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

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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 languageUnknown
Title of host publicationIFIP Advances in Information and Communication Technology
Pages267-272
Volume372
ISBN (Electronic)978-3-642-28255-3
DOIs
Publication statusPublished - 1 Jan 2012
Event3rd IFIP/SOCOLNET Doctoral Conference on Computing, Electrical and Industrial Systems -
Duration: 1 Jan 2012 → …

Conference

Conference3rd IFIP/SOCOLNET Doctoral Conference on Computing, Electrical and Industrial Systems
Period1/01/12 → …

Cite this

Batista, A. M. G., Ortigueira, M. D., & 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) https://doi.org/10.1007/978-3-642-28255-3_29