Simple mental and verbal activities markedly affect HRV through changes in respiratory frequency. This possibility should be taken into account when analyzing HRV without simultaneous acquisition and analysis of respiration.

MDFA seems to be more sensitive as compared with WTMM method in differentiation between multifractal properties of the heart rate in healthy subjects and patients with left ventricular systolic dysfunction.

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The heart rate responds dynamically to various intrinsic and environmental stimuli. The autonomic nervous system is said to play a major role in this response. Multifractal analysis offers a novel method to assess the response of cardiac interbeat intervals. Twenty-four hour ECG recordings of RR interbeat intervals (of 48 elderly volunteers (age 65-94), 40 middle-aged persons (age 45-53) and 36 young adults (age 18-26)) were investigated to study the effect of aging on autonomic regulation during normal activity in healthy adults. Heart RR-interval variability in the very low frequency (VLF) band (32-420 RR intervals) was evaluated by multifractal tools. The nocturnal and diurnal signals of 6 h duration were studied separately. For each signal, the analysis was performed twice: for a given signal and for the integrated signal. A multifractal spectrum was quantified by the h(max) value at which a multifractal spectrum attained its maximum, width of a spectrum, Hurst exponent, extreme events h(left) and distance between the maxima of a signal and its integrated counterpart. The following seven characteristics are suggested as quantifying the age-related decrease in the autonomic function ('int' refers to the integrated signal): (a) h(sleep)(max) - h(max)(wake) > 0.05 for a signal; (b) h(int)(max) > 1.15 for wake; (c) h(int)(max) - h(max) > 0.85 for sleep; (d) Hurst(wake) - Hurst(sleep) < 0.01; (e) width(wake) > 0.07; (f) width(int) < 0.30 for sleep; (g) h(int)(left) > 0.75. Eighty-one percent of elderly people had at least four of these properties, and ninety-two percent of young people had three or less. This shows that the multifractal approach offers a concise and reliable index of healthy aging for each individual. Additionally, the applied method yielded insights into dynamical changes in the autonomic regulation due to the circadian cycle and aging. Our observations support the hypothesis that imbalance in the autonomic control due to healthy aging could be related to changes emerging from the vagal function (Struzik et al 2006 IEEE Trans. Biomed. Eng. 53 89-94).

It can be assumed that more pronounced inflammatory response as an element of stress reaction after MI can predispose to depression. IL17a increase can play particularly important role in this process.

Maxwell's demon is a special case of a feedback controlled system, where the information gathered by measurement is utilized by driving a system along a thermodynamic process that depends on the measurement outcome. The demon illustrates that with feedback one can design an engine that performs work by extracting energy from a single thermal bath. Besides the fundamental questions posed by the demon -the probabilistic nature of the Second Law, the relationship between entropy and information, etc.-there are other practical problems related to feedback engines. One of those is the design of optimal engines, protocols that extract the maximum amount of energy given some amount of information. A refinement of the second law to feedback systems establishes a bound to the extracted energy, a bound that is met by optimal feedback engines. It is also known that optimal engines are characterized by time reversibility. As a consequence, the optimal protocol given a measurement is the one that, run in reverse, prepares the system in the post-measurement state (preparation prescription). In this paper, we review these results and analyze some specific features of the preparation prescription when applied to non-ergodic systems.

Network models have been used to capture, represent and analyse characteristics of living organisms and general properties of complex systems. The use of network representations in the characterization of time series complexity is a relatively new but quickly developing branch of time series analysis. In particular, beat-to-beat heart rate variability can be mapped out in a network of RR-increments, which is a directed and weighted graph with vertices representing RR-increments and the edges of which correspond to subsequent increments. We evaluate entropy measures selected from these network representations in records of healthy subjects and heart transplant patients, and provide an interpretation of the results.

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