Electroencephalogram (EEG)

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

Spatiotemporal Dynamics of Periodic and Aperiodic Brain Activity Under Peripheral Nerve Stimulation With Acupuncture
Spatiotemporal Dynamics of Periodic and Aperiodic Brain Activity Under Peripheral Nerve Stimulation With Acupuncture 150 150 Transactions on Neural Systems and Rehabilitation Engineering (TNSRE)
Brain activities are a mixture of periodic and aperiodic components, manifesting in the power spectral density (PSD) as rhythmic oscillations with spectral peaks and broadband fluctuations. Periodic oscillatory properties of… read more

Multimodal Emotion Recognition Based on EEG and EOG Signals Evoked by the Video-Odor Stimuli
Multimodal Emotion Recognition Based on EEG and EOG Signals Evoked by the Video-Odor Stimuli 150 150 Transactions on Neural Systems and Rehabilitation Engineering (TNSRE)
Affective data is the basis of emotion recognition, which is mainly acquired through extrinsic elicitation. To investigate the enhancing effects of multi-sensory stimuli on emotion elicitation and emotion recognition, we… read more

EEG-Based Brain Functional Network Analysis for Differential Identification of Dementia-Related Disorders and Their Onset
EEG-Based Brain Functional Network Analysis for Differential Identification of Dementia-Related Disorders and Their Onset 150 150 Transactions on Neural Systems and Rehabilitation Engineering (TNSRE)
Diagnosing and treating dementia, including mild cognitive impairment (MCI), is challenging due to diverse disease types and overlapping symptoms. Early MCI detection is vital as it can precede dementia, yet… read more
Comparison of average ERD/ERS of younger and older participants in the alpha-beta frequency band (8–26 Hz).

Age-Related Changes in Vibro-Tactile EEG Response and Its Implications in BCI Applications: A Comparison Between Older and Younger Populations
Author(s)3: Mei Lin Chen, Dannie Fu, Jennifer Boger, Ning Jiang
Age-Related Changes in Vibro-Tactile EEG Response and Its Implications in BCI Applications: A Comparison Between Older and Younger Populations 780 435 Transactions on Neural Systems and Rehabilitation Engineering (TNSRE)

    The rapid increase in the number of older adults around the world is accelerating research in applications to support age-related conditions, such as brain–computer interface (BCI) applications for post-stroke…

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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…

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Imagined Hand Clenching Force and Speed Modulate Brain Activity and Are Classified by NIRS Combined With EEG

Imagined Hand Clenching Force and Speed Modulate Brain Activity and Are Classified by NIRS Combined With EEG
Author(s)3: Yunfa Fu, Xin Xiong, Changhao Jiang, Baolei Xu, Yongcheng Li, Hongyi Li
Imagined Hand Clenching Force and Speed Modulate Brain Activity and Are Classified by NIRS Combined With EEG 780 303 Transactions on Neural Systems and Rehabilitation Engineering (TNSRE)

      Simultaneous acquisition of brain activity signals from the sensorimotor area using NIRS combined with EEG, imagined hand clenching force and speed modulation of brain activity, as well as 6-class…

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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,…

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Evaluate the feasibility of using frontal SSVEP to implement an SSVEP – based BCI in Young, Elderly and ALS groups
Author(s)3: Hao-Teng Hsu, I-Hui Lee, Han-Ting Tsai, Chun-Yen Chang, Hsiang-Chih Chang, Chuan-Chih Hsu, Kuo-Kai Shyu, Hsiao-Huang Chang, Ting-Kuang Yeh, Po-Lei Lee
Evaluate the feasibility of using frontal SSVEP to implement an SSVEP – based BCI in Young, Elderly and ALS groups 780 310 Transactions on Neural Systems and Rehabilitation Engineering (TNSRE)

This paper studied the amplitude-frequency characteristic of frontal steady-state visual evoked potential (SSVEP) and its feasibility as a control signal for brain computer interface (BCI). SSVEPs induced by different stimulation…

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FORCe: Fully Online and Automated Artifact Removal for Brain-Computer Interfacing
Author(s)3: Ian Daly, Reinhold Scherer, Martin Billinger, Gernot Muller-Putz
FORCe: Fully Online and Automated Artifact Removal for Brain-Computer Interfacing 780 858 Transactions on Neural Systems and Rehabilitation Engineering (TNSRE)

A fully automated and online artifact removal method for the electroencephalogram (EEG) is developed for use in braincomputer interfacing (BCI). The method (FORCe) is based upon a novel combination of…

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