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  4. The emotive couch - learning emotions by capacitively sensed movements
 
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2018
Journal Article
Title

The emotive couch - learning emotions by capacitively sensed movements

Abstract
Affective computing allows machines to simulate and detect emotional states. The most common method is the observation of the face by camera. However, in our increasingly observed society, more privacy-aware methods are worth exploring that do not require facial images, but instead look at other physiological indicators of emotion. In this work we present the Emotive Couch, a sensor-augmented piece of smart furniture that detects proximity and motion of the human body. We present the design rationale and use standard machine learning techniques to detect the three basic emotions Anxiety, Interest, and Relaxation. We evaluate the performance of our approach with 15 participants in a study that includes various affect elicitation methods, achieving an accuracy of 77.7 %.
Author(s)
Rus, Silvia
Fraunhofer-Institut für Graphische Datenverarbeitung IGD  
Joshi, Dhanashree Jayant
TU Darmstadt
Braun, Andreas
Fraunhofer-Institut für Graphische Datenverarbeitung IGD  
Kuijper, Arjan  orcid-logo
Fraunhofer-Institut für Graphische Datenverarbeitung IGD  
Journal
Procedia computer science  
Conference
International Conference on Ambient Systems, Networks and Technologies (ANT) 2018  
International Conference on Sustainable Energy Information Technology (SEIT) 2018  
Open Access
DOI
10.1016/j.procs.2018.04.038
Language
English
Fraunhofer-Institut für Graphische Datenverarbeitung IGD  
Keyword(s)
  • Lead Topic: Smart City

  • Research Line: Human computer interaction (HCI)

  • affective computing

  • emotion detection

  • capacitive proximity sensing

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