DocumentCode
2211582
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
fYear
2012
fDate
11-13 April 2012
Firstpage
197
Lastpage
200
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;
fLanguage
English
Publisher
ieee
Conference_Titel
Systems, Signals and Image Processing (IWSSIP), 2012 19th International Conference on
Conference_Location
Vienna
ISSN
2157-8672
Print_ISBN
978-1-4577-2191-5
Type
conf
Filename
6208106
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