Abstract
An experimental multimodal system, designed for polysensory diagnosis and stimulation of persons with impaired communication skills or even non-communicative subjects is presented. The user interface includes an eye tracking device and the EEG monitoring of the subject. Furthermore, the system consists of a device for objective hearing testing and an autostereoscopic projection system designed to stimulate subjects through their immersion in a virtual environment. Data analysis methods are described, and experiments associated with classification of mental states during listening exercises as well as audio-visual stimuli are presented and discussed. Feature extraction was based on discrete wavelet transformation and clustering employing the k-means algorithm was designed. All algorithms were implemented in the Python programming language with the use of Open Source libraries. Tests of the proposed system were performed in a Special School and Educational Center in Kościerzyna, Poland. Results and comparison with data gathered from the control group of healthy people are presented and discussed.
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The project was funded by the National Science Centre on the basis of the decision number DEC-2013/11/B/ST8/04328.
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Kurowski, A. et al. (2017). Multimodal System for Diagnosis and Polysensory Stimulation of Subjects with Communication Disorders. In: Kryszkiewicz, M., Appice, A., Ślęzak, D., Rybinski, H., Skowron, A., Raś, Z. (eds) Foundations of Intelligent Systems. ISMIS 2017. Lecture Notes in Computer Science(), vol 10352. Springer, Cham. https://doi.org/10.1007/978-3-319-60438-1_5
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DOI: https://doi.org/10.1007/978-3-319-60438-1_5
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