Title :
Threshold choice for automatic spindle detection
Author :
Costa, João Caldas da ; Ortigueira, Manuel Duarte ; Batista, Arnaldo ; Paiva, T. Santos
Author_Institution :
Dept. of Syst. & Inf, IPS, Setubal, Portugal
Abstract :
In this paper five choices are presented to determine the threshold for sleep spindle automatic detection. The proposed methods are based on performance measures. The different threshold values are compared using a Wave Morphology for Spindle Detection algorithm. For the presented algorithm, sensitivity ranges from 47.9% to 94.7%, while specificity ranges inversely from 98.7% to 89.0% for the threshold values used; the maximum accuracy reached is 96.6%.
Keywords :
electroencephalography; medical signal detection; EEG patterns; automatic spindle detection; sleep spindle automatic detection algorithm; threshold values; wave morphology; Accuracy; Detectors; Electroencephalography; Morphology; Sensitivity; Sensitivity and specificity; Sleep; EEG; Sleep Spindles; Threshold; Wave Morphology for Spindle Detection;
Conference_Titel :
Systems, Signals and Image Processing (IWSSIP), 2012 19th International Conference on
Conference_Location :
Vienna
Print_ISBN :
978-1-4577-2191-5
