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