Short Time Fourier Transform and Automatic Visual Scoring for the Detection of Sleep Spindles

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

doi:10.1007/978-3-642-28255-3_29

Short Time Fourier Transform and Automatic Visual Scoring for the Detection of Sleep Spindles

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

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

Abstract

Sleep spindles are the most interesting hallmark of stage 2 sleep EEG. Their accurate identification in a polysomnographic signal is essential for sleep professionals to help them mark Stage 2 sleep. Visual spindle scoring however is a tedious workload. In this paper two different approaches are used for the automatic detection of sleep spindles: Short Time Fourier Transform and Automatic Visual Scoring. The results obtained using both methods are compared with human expert scorers.

Original language	Unknown
Title of host publication	IFIP Advances in Information and Communication Technology
Pages	267-272
Volume	372
ISBN (Electronic)	978-3-642-28255-3
DOIs	https://doi.org/10.1007/978-3-642-28255-3_29
Publication status	Published - 1 Jan 2012
Event	3rd IFIP/SOCOLNET Doctoral Conference on Computing, Electrical and Industrial Systems - Duration: 1 Jan 2012 → …

Conference

Conference	3rd IFIP/SOCOLNET Doctoral Conference on Computing, Electrical and Industrial Systems
Period	1/01/12 → …

Access to Document

10.1007/978-3-642-28255-3_29

http://oa.uninova.pt/5299/

Cite this

@inproceedings{f4bbc19ae2ab4386a0e8a351b8358488,

title = "Short Time Fourier Transform and Automatic Visual Scoring for the Detection of Sleep Spindles",

abstract = "Sleep spindles are the most interesting hallmark of stage 2 sleep EEG. Their accurate identification in a polysomnographic signal is essential for sleep professionals to help them mark Stage 2 sleep. Visual spindle scoring however is a tedious workload. In this paper two different approaches are used for the automatic detection of sleep spindles: Short Time Fourier Transform and Automatic Visual Scoring. The results obtained using both methods are compared with human expert scorers.",

keywords = "Sleep Spindles, Short Time Fourier Transform, EEG, Automatic Visual Scoring",

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

year = "2012",

month = jan,

day = "1",

doi = "10.1007/978-3-642-28255-3\_29",

language = "Unknown",

isbn = "978-3-642-28254-6",

volume = "372",

pages = "267--272",

booktitle = "IFIP Advances in Information and Communication Technology",

note = "3rd IFIP/SOCOLNET Doctoral Conference on Computing, Electrical and Industrial Systems ; Conference date: 01-01-2012",

}

Batista, AMG , Ortigueira, MD & DEE Group Author 2012, Short Time Fourier Transform and Automatic Visual Scoring for the Detection of Sleep Spindles. in IFIP Advances in Information and Communication Technology. vol. 372, pp. 267-272, 3rd IFIP/SOCOLNET Doctoral Conference on Computing, Electrical and Industrial Systems, 1/01/12. https://doi.org/10.1007/978-3-642-28255-3_29

TY - GEN

T1 - Short Time Fourier Transform and Automatic Visual Scoring for the Detection of Sleep Spindles

AU - Batista, Arnaldo Manuel Guimarães

AU - Ortigueira, Manuel Duarte

AU - DEE Group Author

PY - 2012/1/1

Y1 - 2012/1/1

N2 - Sleep spindles are the most interesting hallmark of stage 2 sleep EEG. Their accurate identification in a polysomnographic signal is essential for sleep professionals to help them mark Stage 2 sleep. Visual spindle scoring however is a tedious workload. In this paper two different approaches are used for the automatic detection of sleep spindles: Short Time Fourier Transform and Automatic Visual Scoring. The results obtained using both methods are compared with human expert scorers.

AB - Sleep spindles are the most interesting hallmark of stage 2 sleep EEG. Their accurate identification in a polysomnographic signal is essential for sleep professionals to help them mark Stage 2 sleep. Visual spindle scoring however is a tedious workload. In this paper two different approaches are used for the automatic detection of sleep spindles: Short Time Fourier Transform and Automatic Visual Scoring. The results obtained using both methods are compared with human expert scorers.

KW - Sleep Spindles

KW - Short Time Fourier Transform

KW - EEG

KW - Automatic Visual Scoring

U2 - 10.1007/978-3-642-28255-3_29

DO - 10.1007/978-3-642-28255-3_29

M3 - Conference contribution

SN - 978-3-642-28254-6

VL - 372

SP - 267

EP - 272

BT - IFIP Advances in Information and Communication Technology

T2 - 3rd IFIP/SOCOLNET Doctoral Conference on Computing, Electrical and Industrial Systems

Y2 - 1 January 2012

ER -