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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.
Cited literature [4 references]
https://hal.inria.fr/hal-01365594
Contributor : Hal Ifip <>
Submitted on : Tuesday, September 13, 2016 - 3:24:50 PM
Last modification on : Thursday, June 4, 2020 - 6:26:03 PM
Long-term archiving on: : Wednesday, December 14, 2016 - 2:29:14 PM
Contributor : Hal Ifip <>
Submitted on : Tuesday, September 13, 2016 - 3:24:50 PM
Last modification on : Thursday, June 4, 2020 - 6:26:03 PM
Long-term archiving on: : Wednesday, December 14, 2016 - 2:29:14 PM
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Distributed under a Creative Commons Attribution 4.0 International License