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EEG Artifact Detection Algorithm Base on Nonlinear Analysis Method  

Kim, Chul-Ki (Dept. of Control and Instrumentation Eng., Pukyoung National University)
Park, Jun-Mo (School of Electronic and Biomedical Engineering, Tongmyong University)
Kim, Nam-Ho (Dept. of Control and Instrumentation Eng., Pukyoung National University)
Publication Information
Journal of the Institute of Convergence Signal Processing / v.21, no.1, 2020 , pp. 7-12 More about this Journal
Abstract
Various parameters are used to measure anesthetic depth during surgery using brain waves, and in actual clinical use, the linear analysis SEF is widely used. However, with recent studies showing that biological signals including EEG, contain nonlinear properties interest in nonlinear analysis of brain signals is increasing and parameters based on these are being developed. In this study, we are going to develop a parameter that can measure EEG using the nonlinear analysis method and extract noise that can be mixed with external electronic equipment and EEG instrumentation by comparing it with the data from the bispectrum analysis of static waves.
Keywords
EEG; Bispectral analysis; Nonlinear analysis; Anesthesia depth; High order spectrum analysis;
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Times Cited By KSCI : 2  (Citation Analysis)
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