Comparison of Some Spectral Analysis Methods in Detection of Sleep Spindles Using YSA

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Tarih

2015

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Yayıncı

IEEE

Erişim Hakkı

info:eu-repo/semantics/closedAccess

Özet

Sleep spindle is a very determinant factor for detection of Non-REM2 stage in sleep staging studies. When it is considered that about half of the sleep consists of Non-REM2 stage, the importance of automatic sleep spindle detection stands out. In this study, three different spectral analysis method- FFT, Welch and AR have been used to estimate the frequency spectrum of sleep EEG signal and feature extraction from this spectrum has been realized. Obtained features have been used in ANN to classify EEG epochs as epochs with spindle and epochs without spindle. It has been observed that least classification error was obtained with FFT as 15.16%.

Açıklama

23nd Signal Processing and Communications Applications Conference (SIU) -- MAY 16-19, 2015 -- Inonu Univ, Malatya, TURKEY

Anahtar Kelimeler

Sleep Spindle Classification, Fft, Welch, Yule-Ar, Ann

Kaynak

2015 23rd Signal Processing And Communications Applications Conference (Siu)

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