Abstract
In this paper we introduce a speech-based information system for a humanoid robot that is able to adapt its information presentation strategy to different brain patterns of its user. Brain patterns are classified from electroencephalographic (EEG) signals and correspond to situations of low and high mental workload. The robot selects an information presentation style that best matches the detected patterns. The complete system of recognition and adaptation is tested in an evaluation study with ten participants. We achieve a mean recognition rate of 80% and show that an adaptive information presentation strategy improves user satisfaction in comparison to static strategies.
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Heger, D., Putze, F., Schultz, T. (2010). An Adaptive Information System for an Empathic Robot Using EEG Data. In: Ge, S.S., Li, H., Cabibihan, JJ., Tan, Y.K. (eds) Social Robotics. ICSR 2010. Lecture Notes in Computer Science(), vol 6414. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-17248-9_16
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DOI: https://doi.org/10.1007/978-3-642-17248-9_16
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-17247-2
Online ISBN: 978-3-642-17248-9
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