Affective Man-Machine Interface: Unveiling human emotions through biosignals


Broek, Egon L. van den and Lisy, Viliam and Janssen, Joris H. and Westerink, Joyce H.D.M. and Schut, Marleen H. and Tuinenbreijer, Kees (2010) Affective Man-Machine Interface: Unveiling human emotions through biosignals. In: A. Fred & J. Filipe & H. Gamboa (Eds.), Biomedical Engineering Systems and Technologies. Communications in Computer and Information Science, 52 (Part 1). Springer Verlag, Berlin, pp. 21-47. ISBN 9783642117206

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Abstract:As is known for centuries, humans exhibit an electrical profile. This profile is altered through various psychological and physiological processes, which can be measured through biosignals; e.g., electromyography (EMG) and electrodermal activity (EDA). These biosignals can reveal our emotions and, as such, can serve as an advanced man-machine interface (MMI) for empathic consumer products. However, such a MMI requires the correct classification of biosignals to emotion classes. This chapter starts with an introduction on biosignals for emotion detection. Next, a state-of-the-art review is presented on automatic emotion classification. Moreover, guidelines are presented for affective MMI. Subsequently, a research is presented that explores the use of EDA and three facial EMG signals to determine neutral, positive, negative, and mixed emotions, using recordings of 21 people. A range of techniques is tested, which resulted in a generic framework for automated emotion classification with up to 61.31% correct classification of the four emotion classes, without the need of personal profiles. Among various other directives for future research, the results emphasize the need for parallel processing of multiple biosignals.
Item Type:Book Section
Copyright:© 2010 Springer
Electrical Engineering, Mathematics and Computer Science (EEMCS)
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