 2020 | A long short-term memory autoencoder approach for EEG motor imagery classification |
| Elkafrawy et al. | 2020 | Proposed model for thought-based animation based on classifying EEG signals using estimated parameters and multi-SVM |
| Fathima and Kore | 2020 | Enhanced Differential Evolution-Based EEG Channel Selection |
| Feng et al. | 2020 | Decoding of voluntary and involuntary upper-limb motor imagery based on graph fourier transform and cross-frequency coupling coefficients |
| Filipp et al. | 2020 | Application of brain–computer interfaces in assistive technologies |
| Fontanillo et al. | 2020 | Beyond Technologies of Electroencephalography-Based Brain–Computer Interfaces: A Systematic Review From Commercial and Ethical Aspects |
| Gembler et al. | 2020 | Five Shades of Grey: Exploring Quintary m-Sequences for More User-Friendly c-VEP-Based BCIs |
| Ghosh et al. | 2020 | Bi-directional Long Short-Term Memory model to analyze psychological effects on gamers |
| Gorriz et al. | 2020 | Artificial intelligence within the interplay between natural and artificial computation: Advances in data science, trends and applications |
| Grissmann et al. | 2020 | Context Sensitivity of EEG-Based Workload Classification Under Different Affective Valence |
| Gu et al. | 2020 | The effects of varying levels of mental workload on motor imagery-based brain computer interface |
| Gubert et al. | 2020 | The performance impact of data augmentation in CSP-based motor-imagery systems for BCI applications |
| Gurve et al. | 2020 | Trends in Compressive Sensing for EEG Signal Processing Applications |
| Haira et al. | 2020 | A comparison of ECG and EEG metrics for in-flight monitoring of helicopter pilot workload |
| Hernandez-Cuevas et al. | 2020 | Neurophysiological Closed-Loop Control for Competitive Multi-brain Robot Interaction |
| Hussain and Park | 2020 | HealthSOS: Real-Time Health Monitoring System for Stroke Prognostics |
| Idowu et al. | 2020 | Efficient Classification of Motor Imagery using Particle Swarm Optimization-based Neural Network for IoT Applications |
| Ieracitano et al. | 2020 | A novel multi-modal machine learning-based approach for automatic classification of EEG recordings in dementia |
| Jeng et al. | 2020 | Low-Dimensional Subject Representation-based Transfer Learning in EEG Decoding |
| Jin et al. | 2020 | EEG classification using sparse Bayesian extreme learning machine for brain–computer interface |
| Kalafatovich et al. | 2020 | Decoding Visual Recognition of Objects from EEG Signals based on Attention-Driven Convolutional Neural Network |
| Kang et al. | 2020 | EEG-Based Prediction of Successful Memory Formation During Vocabulary Learning |
| Kaongoen and Jo | 2020 | An Ear-EEG-based Brain–Computer Interface using Concentration Level for Control |
| Kaur et al. | 2020 | A study of EEG for enterprise multimedia security |
| Khan et al. | 2020 | High performance multi-class motor imagery EEG classification |
| Kouddad et al. | 2020 | Indexing and Image Search by the Content According to the Biological Base of the Cognitive Processing of Information using a Neural Sensor |
| Kurapa et al. | 2020 | A Hybrid Approach for Extracting EMG signals by Filtering EEG Data for IoT Applications for Immobile Persons |
| Kuzovkin et al. | 2020 | Mental state space visualization for interactive modeling of personalized BCI control strategies |
| Kwon et al. | 2020 | Decoding of Intuitive Visual Motion Imagery Using Convolutional Neural Network under 3D-BCI Training Environment |
| Landau et al. | 2020 | Mind Your Mind: EEG-Based Brain–Computer Interfaces and Their Security in Cyber Space |
| Lee et al. | 2020 | Complex Motor Imagery-based Brain–Computer Interface System: A Comparison between Different Classifiers |
