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Article

Expressure: Detect Expressions Related to Emotional and Cognitive Activities Using Forehead Textile Pressure Mechanomyography

by 1,*, 2 and 1,3
1
German Research Center for Artificial Intelligence (DFKI), 67663 Kaiserslautern, Germany
2
Department of Psychology, University of Kaiserslautern, 67663 Kaiserslautern, Germany
3
Department of Computer Science, University of Kaiserslautern, 67663 Kaiserslautern, Germany
*
Author to whom correspondence should be addressed.
Sensors 2020, 20(3), 730; https://doi.org/10.3390/s20030730
Received: 1 January 2020 / Revised: 22 January 2020 / Accepted: 24 January 2020 / Published: 28 January 2020
(This article belongs to the Special Issue Sensor Applications on Emotion Recognition)
We investigate how pressure-sensitive smart textiles, in the form of a headband, can detect changes in facial expressions that are indicative of emotions and cognitive activities. Specifically, we present the Expressure system that performs surface pressure mechanomyography on the forehead using an array of textile pressure sensors that is not dependent on specific placement or attachment to the skin. Our approach is evaluated in systematic psychological experiments. First, through a mimicking expression experiment with 20 participants, we demonstrate the system’s ability to detect well-defined facial expressions. We achieved accuracies of 0.824 to classify among three eyebrow movements (0.333 chance-level) and 0.381 among seven full-face expressions (0.143 chance-level). A second experiment was conducted with 20 participants to induce cognitive loads with N-back tasks. Statistical analysis has shown significant correlations between the Expressure features on a fine time granularity and the cognitive activity. The results have also shown significant correlations between the Expressure features and the N-back score. From the 10 most facially expressive participants, our approach can predict whether the N-back score is above or below the average with 0.767 accuracy. View Full-Text
Keywords: affective computing; smart textiles; pressure mechanomyography; facial expression; cognitive load; emotion recognition affective computing; smart textiles; pressure mechanomyography; facial expression; cognitive load; emotion recognition
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MDPI and ACS Style

Zhou, B.; Ghose, T.; Lukowicz, P. Expressure: Detect Expressions Related to Emotional and Cognitive Activities Using Forehead Textile Pressure Mechanomyography. Sensors 2020, 20, 730. https://doi.org/10.3390/s20030730

AMA Style

Zhou B, Ghose T, Lukowicz P. Expressure: Detect Expressions Related to Emotional and Cognitive Activities Using Forehead Textile Pressure Mechanomyography. Sensors. 2020; 20(3):730. https://doi.org/10.3390/s20030730

Chicago/Turabian Style

Zhou, Bo, Tandra Ghose, and Paul Lukowicz. 2020. "Expressure: Detect Expressions Related to Emotional and Cognitive Activities Using Forehead Textile Pressure Mechanomyography" Sensors 20, no. 3: 730. https://doi.org/10.3390/s20030730

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