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...
| Publicado en: | InSight: Rivier Academic Journal Vol. 20; no. 1; pp. 1 - 16 |
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| Autores principales: | , , , , |
| Formato: | Artículo |
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Rivier College (InSight: Rivier Academic Journal)
Fall2025
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=hlh&AN=192247932&site=ehost-live header: @attributes: shortDbName: hlh uiTerm: 192247932 longDbName: Humanities International Complete uiTag: AN controlInfo: bkinfo: jinfo: jid: 19469233 B2BS jtl: InSight: Rivier Academic Journal issn: 19469233 maglogo: N pubinfo: dt: Fall2025 vid: 20 iid: 1 pid: 59866 pub: Rivier College (InSight: Rivier Academic Journal) artinfo: ui: 192247932 ppf: 1 ppct: 15 formats: tig: atl: EMOTION DETECTION USING EEG SIGNALS: A SUMMARY. aug: au: 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 refInfo: copyright: @attributes: flag: Y dt: @attributes: year: 2025 holdings: @attributes: islocal: N |
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