| Lee et al. | 2020 | Classification of Upper Limb Movements Using Convolutional Neural Network with 3D Inception Block |
| Leon et al. | 2020 | Deep learning for EEG-based Motor Imagery classification: Accuracy-cost trade-off |
| Li et al. | 2020 | Enhancing BCI-Based Emotion Recognition Using an Improved Particle Swarm Optimization for Feature Selection |
| Liang et al. | 2020 | EEG-Based EMG Estimation of Shoulder Joint for the Power Augmentation System of Upper Limbs |
| Lin et al. | 2020 | A Multi-Scale Activity Transition Network for Data Translation in EEG Signals Decoding |
| Luo et al. | 2020 | EEG Signal Reconstruction Using a Generative Adversarial Network With Wasserstein Distance and Temporal-Spatial-Frequency Loss |
| Luo et al. | 2020 | Estimation of Motor Imagination Based on Consumer-Grade EEG Device |
| Ma et al. | 2020 | Online learning using projections onto shrinkage closed balls for adaptive brain computer interface |
| Mattia et al. | 2020 | The Promotoer, a brain–computer interface-assisted intervention to promote upper limb functional motor recovery after stroke: a study protocol for a randomized controlled trial to test early and long-term efficacy and to identify determinants of response |
| Miao et al. | 2020 | Spatial-Frequency Feature Learning and Classification of Motor Imagery EEG Based on Deep Convolution Neural Network |
| Min and Cai | 2020 | Driver Fatigue Detection Based on Multi-scale Wavelet Log Energy Entropy of Frontal EEG |
| Mishra et al. | 2020 | Effect of hand grip actions on object recognition process: a machine learning-based approach for improved motor rehabilitation |
| Mondini et al. | 2020 | Continuous low-frequency EEG decoding of arm movement for closed-loop, natural control of a robotic arm |
| Nakagome et al. | 2020 | An empirical comparison of neural networks and machine learning algorithms for EEG gait decoding |
| Netzer et al. | 2020 | Real-time EEG classification via coresets for BCI applications |
| Nisar et al. | 2020 | Reducing Sensors in Mental Imagery-Based Cognitive Task for Brain Computer Interface |
| Pa Aung and New | 2020 | Regions of Interest (ROI) Analysis for Upper Limbs EEG Neuroimaging Schemes |
| Padmavathy et al. | 2020 | A novel deep learning classifier and genetic algorithm-based feature selection for hybrid EEG-FNIRS brain–computer interface |
| Paek et al. | 2020 | Towards a Portable Magnetoencephalography-Based Brain Computer Interface with Optically-Pumped Magnetometers |
| Pan et al. | 2020 | Prognosis for patients with cognitive motor dissociation identified by brain–computer interface |
| Pan et al. | 2020 | EEG-Based Emotion Recognition Using Logistic Regression with Gaussian Kernel and Laplacian Prior and Investigation of Critical Frequency Bands |
| Parikh and George | 2020 | Quadcopter Control in Three-Dimensional Space Using SSVEP and Motor Imagery-Based Brain–Computer Interface |
| Petukhov et al. | 2020 | Being present in a real or virtual world: A EEG study |
| Philip and George | 2020 | Visual P300 Mind-Speller Brain–Computer Interfaces: A Walk Through the Recent Developments With Special Focus on Classification Algorithms |
| Qin et al. | 2020 | Smart Home Control for Disabled Using Brain Computer Interface |
| Rakshit et al. | 2020 | A Hybrid Brain–Computer Interface for Closed-Loop Position Control of a Robot Arm |
| Rashid et al. | 2020 | Current Status, Challenges, and Possible Solutions of EEG-Based Brain–Computer Interface: A Comprehensive Review |
| Rashid et al. | 2020 | Five-Class SSVEP Response Detection using Common-Spatial Pattern (CSP)-SVM Approach |
| Riyad et al. | 2020 | Incep-eegnet: A convnet for motor imagery decoding |
| Roy et al. | 2020 | A hybrid classifier combination for home automation using EEG signals |
