Threshold choice for automatic spindle detection

Arnaldo Manuel Guimarães Batista; Manuel Duarte Ortigueira; DEE Group Author

Threshold choice for automatic spindle detection

Arnaldo Manuel Guimarães Batista, Manuel Duarte Ortigueira, DEE Group Author

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

In this paper five choices are presented to determine the threshold for sleep spindle automatic detection. The pro- posed 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%.

Original language	Unknown
Title of host publication	Proceedings of the 19th International Conference on Systems, Signals and Image Processing (IWSSIP 2012)
Pages	197-200
Publication status	Published - 1 Jan 2012
Event	IWSSIP 2012: 19th International Conference on Systems, Signals and Image Processing - Duration: 1 Jan 2012 → …

Conference

Conference	IWSSIP 2012: 19th International Conference on Systems, Signals and Image Processing
Period	1/01/12 → …

Cite this

@inproceedings{c25d02f4b0a341ecb977267328af65bd,

title = "Threshold choice for automatic spindle detection",

abstract = "In this paper five choices are presented to determine the threshold for sleep spindle automatic detection. The pro- posed 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 = "Sleep Spindles, Wave Morphology for Spindle Detection, EEG, Threshold",

author = "Batista, {Arnaldo Manuel Guimar{\~a}es} and Ortigueira, {Manuel Duarte} and {DEE Group Author}",

note = "Sem PDF; IWSSIP 2012: 19th International Conference on Systems, Signals and Image Processing ; Conference date: 01-01-2012",

year = "2012",

month = jan,

day = "1",

language = "Unknown",

isbn = "978-3-200-02328-4",

pages = "197--200",

booktitle = "Proceedings of the 19th International Conference on Systems, Signals and Image Processing (IWSSIP 2012)",

}

TY - GEN

T1 - Threshold choice for automatic spindle detection

AU - Batista, Arnaldo Manuel Guimarães

AU - Ortigueira, Manuel Duarte

AU - DEE Group Author

N1 - Sem PDF

PY - 2012/1/1

Y1 - 2012/1/1

N2 - In this paper five choices are presented to determine the threshold for sleep spindle automatic detection. The pro- posed 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%.

AB - In this paper five choices are presented to determine the threshold for sleep spindle automatic detection. The pro- posed 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%.

KW - Sleep Spindles

KW - Wave Morphology for Spindle Detection

KW - EEG

KW - Threshold

M3 - Conference contribution

SN - 978-3-200-02328-4

SP - 197

EP - 200

BT - Proceedings of the 19th International Conference on Systems, Signals and Image Processing (IWSSIP 2012)

T2 - IWSSIP 2012: 19th International Conference on Systems, Signals and Image Processing

Y2 - 1 January 2012

ER -