Deep Learning Based Inter-subject Continuous Decoding of Motor Imagery for Practical Brain-Computer Interfaces

Intra- and Inter-subject Variability in EEG-Based Sensorimotor Brain Computer Interface: A Review

(2020) Simanto Saha et al.   Frontiers in Computational Neuroscience

Covariate shift estimation based adaptive ensemble learning for handling non-stationarity in motor imagery related EEG-based brain-computer interface

(2019) Haider Raza et al.   NEUROCOMPUTING

Deep learning-based electroencephalography analysis: a systematic review

(2019) Yannick Roy et al.   Journal of Neural Engineering

Wavelet Entropy-Based Inter-subject Associative Cortical Source Localization for Sensorimotor BCI

(2019) Simanto Saha et al.   Frontiers in Neuroinformatics

An Automatic Subject Specific Intrinsic Mode Function Selection for Enhancing Two-Class EEG-Based Motor Imagery-Brain Computer Interface

(2019) Pramod Gaur et al.   IEEE SENSORS JOURNAL

Adaptive neural network classifier for decoding MEG signals

(2019) Ivan Zubarev et al.   NEUROIMAGE

Tangent Space Features-Based Transfer Learning Classification Model for Two-Class Motor Imagery Brain–Computer Interface

(2019) Pramod Gaur et al.   International Journal of Neural Systems

Subject-Independent Brain–Computer Interfaces Based on Deep Convolutional Neural Networks

(2019) O-Yeon Kwon et al.   IEEE Transactions on Neural Networks and Learning Systems

Transfer Learning: A Riemannian Geometry Framework With Applications to Brain–Computer Interfaces

(2018) Paolo Zanini et al.   IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING

Evidence of Variabilities in EEG Dynamics During Motor Imagery-Based Multiclass Brain–Computer Interface

(2018) Simanto Saha et al.   IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING

EEGNet: a compact convolutional neural network for EEG-based brain--computer interfaces

(2018) Vernon Lawhern et al.   Journal of Neural Engineering

A review of classification algorithms for EEG-based brain–computer interfaces: a 10 year update

(2018) F Lotte et al.   Journal of Neural Engineering

Interpreting and Utilising Intersubject Variability in Brain Function

(2018) Mohamed L. Seghier et al.   TRENDS IN COGNITIVE SCIENCES

Sparse Group Representation Model for Motor Imagery EEG Classification

(2018) Yong Jiao et al.   IEEE Journal of Biomedical and Health Informatics

EEG-Based BCI Control Schemes for Lower-Limb Assistive-Robots

(2018) Madiha Tariq et al.   Frontiers in Human Neuroscience

Across-subject offline decoding of motor imagery from MEG and EEG

(2018) Hanna-Leena Halme et al.   Scientific Reports

Active Physical Practice Followed by Mental Practice Using BCI-Driven Hand Exoskeleton: A Pilot Trial for Clinical Effectiveness and Usability

(2018)   IEEE Journal of Biomedical and Health Informatics

Inter-subject transfer learning with end-to-end deep convolutional neural network for EEG-based BCI

(2018) Fatemeh Fahimi et al.   Journal of Neural Engineering

An EEG-EMG correlation-based brain-computer interface for hand orthosis supported neuro-rehabilitation

(2018) Anirban Chowdhury et al.   JOURNAL OF NEUROSCIENCE METHODS

EEG classification using sparse Bayesian extreme learning machine for brain–computer interface

(2018) Zhichao Jin et al.   NEURAL COMPUTING & APPLICATIONS

Deep learning with convolutional neural networks for EEG decoding and visualization

(2017) Robin Tibor Schirrmeister et al.   HUMAN BRAIN MAPPING

A Deep Learning Scheme for Motor Imagery Classification based on Restricted Boltzmann Machines

(2017) Na Lu et al.   IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING

Feedback for reinforcement learning based brain–machine interfaces using confidence metrics