| Sadiq et al. | 2020 | Identification of motor and mental imagery EEG in two and multiclass subject-dependent tasks using successive decomposition index |
| Sahu et al. | 2020 | EEG signal analysis and classification on P300 speller-based BCI performance in ALS patients |
| Schembri et al. | 2020 | The Effect That Auditory Distractions Have on a Visual P300 Speller While Utilizing Low Cost Off-the-Shelf Equipment |
| Schneider et al. | 2020 | Real-time EEG Feedback on Alpha Power Lateralization Leads to Behavioral Improvements in a Covert Attention Task |
| Shao et al. | 2020 | EEG-Controlled Wall-Crawling Cleaning Robot Using SSVEP-Based Brain–Computer Interface |
| She et al. | 2020 | Multi-class motor imagery EEG classification using collaborative representation-based semi-supervised extreme learning machine |
| Shi et al. | 2020 | Feature Extraction of Brain–Computer Interface Electroencephalogram Based on Motor Imagery |
| Siddharth and Trivedi | 2020 | On assessing driver awareness of situational criticalities: Multi-modal bio-sensing and vision-based analysis, evaluations, and insights |
| Singh and Singh | 2020 | Realising transfer learning through convolutional neural network and support vector machine for mental task classification |
| Song et al. | 2020 | A Practical EEG-Based Human-Machine Interface to Online Control an Upper-Limb Assist Robot |
| Suma et al. | 2020 | Spatial-temporal aspects of continuous EEG-based neurorobotic control |
| Sun et al. | 2020 | Multimodal affective state assessment using fNIRS+ EEG and spontaneous facial expression |
| Talukdar et al. | 2020 | Adaptive feature extraction in EEG-based motor imagery BCI: tracking mental fatigue |
| Tan et al. | 2020 | Spiking Neural Networks: Background, Recent Development and the NeuCube Architecture |
| Tao | 2020 | Classification-Oriented Fuzzy-Rough Feature Selection for the EEG-Based Brain Computer Interfaces |
| Tiwari et al. | 2020 | Machine Learning approach for the classification of EEG signals of multiple imagery tasks |
| Torkamani-Azar et al. | 2020 | Prediction of Motor Imagery Performance based on Pre-Trial Spatio-Spectral Alertness Features |
| Torres et al. | 2020 | EEG-Based BCI Emotion Recognition: A Survey |
| Tzdaka et al. | 2020 | Assessing the Relevance of Neurophysiological Patterns to Predict Motor Imagery-based BCI Users’ Performance |
| Vigue-Guix et al. | 2020 | Can the occipital alpha-phase speed up visual detection through a real-time EEG-based brain–computer interface (BCI)? |
| Wafeek et al. | 2020 | A Novel EEG Classification Technique Based on Particle Swarm Optimization for Hand and Finger Movements |
| Wang et al. | 2020 | Enhancing gesture decoding performance using signals from posterior parietal cortex: a stereo-electroencephalograhy (SEEG) study |
| Wang et al. | 2020 | P300 Recognition Based on Ensemble of SVMs |
| William et al. | 2020 | ERP Template Matching for EEG Single Trial Classification |
| Wolpaw et al. | 2020 | Brain–computer interfaces: Definitions and principles |
| Xu et al. | 2020 | Implementing Over 100 Command Codes for a High-Speed Hybrid Brain–Computer Interface Using Concurrent P300 and SSVEP Features |
| Xu et al. | 2020 | Motor Imagery-Based Continuous Teleoperation Robot Control with Tactile Feedback |
| Xu et al. | 2020 | Two-level multi-domain feature extraction on sparse representation for motor imagery classification |
| Yan et al. | 2020 | An improve d common spatial pattern combine d with channel-selection strategy for electroencephalography-based emotion recognition |
| Yang et al. | 2020 | MI3DNet: A Compact CNN for Motor Imagery EEG Classification with Visualizable Dense Layer Parameters |
| Yao et al. | 2020 | Information-preserving feature filter for short-term EEG signals |
