Analysis of Event-Related potentials for emotion recognition

• Autorzy: Majkowski Andrzej , Kołodziej Marcin , Rak Remigiusz Jan

Identyfikatory

DOI

10.15199/48.2024.05.56

Warianty tytułu

PL

Analiza potencjałów wywołanych (ERPs) na potrzeby rozpoznawania emocji

• Języki publikacji: EN

Abstrakty

EN

The primary objective of this study was to determine the feasibility of classifying emotions into three categories (positive, negative, and neutral) using event-related potentials (ERPs) for individual users. Visual stimuli from the International Affective Picture System (IAPS) database were utilized. Various features, such as signal samples, discrete wavelet transform, discrete Fourier transform, and discrete cosine transform, were computed from one-second electroencephalographic signal (EEG) segments following the presentation of the stimulus. For the classification task, a one-nearest neighbor classifier (1-NN) was employed. The research yielded a system for preprocessing and classifying emotions. The study involved eight participants. The experiments presented in this paper demonstrate the possibility of distinguishing emotions into three categories (pleasant, unpleasant, and neutral) for a single user, achieving an average accuracy level of 87%. However, when considering all users collectively, we achieved a classification accuracy of 96%.

PL

Głównym celem artykułu było określenie możliwości klasyfikacji emocji w podziale na trzy kategorie (pozytywne, negatywne i neutralne) przy użyciu potencjałów wywołanych (ERPs) dla poszczególnych użytkowników. Wykorzystano bodźce wizualne z bazy danych International Affective Picture System (IAPS). Jako cechy zastosowano: próbki sygnału, dyskretna transformacja falkowa, dyskretna transformacja Fouriera oraz dyskretna transformacja kosinusowa, uzyskane z jednosekundowych segmentów sygnału elektroencefalograficznego (EEG) po prezentacji bodźca. Do zadania klasyfikacji zastosowano klasyfikator najbliższego sąsiada (1-NN). W wyniku prac powstał system do klasyfikowania emocji. W badaniu uczestniczyło ośmioro uczestników. Eksperymenty przedstawione w tym artykule pokazują możliwość rozróżniania emocji na trzy kategorie (przyjemne, nieprzyjemne i neutralne) dla jednego użytkownika, osiągając średni poziom dokładności 87%. Jednakże, biorąc pod uwagę wszystkich użytkowników łącznie, osiągnięto dokładność klasyfikacji na poziomie 96%.

Słowa kluczowe

EN

electroencephalography; EEG; event-related potential

PL

elektroencefalografia; EEG; potencjał związany ze zdarzeniem

• Wydawca: Wydawnictwo SIGMA-NOT
• Czasopismo: Przegląd Elektrotechniczny
• Rocznik: 2024
• Tom: R. 100, nr 5
• Strony: 290--293
• Opis fizyczny: Bibliogr. 20 poz., rys., tab.

Twórcy

autor

Majkowski Andrzej

• Warsaw University of Technology, Institute of Theory of Electrical Engineering, Measurements and Information Systems, Koszykowa 75, 00-662 Warsaw

• https://orcid.org/0000-0002-6557-836X

autor

Kołodziej Marcin

• Warsaw University of Technology, Institute of Theory of Electrical Engineering, Measurements and Information Systems, Koszykowa 75, 00-662 Warsaw

• https://orcid.org/0000-0003-2856-7298

autor

Rak Remigiusz Jan

• Warsaw University of Technology, Institute of Theory of Electrical Engineering, Measurements and Information Systems, Koszykowa 75, 00-662 Warsaw

• https://orcid.org/0000-0003-0674-453X

Bibliografia

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Uwagi

Opracowanie rekordu ze środków MNiSW, umowa nr POPUL/SP/0154/2024/02 w ramach programu "Społeczna odpowiedzialność nauki II" - moduł: Popularyzacja nauki i promocja sportu (2025).