Electroencephalography

Learning Spatial–Spectral–Temporal EEG Features With Recurrent 3D Convolutional Neural Networks for Cross-Task Mental Workload Assessment

Learning Spatial–Spectral–Temporal EEG Features With Recurrent 3D Convolutional Neural Networks for Cross-Task Mental Workload Assessment
Author(s)3: Pengbo Zhang, Xue Wang, Weihang Zhang, Junfeng Chen
Learning Spatial–Spectral–Temporal EEG Features With Recurrent 3D Convolutional Neural Networks for Cross-Task Mental Workload Assessment 780 395 Transactions on Neural Systems and Rehabilitation Engineering (TNSRE)

    Mental workload assessment is essential for maintaining human health and preventing accidents. Most research on this issue is limited to a single task. However, cross-task assessment is indispensable for…

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Unimanual Versus Bimanual Motor Imagery

Unimanual vs Bimanual Motor Imagery Classifiers for Assistive and Rehabilitative Brain Computer Interfaces
Author(s)3: Vuckovic Aleksandra, Pangaro Sara, Putri Finda
Unimanual vs Bimanual Motor Imagery Classifiers for Assistive and Rehabilitative Brain Computer Interfaces 780 435 Transactions on Neural Systems and Rehabilitation Engineering (TNSRE)

   Bimanual movements are an integral part of everyday activities and are often included in rehabilitation therapies. Yet electroencephalography (EEG) based assistive and rehabilitative brain computer interface (BCI) systems typically…

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simBCI – A framework for studying BCI methods by simulated EEG
Author(s)3: Jussi T. Lindgren, Adrien Merlini, Anatole Lecuyer, Francesco P. Andriulli
simBCI – A framework for studying BCI methods by simulated EEG 367 281 Transactions on Neural Systems and Rehabilitation Engineering (TNSRE)

Brain-Computer Interface (BCI) methods are commonly studied using Electroencephalogram (EEG) data recorded from human experiments. For understanding and developing BCI signal processing techniques real data is costly to obtain and…

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The results of significant and correlation analysis in Delta frequency band.

Magnitude Squared Coherence Method based on Weighted Canonical Correlation Analysis for EEG Synchronization Analysis in Amnesic Mild Cognitive Impairment of Diabetes Mellitus
Author(s)3: Dong Cui, Shunai Qi, Guanghua Gu, Xiaoli Li, Zhaohui Li, Lei Wang, Shimin Yin
Magnitude Squared Coherence Method based on Weighted Canonical Correlation Analysis for EEG Synchronization Analysis in Amnesic Mild Cognitive Impairment of Diabetes Mellitus 538 426 Transactions on Neural Systems and Rehabilitation Engineering (TNSRE)

       Type 2 diabetes mellitus (T2DM) increases the risk of amnestic mild cognitive impairment (aMCI) and Alzheimer’s disease(AD). aMCI is the transitory stage from normal cognition to AD, which seriously…

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Mixed Neural Network Approach for Temporal Sleep Stage Classification
Author(s)3: Hao Dong, Akara Supratak, Wei Pan, Chao Wu, Paul M. Matthews, Yike Guo
Mixed Neural Network Approach for Temporal Sleep Stage Classification 780 1165 Transactions on Neural Systems and Rehabilitation Engineering (TNSRE)

      This paper proposes a practical approach to addressing limitations posed by using of single-channel electroencephalography (EEG) for sleep stage classification. EEG-based characterizations of sleep stage progression contribute the diagnosis…

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Quantitative Evaluation of a Low-Cost Noninvasive Hybrid Interface Based on EEG and Eye Movement

Quantitative Evaluation of a Low-Cost Noninvasive Hybrid Interface Based on EEG and Eye Movement
Author(s)3: Minho Kim, Byung Hyung Kim, Sungho Jo
Quantitative Evaluation of a Low-Cost Noninvasive Hybrid Interface Based on EEG and Eye Movement 556 235 Transactions on Neural Systems and Rehabilitation Engineering (TNSRE)

Abstract This paper describes a low-cost noninvasive brain-computer interface (BCI) hybridized with eye tracking. It also discusses its feasibility through a Fitts’ law-based quantitative evaluation method. Noninvasive BCI has recently…

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