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

Figure 3

Estimation of multiscale entropy (MSE) for the time series of the heart period. 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). While MA does not induce changes, HUT evokes a significant reduction of the complexity of heart period variability, which is observed using LMSE across a wide range of time scales including both low- and high-frequency oscillations. Statistically significant difference, HUT versus SU or MA versus SU.

(a) Heart period, LMSE

(b) Heart period, RMSE