[HTML][HTML] Investigating the Impact of Guided Imagery on Stress, Brain Functions, and Attention: A Randomized Trial
K Zemla, G Sedek, K Wróbel, F Postepski, GM Wojcik - Sensors, 2023 - mdpi.com
The aim of this study was to investigate the potential impact of guided imagery (GI) on
attentional control and cognitive performance and to explore the relationship between …
attentional control and cognitive performance and to explore the relationship between …
EEG-based motor imagery channel selection and classification using hybrid optimization and two-tier deep learning
Brain–computer interface (BCI) technology holds promise for individuals with profound
motor impairments, offering the potential for communication and control. Motor imagery (MI) …
motor impairments, offering the potential for communication and control. Motor imagery (MI) …
Optimal Fuzzy Logic Enabled EEG Motor Imagery Classification for Brain Computer Interface
Brain-computer interface BCI) is a technology that assists in straight link among the human
brain as well as external devices like computers or robotic systems, without including …
brain as well as external devices like computers or robotic systems, without including …
A prototypical network for few-shot recognition of speech imagery data
A Hernandez-Galvan, G Ramirez-Alonso… - … Signal Processing and …, 2023 - Elsevier
Speech imagery (SI) is a Brain-Computer Interface (BCI) paradigm based on EEG signals
analysis where the user imagines speaking out a vowel, phoneme, syllable, or word without …
analysis where the user imagines speaking out a vowel, phoneme, syllable, or word without …
[HTML][HTML] Kernel-based regularized EEGNet using centered alignment and Gaussian connectivity for motor imagery discrimination
M Tobón-Henao, AM Álvarez-Meza… - Computers, 2023 - mdpi.com
Brain–computer interfaces (BCIs) from electroencephalography (EEG) provide a practical
approach to support human–technology interaction. In particular, motor imagery (MI) is a …
approach to support human–technology interaction. In particular, motor imagery (MI) is a …
Subject-independent deep architecture for EEG-based motor imagery classification
Motor imagery (MI) classification based on electroencephalogram (EEG) is a widely-used
technique in non-invasive brain-computer interface (BCI) systems. Since EEG recordings …
technique in non-invasive brain-computer interface (BCI) systems. Since EEG recordings …
Leveraging Temporal Dependency for Cross-subject-MI BCIs by Contrastive Learning and Self-attention
Brain-computer interfaces (BCIs) built based on motor imagery paradigm have found
extensive utilization in motor rehabilitation and the control of assistive applications …
extensive utilization in motor rehabilitation and the control of assistive applications …
A parallel-hierarchical neural network (PHNN) for motor imagery EEG signal classification
K Lu, H Guo, Z Gu, F Qi, S Kuang, L Sun - Biomedical Signal Processing …, 2024 - Elsevier
Motor imagery brain-computer interfaces (MI-BCIs) play a crucial role in fields such as robot
control and stroke rehabilitation. With the flourishing development of deep learning, there …
control and stroke rehabilitation. With the flourishing development of deep learning, there …
[HTML][HTML] Dynamic pruning group equivariant network for motor imagery EEG recognition
X Tang, W Zhang, H Wang, T Wang, C Tan… - … in Bioengineering and …, 2023 - frontiersin.org
Introduction: The decoding of the motor imaging electroencephalogram (MI-EEG) is the most
critical part of the brain-computer interface (BCI) system. However, the inherent complexity of …
critical part of the brain-computer interface (BCI) system. However, the inherent complexity of …
[HTML][HTML] Gender difference in functional activity of 4-months-old infants during sleep: A functional near-infrared spectroscopy study
K Wang, X Ji, T Li - Frontiers in Psychiatry, 2023 - frontiersin.org
Sex differences emerge early in infancy. A number of earlier studies have investigated the
resting-state network of infant sleep states, and there have been many studies using …
resting-state network of infant sleep states, and there have been many studies using …