Background: The Gini coefficient is a statistical tool generally used by economists to quantify income inequality. However, it can be applied to any kind of data with unequal distribution, including heart rate variability (HRV). Objectives: To assess the application of the Gini coefficient to measure inequality in power spectral density of RR intervals, and to use this application as a psychophysiological indicator of mental stress. Methods: Thirteen healthy subjects (19 ± 1.5 years) participated in this study, and their RR intervals were obtained by electrocardiogram during rest (five minutes) and during mental stress (arithmetic challenge; five minutes). These RR intervals were used to obtain the estimates of power spectral densities (PSD). The limits for the PSD bands were defined from 0.15 to 0.40 Hz for high frequency band (HF), from 0.04 to 0.15 Hz for low frequency band (LF), from 0.04 to 0.085 Hz for first low frequency sub-band (LF1) and from 0.085 to 0.15 Hz for second low frequency sub-band (LF2). The spectral Gini coefficient (SpG) was proposed to measure the inequality in the power distribution of the RR intervals in each of above-mentioned HRV bands. SpG from each band was compared with its respective traditional index of HRV during the conditions of rest and mental stress. All the differences were considered statistically significant for p < 0.05. Results: There was a significant decrease in HF power (p = 0.046), as well as significant increases in heart rate (p = 0.004), LF power (p = 0.033), LF2 power (p = 0.019) and LF/HF (p = 0.002) during mental stress. There was also a significant increase in SpG(LF) (p = 0.009) and SpG(LF2) (p = 0.033) during mental stress. Coefficient of variation showed SpG has more homogeneity compared to the traditional index of HRV during mental stress. Conclusions: This pilot study suggested that spectral inequality of Heart Rate Variability analyzed using the Gini coefficient seems to be an independent and homogeneous psychophysiological indicator of mental stress. Also, HR, LF/HF, SpG(LF) of HRV are possibly important, reliable and valid indicators of mental stress.

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Purpose: The aim of the present study was to investigate the role of occlusion time in dynamic changes of autonomic activation during reactive hyperemia. Methods: Healthy subjects (n = 30) in the age range of 18–25 years participated in this study. Vascular reactivity was assessed by measuring the dynamic changes in finger pulse volume amplitude (PVA) and  pulse transit time relative to the RR intervals in the test (occluded arm) and control arm (contralateral non-occluded arm) during 1, 3 and 5 minute of occlusion using two separate Photoplethysmographic sensors. Heart Rate Variability was computed from a simultaneously acquired ECG signal to monitor the dynamic changes in cardiac autonomic nervous activity. Time-varying analysis of all signals were shown every 1 second in average response graphs. Results: Time-varying analysis of vascular and autonomic response during reactive hyperemia demonstrated the presence of a characteristic response pattern with an increase in the Sympathetic index and a decrease in Parasympathetic index at 8 to 10 seconds, an increase in heart rate at 20 seconds and a progressive increase in PVA during the first 60 seconds after occlusion regardless of the time spent in the procedure. Moreover, a decrease in pulse transits time relative to RR intervals,  followed by an increase regardless of the occlusion time was evidenced.  Conclusions: Early cardiovascular sympathetic activation is independent of occlusion time during reactive hyperemia, which suggests this is a vascular autonomic reflex response involved in the generation of the physiological phenomenon of reactive hyperemia.

Theil entropy is a statistical measure used in economics to quantify income inequalities. However, it can be applied to any data distribution including biological signals. In this work, we applied different spectral methods on heart rate variability signals and cellular calcium oscillations previously to Theil entropy analysis. The behavior of Theil entropy and its decomposable property was investigated using exponents in the range of [−1, 2], on the spectrum of synthetic and physiological signals. Our results suggest that the best spectral decomposition method to analyze the spectral inequality of physiological oscillations is the Lomb–Scargle method, followed by Theil entropy analysis. Moreover, our results showed that the exponents that provide more information to describe the spectral inequality in the tested signals were zero, one, and two. It was also observed that the intra-band component is the one that contributes the most to total inequality for the studied oscillations. More in detail, we found that in the state of mental stress, the inequality determined by the Theil entropy analysis of heart rate increases with respect to the resting state. Likewise, the same analytical approach shows that cellular calcium oscillations present on developing interneurons display greater inequality distribution when inhibition of a neurotransmitter system is in place. In conclusion, we propose that Theil entropy is useful for analyzing spectral inequality and to explore its origin in physiological signals.