EMOTION DETECTION USING EEG SIGNALS: A SUMMARY.

Emotion detection using electroencephalogram (EEG) signals offers a groundbreaking approach to analyzing brainwaves and identifying emotional states such as happiness, sadness, and anger. By noninvasively recording electrical brain activity, EEG enables real-time study of emotions with significant a...

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Publicado en:InSight: Rivier Academic Journal Vol. 20; no. 1; pp. 1 - 16
Autores principales: B. V., Nikhil Teja, Devarapally, Yogitha, Alvakonda, Scarlet, Turlapati, Amara Jyothi, Barker, Darlien
Formato: Artículo
Publicado: Rivier College (InSight: Rivier Academic Journal) Fall2025
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Acceso en línea:Ver este registro en EBSCOhost
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          B. V., Nikhil Teja
          Devarapally, Yogitha
          Alvakonda, Scarlet
          Turlapati, Amara Jyothi
          Barker, Darlien
        affil:
          Graduate students, Computer Science Department, Rivier University
          Assistant Professor, Computer Science Department, Rivier University
      su:
        Electroencephalography
        Emotion recognition
        Affective computing
        Human-computer interaction
        Virtual reality
        Brain waves
        Neuropsychiatry
        Real-time computing
      sug:
        subj:
          Electroencephalography
          Emotion recognition
          Affective computing
          Human-computer interaction
          Virtual reality
          Brain waves
          Neuropsychiatry
          Real-time computing
      keyword:
        Affective Computing
        Brainwave Analysis
        EEG Signals
        Emotion Detection in Marketing
        Emotion Recognition
        Human-Computer Interaction
        Non-invasive Monitoring
        Realtime Emotion Detection
      ab: Emotion detection using electroencephalogram (EEG) signals offers a groundbreaking approach to analyzing brainwaves and identifying emotional states such as happiness, sadness, and anger. By noninvasively recording electrical brain activity, EEG enables real-time study of emotions with significant applications across healthcare, marketing, education, and human-computer interaction. In marketing, EEG-based tools help businesses analyze consumer reactions to create personalized strategies. In healthcare, this technology supports mental health diagnosis and tailored therapy by providing dynamic insights into patients' emotions. EEG systems also enhance human-computer interaction, enabling adaptive interfaces that respond to user' emotional states. Integrating EEG with virtual reality (VR) further expands its potential, creating immersive environments for gaming, therapy, and training that adjust dynamically to emotions. These advancements bridge neuroscience and technology, driving innovation in affective computing. The adaptability and real-time capabilities of EEG-based emotion detection systems underscore their transformative role in developing emotionally intelligent technologies. They offer continuous emotion monitoring, advancing our understanding of emotional dynamics and improving user experiences across domains. As this field progresses, EEG-based emotion recognition is poised to revolutionize interactions, fostering systems that meaningfully respond to human emotions.
      pubtype: Academic Journal
      doctype: Article
      src: R
    language: English
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