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2026
Article
Subjects > Psychology
Europe University of Atlantic > Research > Articles and books
Fundación Universitaria Internacional de Colombia > Research > Articles and books
Ibero-american International University > Research > Articles and books
Ibero-american International University > Research > Articles and Books
Universidad Internacional do Cuanza > Research > Articles and books
University of La Romana > Research > Scientific Production Abierto Inglés With the growing academic pressure and competitive educational environment, students often face mental stress, which can affect their academic performance and mental health. Its accurate and timely detection and prevention is important. Traditionally, mental stress has been reported by self-assessment, which is highly subjective and can be erroneous. With advances in neuroscience, electroencephalogram (EEG) signals have been used to study brain states more objectively. EEG-based features, including time-domain, frequency-domain, and various types of connectivity features, have been used to effectively classify stress signals. However, these individual features are only able to present one aspect of the brain under stress. Several studies have combined a distinct set of features extracted from EEG signals, including time and frequency domain features, with other peripheral signals. Stress is a complex mechanism which leads to alternation in brain dynamics, its connectivity patterns and information flow. This study proposed a feature-fusion model that can effectively combine spatial features, i.e. Microstates (MS), connectivity features like Transfer Entropy (TE) and Granger Causality (GC), which provided a new neuromarker for stress classification. These features are combined with attention fusion, which enhances the discriminant features and mitigates the individual limitations within each modality. We also extracted microstates for stress-based signals. It provided a new set of microstate topomaps to study brain networks when under stress, which was not explored previously. The proposed Attention-fusion based multi-feature set is classified using Support Vector Machine, Linear Discriminant Analysis (LDA) and Multilayer Perceptron (MLP) and gave a reliable accuracy of 95.47%, 98.91%, and 83.49%, respectively. To validate the proposed method, the classification results were compared with individual and binary fusion of MS, TE and GC features, which further confirmed the robustness of the framework. This proposed feature fusion provides a more robust stress classification neuromarker, which can effectively cover the brain dynamics for accurate reporting of the underlying mental state. Ejaz, Saliha and Javed, Soyiba and Shafi, Imran and Ahmad, Jamil and Allende Monje, Samuel and Alemany Iturriaga, Josep and Choi, Jin-Ghoo and Ashraf, Imran UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, samuel.allende@uneatlantico.es, josep.alemany@uneatlantico.es, UNSPECIFIED, UNSPECIFIED
Fundación Universitaria Internacional de Colombia > Research > Articles and books
Ibero-american International University > Research > Articles and books
Ibero-american International University > Research > Articles and Books
Universidad Internacional do Cuanza > Research > Articles and books
University of La Romana > Research > Scientific Production Abierto Inglés With the growing academic pressure and competitive educational environment, students often face mental stress, which can affect their academic performance and mental health. Its accurate and timely detection and prevention is important. Traditionally, mental stress has been reported by self-assessment, which is highly subjective and can be erroneous. With advances in neuroscience, electroencephalogram (EEG) signals have been used to study brain states more objectively. EEG-based features, including time-domain, frequency-domain, and various types of connectivity features, have been used to effectively classify stress signals. However, these individual features are only able to present one aspect of the brain under stress. Several studies have combined a distinct set of features extracted from EEG signals, including time and frequency domain features, with other peripheral signals. Stress is a complex mechanism which leads to alternation in brain dynamics, its connectivity patterns and information flow. This study proposed a feature-fusion model that can effectively combine spatial features, i.e. Microstates (MS), connectivity features like Transfer Entropy (TE) and Granger Causality (GC), which provided a new neuromarker for stress classification. These features are combined with attention fusion, which enhances the discriminant features and mitigates the individual limitations within each modality. We also extracted microstates for stress-based signals. It provided a new set of microstate topomaps to study brain networks when under stress, which was not explored previously. The proposed Attention-fusion based multi-feature set is classified using Support Vector Machine, Linear Discriminant Analysis (LDA) and Multilayer Perceptron (MLP) and gave a reliable accuracy of 95.47%, 98.91%, and 83.49%, respectively. To validate the proposed method, the classification results were compared with individual and binary fusion of MS, TE and GC features, which further confirmed the robustness of the framework. This proposed feature fusion provides a more robust stress classification neuromarker, which can effectively cover the brain dynamics for accurate reporting of the underlying mental state. Ejaz, Saliha and Javed, Soyiba and Shafi, Imran and Ahmad, Jamil and Allende Monje, Samuel and Alemany Iturriaga, Josep and Choi, Jin-Ghoo and Ashraf, Imran UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, samuel.allende@uneatlantico.es, josep.alemany@uneatlantico.es, UNSPECIFIED, UNSPECIFIED
Attention-based multi-feature fusion neuromarker for EEG-driven stress classification in learners.
