Data-driven modeling of sleep EEG and EOG reveals characteristics indicative of pre-Parkinson's and Parkinson's disease - Christensen, Julie A.E.; Zoetmulder, Marielle; Koch, Henriette; Frandsen, Rune; Arvastson, Lars; Christensen, Søren R.; Jennum, Poul; Sorensen, Helge B.D. (Journal of neuroscience methods, 2014)
Keywords: Aged; Algorithms; Artificial Intelligence; Automatic classification; Electroencephalography; Electroencephalography - methods; Electrooculography; Electrooculography - methods; Female; Humans; Male; Middle Aged; Models, Neurological; Nocturnal Myoclonus Syndrome - diagnosis; Nocturnal Myoclonus Syndrome - physiopathology; Parkinson Disease - diagnosis; Parkinson Disease - physiopathology; Parkinson's disease; Polysomnography; Polysomnography - methods; Regression Analysis; Sensitivity and Specificity; Signal Processing, Computer-Assisted; Sleep Stages - physiology; Topic modeling; Topic modeling; Electrooculography; Automatic classification; Electroencephalography; Parkinson's disease; Polysomnography