brain-computer interface (BCI)

Improving the Performance of Individually Calibrated SSVEP Classification by Rhythmic Entrainment Source Separation
Improving the Performance of Individually Calibrated SSVEP Classification by Rhythmic Entrainment Source Separation 150 150 Transactions on Neural Systems and Rehabilitation Engineering (TNSRE)
Objective: The supervised decoding algorithms of Steady-State Visual Evoked Potentials (SSVEP) have achieved remarkable performance with sufficient training data. However, these methods have typically failed to achieve acceptable performance in… read more

FACT-Net: A Frequency Adapter CNN With Temporal-Periodicity Inception for Fast and Accurate MI-EEG Decoding
FACT-Net: A Frequency Adapter CNN With Temporal-Periodicity Inception for Fast and Accurate MI-EEG Decoding 150 150 Transactions on Neural Systems and Rehabilitation Engineering (TNSRE)
Motor imagery brain-computer interface (MI-BCI) based on non-invasive electroencephalogram (EEG) signals is a typical paradigm of BCI. However, existing decoding methods face significant challenges in terms of signal decoding accuracy,… read more

A Wearable Brain-Computer Interface With Fewer EEG Channels for Online Motor Imagery Detection
A Wearable Brain-Computer Interface With Fewer EEG Channels for Online Motor Imagery Detection 150 150 Transactions on Neural Systems and Rehabilitation Engineering (TNSRE)
Motor imagery-based brain-computer interfaces (MI-BCIs) have significant potential for neurorehabilitation and motor recovery. However, most BCI systems employ multi-channel electroencephalogram (EEG) recording devices, during which the pre-experimental preparation and post-experimental… read more

An Asynchronous Training-Free SSVEP-BCI Detection Algorithm for Non-Equal Prior Probability Scenarios
An Asynchronous Training-Free SSVEP-BCI Detection Algorithm for Non-Equal Prior Probability Scenarios 150 150 Transactions on Neural Systems and Rehabilitation Engineering (TNSRE)
SSVEP-based brain-computer interface (BCI) systems have received a lot of attention due to their relatively high Signal to Noise Ratio (SNR) and less training requirements. Most of the existing steady-state… read more

Deep Neural Network-based Empirical Mode Decomposition for Motor Imagery EEG Classification
Deep Neural Network-based Empirical Mode Decomposition for Motor Imagery EEG Classification 150 150 Transactions on Neural Systems and Rehabilitation Engineering (TNSRE)
Motor imagery refers to the brain’s response during the mental simulation of physical activities, which can be detected through electroencephalogram (EEG) signals. However, EEG signals exhibit a low signal-to-noise ratio… read more

Learning Invariant Patterns Based on a Convolutional Neural Network and Big Electroencephalography Data for Subject-Independent P300 Brain-Computer Interfaces
Author(s)3: Wei Gao, Tianyou Yu, Jin-Gang Yu, Zhenghui Gu, Kendi Li, Yong Huang, Yuanqing Li, Zhu Liang Yu
Learning Invariant Patterns Based on a Convolutional Neural Network and Big Electroencephalography Data for Subject-Independent P300 Brain-Computer Interfaces 540 430 Transactions on Neural Systems and Rehabilitation Engineering (TNSRE)

A brain-computer interface (BCI) measures and analyzes brain activity and converts this activity into computer commands to control external devices. In contrast to traditional BCIs that require a subject-specific calibration…

read more

Performance Improvement of Near-Infrared Spectroscopy-based Brain-Computer Interfaces Using Transcranial Near-Infrared Photobiomodulation with the Same Device
Author(s)3: Jinuk Kwon, Chang-Hwan Im
Performance Improvement of Near-Infrared Spectroscopy-based Brain-Computer Interfaces Using Transcranial Near-Infrared Photobiomodulation with the Same Device 548 128 Transactions on Neural Systems and Rehabilitation Engineering (TNSRE)
Transcranial near-infrared photobiomodulation (tNIR-PBM) can modulate physiological characteristics of the human brain, such as the cerebral blood flow and oxidative metabolism. Here, we investigated whether the performance of near-infrared spectroscopy (NIRS)-based brain-computer interfaces (BCIs) can be improved by tNIR-PBM applied to the prefrontal cortex with the same NIRS device. read more
A Benchmark Dataset for SSVEP-Based Brain-Computer Interfaces

A Benchmark Dataset for SSVEP-Based Brain-Computer Interfaces
Author(s)3: Yijun Wang, Xiaogang Chen, Xiaorong Gao, Shangkai Gao
A Benchmark Dataset for SSVEP-Based Brain-Computer Interfaces 691 389 Transactions on Neural Systems and Rehabilitation Engineering (TNSRE)

    This paper presents a benchmark steady-state visual evoked potential (SSVEP) dataset acquired with a 40-target brain-computer interface (BCI) speller. The dataset consists of 64-channel Electroencephalogram (EEG) data from 35…

read more
Open Access Dataset for EEG+NIRS Single-Trial Classification

Open Access Dataset for EEG+NIRS Single-Trial Classification
Author(s)3: Jaeyoung Shin, Alexander von Luhmann, Benjamin Blankertz, Do-Won Kim, Jichai Jeong, Han-Jeong Hwang, Klaus-Robert Müller
Open Access Dataset for EEG+NIRS Single-Trial Classification 780 476 Transactions on Neural Systems and Rehabilitation Engineering (TNSRE)

       We provide an open access dataset for hybrid brain-computer interfaces (BCIs) using electroencephalography (EEG) and near-infrared spectroscopy (NIRS). For this, we conducted two BCI experiments (left vs. right hand…

read more
Discriminative Manifold Learning Based Detection of Movement-Related Cortical Potentials

Discriminative Manifold Learning Based Detection of Movement-Related Cortical Potentials
Author(s)3: Chuang Lin, Bing-Hui Wang, Ning Jiang, Ren Xu, Natalie Mrachacz-Kersting, Dario Farina
Discriminative Manifold Learning Based Detection of Movement-Related Cortical Potentials 780 435 Transactions on Neural Systems and Rehabilitation Engineering (TNSRE)

The detection of voluntary motor intention from EEG has been applied to closed-loop brain–computer interfacing (BCI). The movement-related cortical potential (MRCP) is a low frequency component of the EEG signal,…

read more
Search this website