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We assess the feasibility of heart rate variability (HRV) estimated from interbeat interval (IBI) data measured with wrist-worn photoplethysmography device for sleep stage classification. In particular, we examine fractal correlations in the IBIs as the function of both time and scale.Optical heart rate sensor by PulseOn Ltd was utilized for monitoring IBIs from 18 healthy young adult subjects. Reference ambulatory polysomnography recordings were scored by a sleep physician. The HRV was studied by detrended fluctuation analysis by computing scale-dependent spectra of scaling exponents &#x03B1;(s). Dynamic changes were tracked by calculating the spectra &#x03B1;(s, t) in moving temporal windows whose length varied with the scale.The dynamic landscapes of the alpha spectra show distinctive fractal correlations according to the underlying sleep stages. Respiratory effects, blood pressure variations, and thermoregulatory influence appear to be discernible as well. Classification of the alpha spectra yields up to 73 %, 60 % and 54 % average accuracies for 3-class (wake, REM, NREM), 4-class (wake, REM, N1+2, N3) and 5-class (wake, REM, N1, N2, N3) cases, respectively.

Non-Linear Heart Rate Variability Measures in Sleep Stage Analysis with Photoplethysmography