| Yi | 2020 | Efficient machine learning algorithm for electroencephalogram modeling in brain–computer interfaces |
| Zeng et al. | 2020 | InstanceEasyTL: An Improved Transfer-Learning Method for EEG-Based Cross-Subject Fatigue Detection |
| Zhang et al. | 2020 | Pain Control by Co-adaptive Learning in a Brain–Machine Interface |
| Zhang et al. | 2020 | Application of transfer learning in eeg decoding based on brain–computer interfaces: A review |
| Zhou et al. | 2020 | A Hybrid Asynchronous Brain–Computer Interface Combining SSVEP and EOG Signals |
| Zhuang et al. | 2020 | State-of-the-art non-invasive brain–computer interface for neural rehabilitation: A review |
| Aldayel et al. | 2021 | Consumers’ Preference Recognition Based on Brain–Computer Interfaces: Advances, Trends, and Applications |
| Alhudhaif | 2021 | An effective classification framework for brain–computer interface system design based on combining of fNIRS and EEG signals |
| Al-Saegh et al. | 2021 | Deep learning for motor imagery EEG-based classification: A review |
| Alzahab et al. | 2021 | Hybrid deep learning (Hdl)-based brain–computer interface (bci) systems: A systematic review |
| Asogbon et al. | 2021 | A linearly extendible multi-artifact removal approach for improved upper extremity EEG-based motor imagery decoding. |
| Aydarkhanov et al. | 2021 | Closed-loop EEG study on visual recognition during driving |
| Belo et al. | 2021 | EEG-Based Auditory Attention Detection and Its Possible Future Applications for Passive BCI |
| Benaroch et al. | 2021 | Long-Term BCI Training of a Tetraplegic User: Adaptive Riemannian Classifiers and User Training |
| Bhattacharyya et al. | 2021 | Neuro-feedback system for real-time BCI decision prediction |
| Cattai et al. | 2021 | Phase/Amplitude Synchronization of Brain Signals During Motor Imagery BCI Tasks. |
| Chaudhary et al. | 2021 | Neuropsychological and neurophysiological aspects of brain–computer interface (BCI) control in paralysis |
| Chen et al. | 2021 | EEG-Based Anxious States Classification Using Affective BCI-Based Closed Neurofeedback System |
| Chen et al. | 2021 | Implementing a calibration-free SSVEP-based BCI system with 160 targets. |
| Fu et al. | 2021 | Recognizing single-trial motor imagery EEG based on interpretable clustering method |
| Georgiev et al. | 2021 | Virtual reality for neurorehabilitation and cognitive enhancement |
| Gu et al. | 2021 | EEG-based Brain–Computer Interfaces (BCIs): A Survey of Recent Studies on Signal Sensing Technologies and Computational Intelligence Approaches and Their Applications |
| Guner and Erkmen | 2021 | A Low-Cost Real-Time BCI Integration for Automated Door Opening System |
| Gupta et al. | 2021 | Brain computer interface controlled automatic electric drive for neuro-aid system |
| Hong et al. | 2021 | Dynamic Joint Domain Adaptation Network for Motor Imagery Classification |
| Islam et al. | 2021 | Auditory Evoked Potential (AEP)-Based Brain–Computer Interface (BCI) Technology: A Short Review |
| Islam et al. | 2021 | Probability mapping-based artifact detection and removal from single-channel EEG signals for brain–computer interface applications. |
| Jeng et al. | 2021 | Low-Dimensional Subject Representation-Based Transfer Learning in EEG Decoding |
| Ketu et al. | 2021 | Hybrid classification model for eye state detection using electroencephalogram signals |
| Khan et al. | 2021 | Analysis of Human Gait Using Hybrid EEG-fNIRS-Based BCI System: A Review |
| Kharchenko et al. | 2021 | Influence of Signal Preprocessing When Highlighting Steady-State Visual Evoked Potentials Based on a Multivariate Synchronization Index |
