Emotion detection using noninvasive low cost sensors

Emotion recognition from biometrics is relevant to a wide range of application domains, including healthcare. Existing approaches usually adopt multi-electrodes sensors that could be expensive or uncomfortable to be used in real-life situations. In this study, we investigate whether we can reliably...

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Bibliographic Details
Published inInternational Conference on Affective Computing and Intelligent Interaction and workshops pp. 125 - 130
Main Authors Girardi, Daniela, Lanubile, Filippo, Novielli, Nicole
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.10.2017
Subjects
Brain modeling
Electrodes
Electroencephalography
Electromyography
Emotion recognition
Sensors
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Summary:Emotion recognition from biometrics is relevant to a wide range of application domains, including healthcare. Existing approaches usually adopt multi-electrodes sensors that could be expensive or uncomfortable to be used in real-life situations. In this study, we investigate whether we can reliably recognize high vs. low emotional valence and arousal by relying on noninvasive low cost EEG, EMG, and GSR sensors. We report the results of an empirical study involving 19 subjects. We achieve state-of-the-art classification performance for both valence and arousal even in a cross-subject classification setting, which eliminates the need for individual training and tuning of classification models.
ISSN:2156-8111
DOI:10.1109/ACII.2017.8273589