Entropic Measures of Complexity of Short-Term Dynamics of Nocturnal Heartbeats in an Aging Population

Abstract

Two entropy-based approaches are investigated to study patterns describing differences in time intervals between consecutive heartbeats. The first method explores matrices arising from networks of transitions constructed following events represented by a time series. The second method considers distributions of ordinal patterns of length three, whereby patterns with repeated values are counted as different patterns. Both methods provide estimators of dynamical aspects of short-term heartbeat signals obtained from nocturnal Holter electrocardiogram (ECG) recordings of healthy people of different ages and genders. The deceleration capacity, arising from the adjacency matrix of the network, and the entropy rate, resulting from the transition matrix of the network, are also calculated, and both significantly decay with aging. As people age, the permutation entropy grows, due to the increase in patterns with repeated values. All of these estimators describe in a consistent way changes in the beat-to-beat heart period dynamics caused by aging. An overall slowing Entropy 2015, 17 1254 down of heart period changes is observed, and an increase of permutation entropy results from the progressive increase of patterns with repeated values. This result points to the sympathetic drive becoming dominant in cardiac regulation of nocturnal heart rate with age.

Changes of Permutation Pattern Entropy and Ordinal Pattern Entropy During Three Emotion States: Natural, Happiness and Sadness

“…Bian et al presented that OPEn could effectively distinguish young and elderly group from RRI time series [10]. Makowiec et al showed that OPEn grew systematically with age and it increased depended on gender [11]. Wejer et al [12] confirmed that OPEn reduced after the tilt compared to at rest for both vasovagal patients and healthy people groups [12].…”

“…PPEn of RRI time series can be observed that the mean value due to non-shockable ventricular arrhythmia class was higher than shockable VA class [9]. Then, the OPEn follows the PPEn was considered to deal with the equals of segments [10][11][12]. Bian et al presented that OPEn could effectively distinguish young and elderly group from RRI time series [10].…”

The distribution of information for sEMG signals in the rectal cancer treatment process

“…Quite recently, considerable attention has been paid to the entropy-based techniques with a very promising potential in bio-medical signal processing [8,9,10,11]. The idea of implementing the entropy notions for the measure of biodiversity is present in an increasing number of the studied biosystems, from the microscopic level [12,13] to the whole body response that can be investigated by the spectrum of electrophysiological signals as electrocardiography (ECG) [14,15,16], encephalography (EEG) [17] or magnetoencephalography (MEG) [18]. The specific values of the approximate entropy measures and their dependence on the time scales were analysed for the sEMG signals registered with patients with colorectal cancer [19].…”

Dynamical Landscape of Heart Rhythm in Discerning Erratic Rhythm in Elderly People

“…Many measures estimating heart rate variability (HRV) have been proposed in order to quantify the regulatory function of the ANS, see [1][2][3]. Intensive healthy population studies have found a correlation between an increase in age and a decrease in many HRV indices, including indices such as RMSDD, pNN50 and HF, which are known to describe the short-term HRV (ST-HRV) [4][5][6][7][8][9][10]. Therefore, higher values of HRV have been attributed to better organization of feedback reflexes driving the organism's response to actual body needs.…”