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      DEAP: A Database for Emotion Analysis ;Using Physiological Signals

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          Abstract

          IEEE Transactions on Affective Computing, 3(1), 18-31

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          Most cited references40

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          Autonomic nervous system activity in emotion: A review

          Autonomic nervous system (ANS) activity is viewed as a major component of the emotion response in many recent theories of emotion. Positions on the degree of specificity of ANS activation in emotion, however, greatly diverge, ranging from undifferentiated arousal, over acknowledgment of strong response idiosyncrasies, to highly specific predictions of autonomic response patterns for certain emotions. A review of 134 publications that report experimental investigations of emotional effects on peripheral physiological responding in healthy individuals suggests considerable ANS response specificity in emotion when considering subtypes of distinct emotions. The importance of sound terminology of investigated affective states as well as of choice of physiological measures in assessing ANS reactivity is discussed. Copyright © 2010 Elsevier B.V. All rights reserved.
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            A survey of affect recognition methods: audio, visual, and spontaneous expressions.

            Automated analysis of human affective behavior has attracted increasing attention from researchers in psychology, computer science, linguistics, neuroscience, and related disciplines. However, the existing methods typically handle only deliberately displayed and exaggerated expressions of prototypical emotions despite the fact that deliberate behaviour differs in visual appearance, audio profile, and timing from spontaneously occurring behaviour. To address this problem, efforts to develop algorithms that can process naturally occurring human affective behaviour have recently emerged. Moreover, an increasing number of efforts are reported toward multimodal fusion for human affect analysis including audiovisual fusion, linguistic and paralinguistic fusion, and multi-cue visual fusion based on facial expressions, head movements, and body gestures. This paper introduces and surveys these recent advances. We first discuss human emotion perception from a psychological perspective. Next we examine available approaches to solving the problem of machine understanding of human affective behavior, and discuss important issues like the collection and availability of training and test data. We finally outline some of the scientific and engineering challenges to advancing human affect sensing technology.
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              Detecting Stress During Real-World Driving Tasks Using Physiological Sensors

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                Author and article information

                Journal
                Institute of Electrical and Electronics Engineers (IEEE)
                2012
                January 2012
                11 June 2019
                Article
                10.1109/T-AFFC.2011.15
                4e2581c8-b758-4d03-a152-b1f6a505f2cf
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