Review of EEG Affective Recognition with a Neuroscience Perspective

RY Lim, WCL Lew, KK Ang - Brain Sciences, 2024 - mdpi.com
Emotions are a series of subconscious, fleeting, and sometimes elusive manifestations of
the human innate system. They play crucial roles in everyday life—influencing the way we …

[HTML][HTML] Parallel Ictal-Net, a Parallel CNN Architecture with Efficient Channel Attention for Seizure Detection

G Hernández-Nava, S Salazar-Colores… - Sensors, 2024 - mdpi.com
Around 70 million people worldwide are affected by epilepsy, a neurological disorder
characterized by non-induced seizures that occur at irregular and unpredictable intervals …

[HTML][HTML] Evaluation of the Relation between Ictal EEG Features and XAI Explanations

SE Sánchez-Hernández, S Torres-Ramos… - Brain Sciences, 2024 - mdpi.com
Epilepsy is a neurological disease with one of the highest rates of incidence worldwide.
Although EEG is a crucial tool for its diagnosis, the manual detection of epileptic seizures is …

Detecting Psychological Interventions Using Bilateral Electromyographic Wearable Sensors

YR Veeranki, S Garcia-Retortillo, Z Papadakis… - Sensors, 2024 - mdpi.com
This study investigated the impact of auditory stimuli on muscular activation patterns using
wearable surface electromyography (EMG) sensors. Employing four key muscles …

[HTML][HTML] The Use of Generative Adversarial Network and Graph Convolution Network for Neuroimaging-Based Diagnostic Classification

N Huynh, D Yan, Y Ma, S Wu, C Long, MT Sami… - Brain Sciences, 2024 - mdpi.com
Functional connectivity (FC) obtained from resting-state functional magnetic resonance
imaging has been integrated with machine learning algorithms to deliver consistent and …

[HTML][HTML] Bimodal Transformer with Regional EEG Data for Accurate Gameplay Regularity Classification

J Lee, JH Han - Brain Sciences, 2024 - mdpi.com
As games have been applied across various fields, including education and healthcare,
numerous new games tailored to each field have emerged. Therefore, understanding user …

Decoding Subject-Driven Cognitive States from EEG Signals for Cognitive Brain–Computer Interface

D Huang, Y Wang, L Fan, Y Yu, Z Zhao, P Zeng… - Brain Sciences, 2024 - mdpi.com
In this study, we investigated the feasibility of using electroencephalogram (EEG) signals to
differentiate between four distinct subject-driven cognitive states: resting state, narrative …

[HTML][HTML] Electroencephalographic Signal Data Augmentation Based on Improved Generative Adversarial Network

X Du, X Wang, L Zhu, X Ding, Y Lv, S Qiu, Q Liu - Brain Sciences, 2024 - mdpi.com
EEG signals combined with deep learning play an important role in the study of human–
computer interaction. However, the limited dataset makes it challenging to study EEG …