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metadata language: German

Read my Face: Automatic Facial Coding versus Psychophysiological Indicators of Emotional Valence and Arousal

Version
1
Resource Type
Dataset
Creator
  • Höfling, Tim
Publication Date
2019-12-12
Description
  • Abstract

    Facial expressions provide insight into a person’s emotional experience. There has been tremendous progress in the field of computer vision, which enables researchers to automatically decode emotional facial expressions with impressive accuracy in standardized images of prototypical basic emotions. We tested the sensitivity of a well-established automatic facial coding software program to detect spontaneous emotional reactions in individuals responding to emotional pictures. We compared automatically generated scores for valence and arousal of the Facereader (FR; Noldus Information Technology) with the current psychophysiological gold standard of measuring emotional valence (Facial Electromyography, EMG) and arousal (Skin Conductance, SC). We recorded physiological and behavioral measurements of 43 healthy participants while they looked at pleasant, unpleasant, and neutral scenes. When viewing pleasant pictures, FR Valence and EMG were both comparably sensitive. However, for unpleasant pictures, FR Valence did shows an expected negative shift, but the signal did not differentiates well between responses to neutral and unpleasant stimuli, that were distinguishable with EMG. Furthermore, FR Arousal values had a stronger correlation with self-reported valence than with arousal while SC was sensitive and specifically associated with self-reported arousal. This is the first study to systematically compare FR measurement of spontaneous emotional reactions to standardized emotional images with established psychophysiological measurement tools. This novel technology has yet to make strides to surpass the sensitivity of established psychophysiological measures. However, it provides a promising new measurement technique for non-contact assessment of emotional responses.

Data and File Information
  • Unit Type: Other
    Number of Units: 1
    • File Name: IAPS Aggregated Data ANOVA.sav
      File Format: application/octet-stream
      File Size: 45352
      Data Fingerprint: e892994a45590fa5693d9e72cd83e6f1
      Method Fingerprint: MD5
  • Unit Type: Other
    Number of Units: 1
    • File Name: IAPS Aggregated Data Correlation.sav
      File Format: application/octet-stream
      File Size: 12815
      Data Fingerprint: fa01238447d2d47b3488757c58c2b90d
      Method Fingerprint: MD5
  • Unit Type: Other
    Number of Units: 1
    • File Name: Read me.txt
      File Format: text/plain
      File Size: 3460
      Data Fingerprint: 5fa9f83c00ef327ad7340f1fb1175c16
      Method Fingerprint: MD5
Availability
Delivery

Update Metadata: 2019-12-17 | Issue Number: 1 | Registration Date: 2019-12-17

Höfling, Tim (2019): Read my Face: Automatic Facial Coding versus Psychophysiological Indicators of Emotional Valence and Arousal. Version: 1. Universitätsbibliothek Mannheim. Dataset. https://doi.org/10.7801/319