Brain Computer Interface: Deep Learning Approach to Predict Human Emotion Recognition Article Swipe
Carmelo Ardito
,
Ilaria Bortone
,
Tommaso Colafiglio
,
Tommaso Di Noia
,
Eugenio Di Sciascio
,
Domenico Lofù
,
Fedelucio Narducci
,
Rodolfo Sardone
,
Paolo Sorino
·
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.1109/smc53654.2022.9945554
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.1109/smc53654.2022.9945554
Brain-Computer Interfaces allow controlling machines through signals coming from Electroencephalography (EEG) analysis. Nowadays, there are several cheap electroencephalographs available on the market that guarantee good quality EEG signals. A very interesting approach in this area is related to detecting the emotional states of a user through the analysis of her EEG signal. In our study, we tried to detect the emotional polarity (Valence), the state of emotional excitement (Arousal), and the level of emotion control (Dominance). Through metric interpolation and Russell's circumplex model, it is possible to characterize and define the current emotional state of the user who wears the device. Our study presents a prototype of an EEG-based emotion recognizer that provides the user's emotional state exploitable as bio-feedback.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1109/smc53654.2022.9945554
- OA Status
- green
- Cited By
- 14
- References
- 44
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4309374825
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4309374825Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1109/smc53654.2022.9945554Digital Object Identifier
- Title
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Brain Computer Interface: Deep Learning Approach to Predict Human Emotion RecognitionWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2022Year of publication
- Publication date
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2022-10-09Full publication date if available
- Authors
-
Carmelo Ardito, Ilaria Bortone, Tommaso Colafiglio, Tommaso Di Noia, Eugenio Di Sciascio, Domenico Lofù, Fedelucio Narducci, Rodolfo Sardone, Paolo SorinoList of authors in order
- Landing page
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https://doi.org/10.1109/smc53654.2022.9945554Publisher landing page
- Open access
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YesWhether a free full text is available
- OA status
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greenOpen access status per OpenAlex
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https://hdl.handle.net/11573/1699400Direct OA link when available
- Concepts
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Electroencephalography, Computer science, Valence (chemistry), Arousal, Emotion recognition, Brain–computer interface, Artificial intelligence, Feature extraction, Emotional valence, Human–computer interaction, Speech recognition, Psychology, Cognition, Neuroscience, Quantum mechanics, PhysicsTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
14Total citation count in OpenAlex
- Citations by year (recent)
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2025: 3, 2024: 7, 2023: 3, 2022: 1Per-year citation counts (last 5 years)
- References (count)
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44Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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