Efficient Computation of Multiscale Entropy over Short Biomedical Time Series Based on Linear State-Space Models

Figure 4

Estimation of multiscale entropy (MSE) for the time series of the systolic arterial pressure. Plots depict the distributions (median and 25th–75th percentiles) of the MSE estimates ) computed as a function of the cutoff frequency of the low-pass filter used to eliminate the fast temporal scales of the process in the resting supine position (SU, diamonds), during postural stress induced by head-up tilt (HUT, squares), and during mental stress induced by mental arithmetics (MA, circles). The multiscale complexity of systolic pressure dynamics increases consistently across multiple time scales during MA and increases for time scales associated with low-frequency oscillations during HUT. Statistically significant difference, HUT versus SU or MA versus SU.

(a) Systolic pressure, LMSE

(b) Systolic pressure, RMSE