Application of knowledge-based system for fast identification of EEG frequency

Piotr Filipkowski and Michał Horodelski
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Piotr Filipkowski: Szkoła Główna Handlowa w Warszawie
Michał Horodelski: Katolicki Uniwersytet Lubelski Jana Pawła II

Collegium of Economic Analysis Annals, 2015, issue 38, 353-368

Abstract: In the paper, the authors solve the problem of fast interpretation of data from selected psychophysiology devices, dedicated to research on semi-trained respondents acting in stress environment, making highly responsible decisions in short time. Results from EEG (electroencephalography), among others, are evaluated by therapists according to their knowledge. Classic methods are acceptable for accidental cases, but in group cases they prolong the time of the analysis. In the paper the authors present a method of digital support of therapist’s or trainer’s decisions in the interpretation of data received form medical devices. The authors propose an algorithm and its implementations for visualizations of given interpretations, which help to increase the speed of biofeedback for therapist. Additionally, the authors propose a built-in platform which is mobile, scalable and allows using engineering tools, including computational intelligence in future work. Method: An environment of Knowledge-Base System 2014 for the automatic interpretation of data from sensors has been developed together with a batch system with an internal knowledge base, ready to work in LiveCD mode in accordance with the IEEE829 standard, providing not only mobility, but also the acceleration of various applications integrated with psychophysiological devices. Quality evaluation: To examine the compatibility of KBS system with the requirements, an abstract verification based on the model checking method has been used.

Keywords: decision support systems; knowledge-based system; psychophysiological device; EEG; scilab gui; batch operating systems; model checking (search for similar items in EconPapers)
Date: 2015
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