M. Šorf, J. Hodný, R. Pecherek, and L. Lhotská (Czech Republic)
physiological signals, skin conductance response, Fouriertransform, wavelet transform, artificial intelligence,physiological signals processing.
This paper describes developed software tools for physiological signal processing and a special software tool for skin conductance response processing. Input data are physiological signals and output data are parameters of signals. These parameters are further evaluated using artificial intelligence methods and statistical methods. The artificial intelligence methods used are machine learning (decision tree generation), neural network, expert system, fuzzy system and combination of machine learning (decision tree) and expert system This paper further describes measurement of physiological signals (heart frequency, respiratory frequency, skin galvanic reaction, systolic and diastolic blood pressures, muscular tonus, EMG, etc.), their processing and applications in educational process.
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