| Kharchenko et al. | 2021 | Implementation of robot–human control bio-interface when highlighting visual-evoked potentials based on multivariate synchronization index |
| Kumar et al. | 2021 | The classification of EEG-based winking signals: a transfer learning and random forest pipeline |
| Liu et al. | 2021 | P300 event-related potential detection using one dimensional convolutional capsule networks |
| Liu et al. | 2021 | Multiscale space-time-frequency feature-guided multitask learning CNN for motor imagery EEG classification |
| Liu et al. | 2021 | A Utility Human Machine Interface Using Low Cost EEG Cap and Eye Tracker |
| Miladinovic et al. | 2021 | Effect of power feature covariance shift on BCI spatial-filtering techniques: A comparative study |
| Mishra et al. | 2021 | Effect of hand grip actions on object recognition process: a machine learning-based approach for improved motor rehabilitation |
| Qi et al. | 2021 | Spatiotemporal-Filtering-Based Channel Selection for Single-Trial EEG Classification |
| Qi et al. | 2021 | Wielding and evaluating the removal composition of common artefacts in EEG signals for driving behaviour analysis. |
| Rammy et al. | 2021 | Sequence-to-sequence deep neural network with spatio-spectro and temporal features for motor imagery classification |
| Ravirahul et al. | 2021 | Mind Wave Controlled Assistive Robot |
| Reyes et al. | 2021 | LSTM-based brain–machine interface tool for text generation through eyes blinking detection |
| Riyad et al. | 2021 | A novel multi-scale convolutional neural network for motor imagery classification |
| Rybar et al. | 2021 | Decoding of semantic categories of imagined concepts of animals and tools in fNIRS |
| Saga et al. | 2021 | Elucidation of EEG Characteristics of Fuzzy Reasoning-Based Heuristic BCI and Its Application to Patient With Brain Infarction |
| Santos et al. | 2021 | Comparison of LORETA and CSP for Brain–Computer Interface Applications |
| Shaban et al. | 2021 | Classification of Lactate Level Using Resting-State EEG Measurements |
| Shahbakhti et al. | 2021 | VME-DWT: An Efficient Algorithm for Detection and Elimination of Eye Blink from Short Segments of Single EEG Channel |
| Shi et al. | 2021 | A binary harmony search algorithm as channel selection method for motor imagery-based BCI |
| Somadder et al. | 2021 | Frequency Domain CSP for Foot Motor Imagery Classification Using SVM for BCI Application |
| Stival et al. | 2021 | Connectivity modeling meets machine learning: The next generation of eeg-based brain computer interfaces |
| Sulaiman et al. | 2021 | Offline eeg-based dc motor control for wheelchair application |
| Sun et al. | 2021 | WLnet: Towards an Approach for Robust Workload Estimation Based on Shallow Neural Networks |
| Wang et al. | 2021 | EEG-based auditory attention decoding using speech-level-based segmented computational models |
| Xu et al. | 2021 | Review of brain encoding and decoding mechanisms for EEG-based brain–computer interface |
| Yoo | 2021 | Electroencephalogram-based neurofeedback training in persons with stroke: A scoping review in occupational therapy |
| Yu et al. | 2021 | Cross-correlation-based discriminant criterion for channel selection in motor imagery BCI systems |
| Zeng et al. | 2021 | An EEG-Based Transfer Learning Method for Cross-Subject Fatigue Mental State Prediction |
| Zhang et al. | 2021 | Improving EEG Decoding via Clustering-Based Multitask Feature Learning |
| Zhang et al. | 2021 | EEG-inception: an accurate and robust end-to-end neural network for EEG-based motor imagery classification |
| Zhang et al. | 2021 | Tiny noise, big mistakes: adversarial perturbations induce errors in brain–computer interface spellers |
| Zolfaghari et al. | 2021 | Using convolution neural networks pattern for classification of motor imagery in bci system |