Multifractal analysis of central (electrocardiography) and peripheral (laser Doppler flowmetry) cardiovascular time series from healthy human subjects

Peripheral blood flow estimated by laser doppler flowmetry provides additional information about sleep state beyond that provided by pulse rate variability

Pulse rate variability (PRV), derived from Laser Doppler flowmetry (LDF) or photoplethysmography, has recently become widely used for sleep state assessment, although it cannot identify all the sleep stages. Peripheral blood flow (BF), also estimated by LDF, may be modulated by sleep stages; however, few studies have explored its potential for assessing sleep state. Thus, we aimed to investigate whether peripheral BF could provide information about sleep stages, and thus improve sleep state assessment. We performed electrocardiography and simultaneously recorded BF signals by LDF from the right-index finger and ear concha of 45 healthy participants (13 women; mean age, 22.5 ± 3.4 years) during one night of polysomnographic recording. Time- and frequency-domain parameters of peripheral BF, and time-domain, frequency-domain, and non-linear indices of PRV and heart rate variability (HRV) were calculated. Finger-BF parameters in the time and frequency domains provided information about different sleep stages, some of which (such as the difference between N1 and rapid eye movement sleep) were not revealed by finger-PRV. In addition, finger-PRV patterns and HRV patterns were similar for most parameters. Further, both finger- and ear-BF results showed 0.2-0.3 Hz oscillations that varied with sleep stages, with a significant increase in N3, suggesting a modulation of respiration within this frequency band. These results showed that peripheral BF could provide information for different sleep stages, some of which was complementary to the information provided by PRV. Furthermore, the combination of peripheral BF and PRV may be more advantageous than HRV alone in assessing sleep states and related autonomic nervous activity.

Nonlinear temperature effects on multifractal complexity of metabolic rate of mice

Complex physiological dynamics have been argued to be a signature of healthy physiological function. Here we test whether the complexity of metabolic rate fluctuations in small endotherms decreases with lower environmental temperatures. To do so, we examine the multifractal temporal scaling properties of the rate of change in oxygen consumption r(VO₂), in the laboratory mouse Mus musculus, assessing their long range correlation properties across seven different environmental temperatures, ranging from 0 °C to 30 °C. To do so, we applied multifractal detrended fluctuation analysis (MF-DFA), finding that r(VO₂) fluctuations show two scaling regimes. For small time scales below the crossover time (approximately 10² s), either monofractal or weak multifractal dynamics are observed depending on whether T_a < 15 °C or T_a > 15 °C respectively. For larger time scales, r(VO₂) fluctuations are characterized by an asymptotic scaling exponent that indicates multifractal anti-persistent or uncorrelated dynamics. For both scaling regimes, a generalization of the multiplicative cascade model provides very good fits for the Renyi exponents τ(q), showing that the infinite number of exponents h(q) can be described by only two independent parameters, a and b. We also show that the long-range correlation structure of r(VO₂) time series differs from randomly shuffled series, and may not be explained as an artifact of stochastic sampling of a linear frequency spectrum. These results show that metabolic rate dynamics in a well studied micro-endotherm are consistent with a highly non-linear feedback control system.

Complexity analysis of the microcirculatory-blood-flow response following acupuncture stimulation

Beat-to-beat cardiovascular variability analysis provides important information on the circulatory regulatory activities. Changes in the arterial pulse transmission or the opening condition of arteriolar openings might change the fluctuation pattern of the MBF supply, and thus change the complexity property therein. We performed complexity analysis of beat-to-beat laser Doppler flowmetry (LDF) signals to study the microcirculatory-blood-flow (MBF) response at the needled site (Hegu acupoint) following acupuncture stimulation (AS). LDF signals were measured in male healthy volunteers (n=29). Each experiment involved recording a 20-minute baseline-data sequence and two sets of effects data recorded 0-20 and 50-70min after stopping AS. Approximate-entropy (ApEn) analysis, which quantifies the unpredictability of fluctuations in a time series, was performed on each 20-minute beat-to-beat LDF data sequence. The present findings indicate that AS can not only improve the local blood supply but may also increase ApEn values and decrease MBF variability parameters. This was the first attempt to apply complexity analysis to LDF signals in order to elucidate microcirculatory responses following AS. The observed results are probably attributable to the contradictory effects on the MBF supply induced by AS, which might interfere with the microcirculatory regulatory activities so as to increase the complexity of LDF signals. The present findings could help to identify the mechanism underlying the effects of AS, might aid the development of an index for monitoring the induced microcirculatory regulatory responses, and thus provide an evidence-based connection between AS and modern physiology.