(2017) Noeline W Prins et al.   Journal of Neural Engineering

Contralesional Brain–Computer Interface Control of a Powered Exoskeleton for Motor Recovery in Chronic Stroke Survivors

(2017) David T. Bundy et al.   STROKE

Online Covariate Shift Detection based Adaptive Brain-Computer Interface to Trigger Hand Exoskeleton Feedback for Neuro-Rehabilitation

(2017) Anirban Chowdhury et al.   IEEE Transactions on Cognitive and Developmental Systems

Transfer Learning in Brain-Computer Interfaces Abstract\uFFFDThe performance of brain-computer interfaces (BCIs) improves with the amount of avail

(2016) Vinay Jayaram et al.   IEEE Computational Intelligence Magazine

A novel deep learning approach for classification of EEG motor imagery signals

(2016) Yousef Rezaei Tabar et al.   Journal of Neural Engineering

Making brain–machine interfaces robust to future neural variability

(2016) David Sussillo et al.   Nature Communications

Proof of Principle of a Brain-Computer Interface Approach to Support Poststroke Arm Rehabilitation in Hospitalized Patients: Design, Acceptability, and Usability

(2015) Giovanni Morone et al.   ARCHIVES OF PHYSICAL MEDICINE AND REHABILITATION

Leveraging anatomical information to improve transfer learning in brain–computer interfaces

(2015) Mark Wronkiewicz et al.   Journal of Neural Engineering

MEG-based neurofeedback for hand rehabilitation

(2015) Stephen T. Foldes et al.   Journal of NeuroEngineering and Rehabilitation

Evaluating Quantum Neural Network filtered motor imagery brain-computer interface using multiple classification techniques

(2015) Vaibhav Gandhi et al.   NEUROCOMPUTING

Adaptive learning with covariate shift-detection for motor imagery-based brain–computer interface

(2015) Haider Raza et al.   SOFT COMPUTING

Integrating dynamic stopping, transfer learning and language models in an adaptive zero-training ERP speller

(2014) Pieter-Jan Kindermans et al.   Journal of Neural Engineering

Using Reinforcement Learning to Provide Stable Brain-Machine Interface Control Despite Neural Input Reorganization

(2014) Eric A. Pohlmeyer et al.   PLoS One

Brain-machine interface in chronic stroke rehabilitation: A controlled study

(2013) Ander Ramos-Murguialday et al.   ANNALS OF NEUROLOGY

Online use of error-related potentials in healthy users and people with severe motor impairment increases performance of a P300-BCI

(2012) Martin Spüler et al.   CLINICAL NEUROPHYSIOLOGY

Whether generic model works for rapid ERP-based BCI calibration

(2012) Jing Jin et al.   JOURNAL OF NEUROSCIENCE METHODS

A subject transfer framework for EEG classification

(2011) Wenting Tu et al.   NEUROCOMPUTING

Multisubject Learning for Common Spatial Patterns in Motor-Imagery BCI

(2011) Dieter Devlaminck et al.   Computational Intelligence and Neuroscience

Application of Covariate Shift Adaptation Techniques in Brain–Computer Interfaces

(2010) Yan Li et al.   IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING

Regularizing Common Spatial Patterns to Improve BCI Designs: Unified Theory and New Algorithms

(2010) Fabien Lotte et al.   IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING

Toward Unsupervised Adaptation of LDA for Brain–Computer Interfaces

(2010) C Vidaurre et al.   IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING

Towards a cure for BCI illiteracy: machine learning based co-adaptive learning

(2009) Benjamin Blankertz et al.   BMC NEUROSCIENCE

Composite Common Spatial Pattern for Subject-to-Subject Transfer

(2009) Hyohyeong Kang et al.   IEEE SIGNAL PROCESSING LETTERS

Subject-independent mental state classification in single trials

(2009) Siamac Fazli et al.   NEURAL NETWORKS

Think to Move: a Neuromagnetic Brain-Computer Interface (BCI) System for Chronic Stroke

(2008) Ethan Buch et al.   STROKE