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2019 | OriginalPaper | Buchkapitel

ECG-Based Human Emotion Recognition Across Multiple Subjects

verfasst von : Desislava Nikolova, Petia Mihaylova, Agata Manolova, Petia Georgieva

Erschienen in: Future Access Enablers for Ubiquitous and Intelligent Infrastructures

Verlag: Springer International Publishing

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Abstract

Electrocardiogram (ECG) based affective computing is a new research field that aims to find correlates between human emotions and the registered ECG signals. Typically, emotion recognition systems are personalized, i.e. the discrimination models are subject-dependent. Building subject-independent models is a harder problem due to the high ECG variability between individuals. In this paper, we study the potential of two machine learning methods (Logistic Regression and Artificial Neural Network) to discriminate human emotional states across multiple subjects. The users were exposed to movies with different emotional content (neutral, fear, disgust) and their ECG activity was registered. Based on extracted features from the ECG recordings, the three emotional states were partially discriminated.

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Literatur
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Metadaten
Titel
ECG-Based Human Emotion Recognition Across Multiple Subjects
verfasst von
Desislava Nikolova
Petia Mihaylova
Agata Manolova
Petia Georgieva
Copyright-Jahr
2019
DOI
https://doi.org/10.1007/978-3-030-23976-3_3