Study of time reversibility/irreversibility of cardiovascular data: theoretical results and application to laser Doppler flowmetry and heart rate variability signals

Time irreversibility can be qualitatively defined as the degree of a signal for temporal asymmetry. Recently, a time irreversibility characterization method based on entropies of positive and negative increments has been proposed for experimental signals and applied to heart rate variability (HRV) data (central cardiovascular system (CVS)). The results led to interesting information as a time asymmetry index was found different for young subjects and elderly people or heart disease patients. Nevertheless, similar analyses have not yet been conducted on laser Doppler flowmetry (LDF) signals (peripheral CVS). We first propose to further investigate the above-mentioned characterization method. Then, LDF signals, LDF signals reduced to samples acquired during ECG R peaks (LDF_R(ECG) signals) and HRV recorded simultaneously in healthy subjects are processed. Entropies of positive and negative increments for LDF signals show a nonmonotonic pattern: oscillations--more or less pronounced, depending on subjects--are found with a period matching the one of cardiac activity. However, such oscillations are not found with LDF_R(ECG) nor with HRV. Moreover, the asymmetry index for LDF is markedly different from the ones of LDF_R(ECG) and HRV. The cardiac activity may therefore play a dominant role in the time irreversibility properties of LDF signals.

Oscillations in the evaluation of fractal dimension of RR intervals time series

Previously, we have reported the presence of oscillations in the graphs we have used to evaluate the Higuchi's fractal dimension in RR intervals time series of congestive heart failure (CHF) patients in the sleep phase but these oscillations hardly appear in all the six hours of the awake phase. In this paper we report the same analysis for heart rate time series for different groups of healthy subjects; we are looking for the presence of this kind of oscillations in other situations. We analyzed all the time series in the Exaggerated Heart Rate Oscillations database of Physionet during two meditation techniques: volunteers with spontaneous breathing, subjects in meditation, volunteers in a metronomic breathing group and elite athletes. We have found oscillations in the graphs of the Higuchi's fractal dimension in the heart rate time series of subjects in meditation and metronomic breathing and this fact coincides with previous reported results.

Multiscale entropy of laser Doppler flowmetry signals in healthy human subjects

PURPOSE

The cardiovascular system (CVS) regulation can be studied from a central viewpoint, through heart rate variability (HRV) data, and from a peripheral viewpoint, through laser Doppler flowmetry (LDF) signals. Both the central and peripheral CVSs are regulated by several interacting mechanisms, each having its own temporal scale. The central CVS has been the subject of many multiscale studies. By contrast, these studies at the level of the peripheral CVS are very recent. Among the multiscale studies performed on the central CVS data, multiscale entropy has been proven to give interesting physiological information for diagnostic purposes. However, no multiscale entropy analysis has been performed on LDF signals. The authors' goal is therefore to propose a first multiscale entropy study of LDF data recorded in healthy subjects.

METHODS

The LDF signals recorded in the forearm of seven healthy subjects are processed. Their period sampling is T=50 ms, and coarse-graining scales from T to 23T are studied. Also, for validation, the algorithm is first tested on synthetic signals of known theoretical multiscale entropy.

RESULTS

The results reveal nonmonotonic evolution of the multiscale entropy of LDF signals, with a maximum at small scales around 7T and a minimum at longer scales around 18T, singling out in this way two distinctive scales where the LDF signals undergo specific changes from high to low complexity. This also marks a strong contrast with the HRV signals that usually display a monotonic increase in the evolution of the multiscale entropy.

CONCLUSIONS

Multiscale entropy of LDF signals in healthy subjects shows variation with scales. Moreover, as the variation pattern observed appears similar for all the tested signals, multiscale entropy could potentially be a useful stationary signature for LDF signals, which otherwise are probe-position and subject dependent. Further work could now be conducted to evaluate possible diagnostic purposes of the multiscale entropy of LDF signals.