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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Luis M. Camarinha-Matos; Ehsan Shahamatnia; Gonçalo Nunes. 3rd Doctoral Conference on Computing, Electrical and Industrial Systems (DoCEIS), Feb 2012, Costa de Caparica, Portugal. Springer, IFIP Advances in Information and Communication Technology, AICT-372, pp.267-272, 2012, Technological Innovation for Value Creation. 〈10.1007/978-3-642-28255-3_29〉
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João Costa, Manuel Ortigueira, Arnaldo Batista. Short Time Fourier Transform and Automatic Visual Scoring for the Detection of Sleep Spindles. Luis M. Camarinha-Matos; Ehsan Shahamatnia; Gonçalo Nunes. 3rd Doctoral Conference on Computing, Electrical and Industrial Systems (DoCEIS), Feb 2012, Costa de Caparica, Portugal. Springer, IFIP Advances in Information and Communication Technology, AICT-372, pp.267-272, 2012, Technological Innovation for Value Creation. 〈10.1007/978-3-642-28255-3_29〉. 〈hal-01365594〉

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