Multiscale Entropy Analysis of Complex Physiologic Time Series

Abstract

Abstract

Electrophysiological entropy in younger adults, older controls and older cognitively declined adults

“…Zhao et al (2007) reported that the use of a time domain Tsallis entropy estimator applied to long duration background EEG waveforms was successful in producing markers for subjects with Alzheimer's disease. Escudero et al (2006) reported reduced uncertainty of spontaneous EEG in AD subjects when compared with healthy subjects using a Multiscale entropy (MSE) analysis (Costa et al, 2002). However, MSE does not produce a single measure but instead a set of values for each of the time scale values under investigation and, hence, it is necessary to complete a further parameterisation of this set of values (or more typically of the curve formed from these values).…”

Glycemic Control, Hand Activity, and Complexity of Biological Signals in Diabetes Mellitus

“…However, the influence of handgrip strength on any time scales MSE or RMSE was not remarkable in individuals without diabetes and those with poorly controlled diabetes. Several physiological signals such as sleep electroencephalographic wave [26], electromyographic signals [27], body temperature [28], intracranial pressure [29], pulse rate [12], and blood pressure [15] have been used for MSE analysis to mainly evaluate autonomic nervous dysfunction, cardiovascular disease, treatment effect, and disease prognosis. Trunkvalterova et al revealed that the MSE of blood pressures and pulse rate at scale factor = 3 in patients with type 1 diabetes were significantly lower than those in the unaffected controls [15].…”

“…Therefore, 퐸 is computed for each new coarse-grained time series { 푗 (휏) } of which the length is / and is plotted as a function of the scale factor [12]. The scale factor up to 10 was selected for a minimal length of the coarse-grained time series equal to 150 beats, a length appropriate for a reliable estimate of 퐸 [23].…”

“…Javorka et al have revealed that many frequency and time domain linear indexes of HRV such as root-mean-square of successive differences of R-R intervals (RMSSD) are significantly reduced in patients with diabetes [11]. Costa et al proposed the nonlinear index of multiscale entropy (MSE) to reflect the complexity of physiological signals [12], which has been utilized additionally to the linear parameters. In brief, a healthy system exhibits an exquisite complex control to preserve homeostasis, generally leading to a high level of MSE [12].…”

“…Costa et al proposed the nonlinear index of multiscale entropy (MSE) to reflect the complexity of physiological signals [12], which has been utilized additionally to the linear parameters. In brief, a healthy system exhibits an exquisite complex control to preserve homeostasis, generally leading to a high level of MSE [12]. Silva et al demonstrated that the nonlinear characteristics of small-time scales MSE 2 Complexity of HRV are much influenced by parasympathetic activity in experimental mice [13].…”