Physiological Signal Analysis for Automatic Emotion Recognition in Humans

Student: Demochkina Polina

Faculty: Faculty of Informatics, Mathematics, and Computer Science (HSE Nizhny Novgorod)

Educational Programme: Data Mining (Master)

Year of Graduation: 2024

In this work, a comprehensive literature review on the subject of emotion recognition was conducted, and a new multimodal approach for recognizing emotions through the analysis of ECG and EEG signals was developed. Experimental results on the DREAMER dataset showed that the proposed method improves the baseline method by 22.5% for both valence and arousal, and achieves accuracy comparable to the best-known techniques, in addition to being adaptable for real-time applications.

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