A short review and primer on electromyography in human computer interaction applications
August 29, 2016 ยท The Cartographer ยท ๐ arXiv.org
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"Title-pattern auto-detect: A short review and primer on electromyography in human computer interaction applications"
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Authors
Niklas Ravaja, Benjamin Cowley, Jari Torniainen
arXiv ID
1608.08041
Category
cs.HC: Human-Computer Interaction
Citations
2
Venue
arXiv.org
Last Checked
4 days ago
Abstract
The application of psychophysiology in human-computer interaction is a growing field with significant potential for future smart personalised systems. Working in this emerging field requires comprehension of an array of physiological signals and analysis techniques. Electromyography (EMG) is a useful signal to estimate the emotional context of individuals, because it is relatively robust, and simple to record and analyze. Common uses are to infer emotional valence in response to a stimulus, and to index some symptoms of stress. However, in order to interpret EMG signals, they must be considered alongside data on physical, social and intentional context. Here we present a short review on the application of EMG in human-computer interaction. This paper aims to serve as a primer for the novice, enabling rapid familiarisation with the latest core concepts. We put special emphasis on everyday human-computer interface applications to distinguish from the more common clinical or sports uses of psychophysiology. This paper is an extract from a comprehensive review of the entire field of ambulatory psychophysiology, including 12 similar chapters, plus application guidelines and systematic review. Thus any citation should be made using the following reference: B. Cowley, M. Filetti, K. Lukander, J. Torniainen, A. Henelius, L. Ahonen, O. Barral, I. Kosunen, T. Valtonen, M. Huotilainen, N. Ravaja, G. Jacucci. The Psychophysiology Primer: a guide to methods and a broad review with a focus on human-computer interaction. Foundations and Trends in Human-Computer Interaction, vol. 9, no. 3-4, pp. 150--307, 2016.
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