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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.
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João Costa, Manuel Ortigueira, Arnaldo Batista. Short Time Fourier Transform and Automatic Visual Scoring for the Detection of Sleep Spindles. 3rd Doctoral Conference on Computing, Electrical and Industrial Systems (DoCEIS), Feb 2012, Costa de Caparica, Portugal. pp.267-272, ⟨10.1007/978-3-642-28255-3_29⟩. ⟨hal-01365594⟩

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