OOIR: Observatory of International Research

Papers

(The H4-Index of IEEE Transactions on Neural Systems and Rehabilitation Engineering is 45. The table below lists those papers that are above that threshold based on CrossRef citation counts [max. 250 papers]. The publications cover those that have been published in the past four years, i.e., from 2020-05-01 to 2024-05-01.)

Article	Citations
An Attention-Based Deep Learning Approach for Sleep Stage Classification With Single-Channel EEG	249
Brain-Controlled Robotic Arm System Based on Multi-Directional CNN-BiLSTM Network Using EEG Signals	186
A Computerized Method for Automatic Detection of Schizophrenia Using EEG Signals	113
Performance Evaluation of Lower Limb Exoskeletons: A Systematic Review	107
Multi-View Spatial-Temporal Graph Convolutional Networks With Domain Generalization for Sleep Stage Classification	105
Manifold Embedded Knowledge Transfer for Brain-Computer Interfaces	98
Transcutaneous Spinal Cord Stimulation Restores Hand and Arm Function After Spinal Cord Injury	96
Bispectrum-Based Channel Selection for Motor Imagery Based Brain-Computer Interfacing	94
A New Framework for Automatic Detection of Patients With Mild Cognitive Impairment Using Resting-State EEG Signals	86
Improving the Performance of Individually Calibrated SSVEP-BCI by Task- Discriminant Component Analysis	81
FS-HGR: Few-Shot Learning for Hand Gesture Recognition via Electromyography	73
Wearable Assistive Tactile Communication Interface Based on Integrated Touch Sensors and Actuators	70
Learning Common Time-Frequency-Spatial Patterns for Motor Imagery Classification	69
A Multi-Scale Fusion Convolutional Neural Network Based on Attention Mechanism for the Visualization Analysis of EEG Signals Decoding	69
Detecting High-Functioning Autism in Adults Using Eye Tracking and Machine Learning	68
Physics-Informed Deep Learning for Musculoskeletal Modeling: Predicting Muscle Forces and Joint Kinematics From Surface EMG	68
A Temporal-Spectral-Based Squeeze-and- Excitation Feature Fusion Network for Motor Imagery EEG Decoding	67
Neural Decoding of Imagined Speech and Visual Imagery as Intuitive Paradigms for BCI Communication	67
Dreem Open Datasets: Multi-Scored Sleep Datasets to Compare Human and Automated Sleep Staging	64
How Sensitive Are EEG Results to Preprocessing Methods: A Benchmarking Study	64
Combination of Augmented Reality Based Brain- Computer Interface and Computer Vision for High-Level Control of a Robotic Arm	61
A Transformer-Based Approach Combining Deep Learning Network and Spatial-Temporal Information for Raw EEG Classification	60
Design and Experimental Evaluation of a Semi-Passive Upper-Limb Exoskeleton for Workers With Motorized Tuning of Assistance	60
Computer Vision to Automatically Assess Infant Neuromotor Risk	58
RobustSleepNet: Transfer Learning for Automated Sleep Staging at Scale	57

Enhancing EEG-Based Classification of Depression Patients Using Spatial Information	56
Observing Actions Through Immersive Virtual Reality Enhances Motor Imagery Training	56
Motor Imagery EEG Decoding Method Based on a Discriminative Feature Learning Strategy	56
Speech Vision: An End-to-End Deep Learning-Based Dysarthric Automatic Speech Recognition System	55
Brain Functional Networks Based on Resting-State EEG Data for Major Depressive Disorder Analysis and Classification	55
Symbitron Exoskeleton: Design, Control, and Evaluation of a Modular Exoskeleton for Incomplete and Complete Spinal Cord Injured Individuals	54
EEG-Inception: A Novel Deep Convolutional Neural Network for Assistive ERP-Based Brain-Computer Interfaces	54
An Effective Dual Self-Attention Residual Network for Seizure Prediction	53
Seizure Prediction Using Directed Transfer Function and Convolution Neural Network on Intracranial EEG	53
DeepSleepNet-Lite: A Simplified Automatic Sleep Stage Scoring Model With Uncertainty Estimates	51
Deep Temporal-Spatial Feature Learning for Motor Imagery-Based Brain–Computer Interfaces	51
Inter- and Intra-Subject Transfer Reduces Calibration Effort for High-Speed SSVEP-Based BCIs	51
Different Set Domain Adaptation for Brain-Computer Interfaces: A Label Alignment Approach	50
Motor Imagery Hand Movement Direction Decoding Using Brain Computer Interface to Aid Stroke Recovery and Rehabilitation	49
An Improved Performance of Deep Learning Based on Convolution Neural Network to Classify the Hand Motion by Evaluating Hyper Parameter	48
Self-Aligning Mechanism Improves Comfort and Performance With a Powered Knee Exoskeleton	48
Enhanced Motor Imagery Based Brain- Computer Interface via FES and VR for Lower Limbs	47
Open Access Dataset, Toolbox and Benchmark Processing Results of High-Density Surface Electromyogram Recordings	47
EEG Conformer: Convolutional Transformer for EEG Decoding and Visualization	47
Dynamic Joint Domain Adaptation Network for Motor Imagery Classification	46
Convolutional Correlation Analysis for Enhancing the Performance of SSVEP-Based Brain-Computer Interface	45