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Psychological Responses to Stress01:20

Psychological Responses to Stress

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Psychological responses to stress encompass the various cognitive and emotional reactions individuals experience when faced with challenging or threatening situations, such as a job loss. Prolonged exposure to stressors can disturb emotional balance, increasing negative emotions (e.g., anxiety and sadness) and diminishing positive emotions (e.g., joy and satisfaction). These persistent emotional shifts are associated with an increased risk of both physical illness and mental health issues, such...
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Physiological Foundation of Stress01:24

Physiological Foundation of Stress

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Stress triggers a coordinated physiological response involving the sympathetic nervous system (SNS) and the hypothalamic-pituitary-adrenal (HPA) axis. This dual activation ensures that the body is prepared for both immediate and prolonged stress management. The process begins with the perception of a stressor. This initial phase activates the SNS, leading to the rapid release of adrenaline (epinephrine) from the adrenal glands.
Role of the Sympathetic Nervous System
Adrenaline triggers the...
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Stress and Mental Health01:30

Stress and Mental Health

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Chronic stress profoundly affects mental health, significantly influencing mood, behavior, and overall quality of life. Research closely links chronic stress with mental health conditions such as depression, anxiety, and substance use disorders. Ongoing exposure to stress can lead to physiological and psychological changes, initiating a cycle of emotional distress and maladaptive coping mechanisms.
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Stress Prevention and Stress Management Techniques II01:23

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Personality types, particularly Type A and Type B, significantly influence how individuals respond to stress. These personality distinctions are marked by varying levels of ambition, competitiveness, and coping styles, all of which shape an individual's resilience to stressors.
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Stress Prevention and Stress Management Techniques III01:25

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Regular exercise and meditation serve as essential tools in managing stress and promoting physical and mental well-being.
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Stress Prevention and Stress Management Techniques IV01:26

Stress Prevention and Stress Management Techniques IV

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Stress often leads to unhealthy habits like smoking, excessive drinking, and overeating, which offer short-term relief but ultimately increase long-term health risks. These behaviors create a cycle that temporarily lowers stress levels but can result in severe long-term health consequences. Breaking these habits is essential to reduce the risk of chronic diseases and improve overall well-being. Three primary changes that support better health include quitting smoking, reducing alcohol intake,...
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Updated: May 6, 2026

Assessing the Multiple Dimensions of Engagement to Characterize Learning: A Neurophysiological Perspective
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Un nuevo marco de aprendizaje profundo híbrido optimizado para la detección de estrés mental utilizando

Maithili Shailesh Andhare1,2, T Vijayan1, B Karthik1

  • 1Department of Electronics Communication Engineering, Bharath Institute of Higher Education and Research, Chennai 600073, India.

Brain sciences
|August 28, 2025
PubMed
Resumen
Este resumen es generado por máquina.

Este estudio presenta BDDNet, un nuevo marco de aprendizaje profundo para detectar el estrés mental a partir de electroencefalogramas (EEG). BDDNet logra una alta precisión mediante la integración de múltiples modelos de aprendizaje profundo y algoritmos de optimización para una mejor detección de estrés.

Palabras clave:
Red de creencias profundasred neuronal convolucional profundaaprendizaje profundoel comportamiento humanomemoria larga a corto plazodetección del estrés

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Área de la Ciencia:

  • La neurociencia
  • Ciencias de la computación
  • Inteligencia artificial

Sus antecedentes:

  • El estrés mental, desencadenado por varias presiones, afecta significativamente el comportamiento humano y se estudia cada vez más utilizando electroencefalogramas (EEG).
  • Los métodos de aprendizaje profundo (DL) existentes para la detección de estrés basados en EEG enfrentan desafíos como estructuras complejas, desequilibrio de clases y dificultades de procesamiento de señales.

Objetivo del estudio:

  • Presentar un nuevo marco de aprendizaje profundo híbrido, BDDNet, para mejorar la detección del estrés mental utilizando EEG.
  • Mejorar la representación espectrotemporal de las características y el análisis de la dependencia a largo plazo de las señales EEG para la detección del estrés.

Principales métodos:

  • Desarrolló BDDNet, un marco híbrido que combina una red neuronal convolucional profunda (DCNN), memoria de corto plazo bidireccional (BiLSTM) y una red de creencias profundas (DBN).
  • Utilizó múltiples características de EEG (MEF) para el análisis integral del espectro y el dominio del tiempo.
  • Empleado un algoritmo de búsqueda de cuervo mejorado (ICSA) para la selección eficiente de canales y un algoritmo de optimización de empleados (EOA) para la sintonización de hiperparámetros.

Principales resultados:

  • El marco BDDNet-ICSA demostró un rendimiento superior en el conjunto de datos públicos DEAP.
  • Logró métricas altas que incluyen 97.6% de recuperación, 97.6% de precisión, 97.6% de puntuación F1, 96.9% de selectividad, 96.9% de valor predictivo negativo (VAN) y 97.3% de precisión.
  • Superó las técnicas tradicionales de detección de estrés.

Conclusiones:

  • BDDNet ofrece una solución robusta y efectiva para la detección precisa del estrés mental a partir de los datos de EEG.
  • El enfoque de aprendizaje profundo híbrido combinado con algoritmos de optimización mejora significativamente las capacidades de detección de estrés.
  • Este marco es prometedor para avanzar en el monitoreo y manejo del estrés mental no invasivo.