Details Details PDF BIBTEX RIS Title Effect of Feature Extraction on Automatic Sleep Stage Classification by Artificial Neural Network Journal title Metrology and Measurement Systems Yearbook 2017 Volume vol. 24 Issue No 2 Authors Prucnal, Monika ; Polak, Adam G. Keywords sleep stage classification ; EEG signal ; power spectral density ; discrete wavelet transform ; empirical mode decomposition ; artificial neural network Divisions of PAS Nauki Techniczne Coverage 229–240 Publisher Polish Academy of Sciences Committee on Metrology and Scientific Instrumentation Date 2017.06.30 Type Artykuły / Articles Identifier DOI: 10.1515/mms-2017-0036 ; ISSN 2080-9050, e-ISSN 2300-1941 Source Metrology and Measurement Systems; 2017; vol. 24; No 2; 229–240 References Wu (2015), Assess Sleep Stage by Modern Signal Processing Techniques, IEEE Trans Biomed Eng, 62, 1159. ; Mohammadi (2016), Improving time - frequency domain sleep EEG classification via singular spectrum analysis, Neurosci Methods, 273. ; Jabłoński (2013), Modern methods for description of complex couplings in neurophysiology of respiration, IEEE Sensors, 13, 3182. ; Oh (2014), A Novel EEG Feature Extraction Method Using Hjorth Parameter, Electron Electr Eng, 2, 106. ; Hassan (2016), Automatic sleep scoring using statistical features in the EMD domain and ensemble methods, Biocybern Biomed Eng, 36, 248. ; 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