Abstract
Most studies considering spectral features of HRV during sleep divided total frequency band into low frequency (LF, 0.04~0.15Hz) and high frequency (HF, 0.15~0.4 Hz) roughly, and were limited to a few measures like the power in LF and HF, or the ratio of them. To make full use of HRV, more comprehensive spectral features were evaluated in this paper. LF was further divided into true LF (0.04~0.1Hz) and medium frequency (0.1~0.15Hz). Spectrum power, mean frequency and spectral entropy of different spectral bands, fractal dimension and peak in HF (20 measures in total) were calculated for wake, REM, light sleep and deep sleep. The significance between sleep stages of each feature was evaluated. The random forest method was adopted for sleep staging and features importance rank. The results suggested that almost all the new proposed features showed significant differences during different sleep stages. They can improve sleep stages classification performance notably. Our study provided new features for sleep stages classification based on ECG.
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