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. © 2012 IFIP International Federation for Information Processing.
CITATION STYLE
Da Costa, J. C., Ortigueira, M. D., & Batista, A. (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 AICT, pp. 267–272). https://doi.org/10.1007/978-3-642-28255-3_29
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