Article
Subjects > Psychology
Subjects > Nutrition Europe University of Atlantic > Research > Articles and books
Ibero-american International University > Research > Articles and books
Universidad Internacional do Cuanza > Research > Articles and books
University of La Romana > Research > Scientific Production Abierto Español Introducción: la neuroinflamación crónica de bajo grado y la disfunción del eje intestino-cerebro constituyen mecanismos centrales en la fisiopatología del trastorno del espectro autista (TEA). La curcumina, un polifenol derivado de Curcuma longa, presenta propiedades antiinflamatorias, antioxidantes y neuroinmunomoduladoras que podrían tener un impacto terapéutico en esta población. Objetivos: evaluar los efectos de la suplementación con curcumina sobre la inflamación sistémica, la regulación del procesamiento sensorial y los trastornos de la interacción intestino-cerebro en niños con TEA. Métodos: se realizó un ensayo clínico aleatorizado, doble ciego y controlado con placebo en 60 niños con TEA durante ocho semanas. Los participantes fueron asignados a recibir curcumina (3.000 mg/día) o placebo. Se evaluaron como variables principales la proteína C reactiva ultrasensible (PCR-us), la velocidad de sedimentación globular (VSG) y la calprotectina fecal. Como variables secundarias, se analizaron el Índice General de Disfunción de la Regulación del Procesamiento Sensorial (IGDRPS) y los criterios Roma IV para trastornos de la interacción intestino-cerebro. Resultados: el grupo tratado con curcumina presentó reducciones significativas en PCR-us (-83,8 %), VSG (-42,3 %) y calprotectina fecal (-73,7 %), junto con una mejoría del 49 % en el IGDRPS y resolución de los síntomas gastrointestinales en el 90 % de los casos (p < 0,001). No se registraron eventos adversos durante la intervención. Conclusiones: la suplementación con curcumina atenúa la inflamación sistémica y entérica, mejora la regulación sensorial y reduce los trastornos funcionales gastrointestinales en niños con TEA, posicionándose como una alternativa coadyuvante segura, accesible y de bajo costo dentro de un abordaje integrativo. Vergara Serpa, Juan José and Sumalla Cano, Sandra UNSPECIFIED, sandra.sumalla@uneatlantico.es
Subjects > Nutrition Europe University of Atlantic > Research > Articles and books
Ibero-american International University > Research > Articles and books
Universidad Internacional do Cuanza > Research > Articles and books
University of La Romana > Research > Scientific Production Abierto Español Introducción: la neuroinflamación crónica de bajo grado y la disfunción del eje intestino-cerebro constituyen mecanismos centrales en la fisiopatología del trastorno del espectro autista (TEA). La curcumina, un polifenol derivado de Curcuma longa, presenta propiedades antiinflamatorias, antioxidantes y neuroinmunomoduladoras que podrían tener un impacto terapéutico en esta población. Objetivos: evaluar los efectos de la suplementación con curcumina sobre la inflamación sistémica, la regulación del procesamiento sensorial y los trastornos de la interacción intestino-cerebro en niños con TEA. Métodos: se realizó un ensayo clínico aleatorizado, doble ciego y controlado con placebo en 60 niños con TEA durante ocho semanas. Los participantes fueron asignados a recibir curcumina (3.000 mg/día) o placebo. Se evaluaron como variables principales la proteína C reactiva ultrasensible (PCR-us), la velocidad de sedimentación globular (VSG) y la calprotectina fecal. Como variables secundarias, se analizaron el Índice General de Disfunción de la Regulación del Procesamiento Sensorial (IGDRPS) y los criterios Roma IV para trastornos de la interacción intestino-cerebro. Resultados: el grupo tratado con curcumina presentó reducciones significativas en PCR-us (-83,8 %), VSG (-42,3 %) y calprotectina fecal (-73,7 %), junto con una mejoría del 49 % en el IGDRPS y resolución de los síntomas gastrointestinales en el 90 % de los casos (p < 0,001). No se registraron eventos adversos durante la intervención. Conclusiones: la suplementación con curcumina atenúa la inflamación sistémica y entérica, mejora la regulación sensorial y reduce los trastornos funcionales gastrointestinales en niños con TEA, posicionándose como una alternativa coadyuvante segura, accesible y de bajo costo dentro de un abordaje integrativo. Vergara Serpa, Juan José and Sumalla Cano, Sandra UNSPECIFIED, sandra.sumalla@uneatlantico.es
Curcumina en niños con trastorno del espectro autista: inflamación sistémica, regulación sensorial y trastornos de la interacción intestino-cerebro. Ensayo clínico aleatorizado, doble ciego y controlado con placebo (CURATEA).
This list was generated on Fri Aug 14 02:00:51 2026 UTC.