Browsing by Author "Kalauzi, Aleksandar (7801322210)"

Heart rate (HR) asymmetry is a dynamic phenomenon related to the interplay of dominant regulatory mechanisms of cardiovascular system which operate over different scales of observation. The aim of this work is to examine asymmetry phenomenon in heart failure (HF) patients with sinus rhythm. We computed Guzik's index of heart rate asymmetry related to HR deceleration (C-{d}) from the Poincaré plot (Pp) analysis extended up to 20th order. In the control group asymmetry is maintained over all orders of the Pp. In HF patients with asymmetric properties, C-{d} is reduced in the range between 2ndand 5th order of the Pp analysis, compared the control subjects. More, this method revealed two clusters of HF patients. In conclusion, proposed new approach can be applied to reveal alterations in the behavior of the cardiovascular control mechanisms in pathological conditions. © 2020 IEEE.

Heart rate (HR) asymmetry is a dynamic phenomenon related to the interplay of dominant regulatory mechanisms of cardiovascular system which operate over different scales of observation. The aim of this work is to examine asymmetry phenomenon in heart failure (HF) patients with sinus rhythm. We computed Guzik's index of heart rate asymmetry related to HR deceleration (C-{d}) from the Poincaré plot (Pp) analysis extended up to 20th order. In the control group asymmetry is maintained over all orders of the Pp. In HF patients with asymmetric properties, C-{d} is reduced in the range between 2ndand 5th order of the Pp analysis, compared the control subjects. More, this method revealed two clusters of HF patients. In conclusion, proposed new approach can be applied to reveal alterations in the behavior of the cardiovascular control mechanisms in pathological conditions. © 2020 IEEE.

Heart failure (HF) is one of the most frequent heart diseases. It is usually characterized with structural and functional cardiac abnormalities followed by dysfunction of autonomic cardiac control. Current methods of heartbeat interval analysis are not capable to differentiate HF patients and some new differentiation of HF patients could be useful in the determination of the direction of their treatment. In this study, we examined potential of the ratio of the short-term and long-term scaling exponents (α1 and α2) to separate HF patients with similar level of reduced cardiac autonomic nervous system control and with no significant difference in age, left ventricular ejection fraction (LVEF) and NYHA class. Thirty-five healthy control subjects and 46 HF patients underwent 20 min of continuous supine resting ECG recording. The interbeat interval time series were analyzed using standardized power spectrum analysis, detrended fluctuation analysis method and standard Poincaré plot (PP) analysis with measures of asymmetry of the PP. Compared with healthy control group, in HF patients linear measures of autonomic cardiac control were statistically significantly reduced (p < 0.05), heart rate asymmetry was preserved (Cup > Cdown, p < 0.01), and long-term scaling exponent α2 was significantly higher. Cluster analysis of the ratio of short- and long-term scaling exponents showed capability of this parameter to separate four clusters of HF patients. Clusters were determined by interplay of presence of short-term and long-term correlations in interbeat intervals. Complementary measure, commonly accepted ratio of the PP descriptors, SD2/SD1, showed tendency toward statistical significance to separate HF patients in obtained clusters. Also, heart rate asymmetry was preserved only in two clusters. Finally, a multiple regression analysis showed that the ratio α1/α2 could be used as an integrated measure of cardiac dynamic with complex physiological background which, besides spectral components as measures of autonomic cardiac control, also involves breathing frequency and mechanical cardiac parameter, left ventricular ejection fraction. © 2019 Platiša, Radovanović, Kalauzi, Milašinović and Pavlović. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

Heart failure (HF) is one of the most frequent heart diseases. It is usually characterized with structural and functional cardiac abnormalities followed by dysfunction of autonomic cardiac control. Current methods of heartbeat interval analysis are not capable to differentiate HF patients and some new differentiation of HF patients could be useful in the determination of the direction of their treatment. In this study, we examined potential of the ratio of the short-term and long-term scaling exponents (α1 and α2) to separate HF patients with similar level of reduced cardiac autonomic nervous system control and with no significant difference in age, left ventricular ejection fraction (LVEF) and NYHA class. Thirty-five healthy control subjects and 46 HF patients underwent 20 min of continuous supine resting ECG recording. The interbeat interval time series were analyzed using standardized power spectrum analysis, detrended fluctuation analysis method and standard Poincaré plot (PP) analysis with measures of asymmetry of the PP. Compared with healthy control group, in HF patients linear measures of autonomic cardiac control were statistically significantly reduced (p < 0.05), heart rate asymmetry was preserved (Cup > Cdown, p < 0.01), and long-term scaling exponent α2 was significantly higher. Cluster analysis of the ratio of short- and long-term scaling exponents showed capability of this parameter to separate four clusters of HF patients. Clusters were determined by interplay of presence of short-term and long-term correlations in interbeat intervals. Complementary measure, commonly accepted ratio of the PP descriptors, SD2/SD1, showed tendency toward statistical significance to separate HF patients in obtained clusters. Also, heart rate asymmetry was preserved only in two clusters. Finally, a multiple regression analysis showed that the ratio α1/α2 could be used as an integrated measure of cardiac dynamic with complex physiological background which, besides spectral components as measures of autonomic cardiac control, also involves breathing frequency and mechanical cardiac parameter, left ventricular ejection fraction. © 2019 Platiša, Radovanović, Kalauzi, Milašinović and Pavlović. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

We applied a novel approach to respiratory waveform analysis-Monotone Signal Segments Analysis (MSSA) on 6-h recordings of respiratory signals in rats. To validate MSSA as a respiratory signal analysis tool we tested it by detecting: breaths and breath-to-breath intervals; respiratory timing and volume modes; and changes in respiratory pattern caused by lesions of monoaminergic systems in rats. MSSA differentiated three respiratory timing (tachypneic, eupneic, bradypneic-apneic), and three volume (artifacts, normovolemic, hypervolemic-sighs) modes. Lesion-induced respiratory pattern modulation was visible as shifts in the distributions of monotone signal segment amplitudes, and of breath-to-breath intervals. Specifically, noradrenergic lesion induced an increase in mean volume (p ≤ 0.03), with no change of the mean breath-to-breath interval duration (p ≥ 0.06). MSSA of timing modes detected noradrenergic lesion-induced interdependent changes in the balance of eupneic (decrease; p ≤ 0.02), and tachypneic (an increase; p ≤ 0.02) breath intervals with respect to control. In terms of breath durations within each timing mode, there was a tendency toward prolongation of the eupneic (p ≤ 0.08) and bradypneic-apneic (p ≤ 0.06) intervals. These results demonstrate that MSSA is sensitive to subtle shifts in respiratory rhythmogenesis not detectable by simple respiratory pattern descriptive statistics. MSSA represents a potentially valuable new tool for investigations of respiratory pattern control. © 2008 Elsevier B.V. All rights reserved.

We applied a novel approach to respiratory waveform analysis-Monotone Signal Segments Analysis (MSSA) on 6-h recordings of respiratory signals in rats. To validate MSSA as a respiratory signal analysis tool we tested it by detecting: breaths and breath-to-breath intervals; respiratory timing and volume modes; and changes in respiratory pattern caused by lesions of monoaminergic systems in rats. MSSA differentiated three respiratory timing (tachypneic, eupneic, bradypneic-apneic), and three volume (artifacts, normovolemic, hypervolemic-sighs) modes. Lesion-induced respiratory pattern modulation was visible as shifts in the distributions of monotone signal segment amplitudes, and of breath-to-breath intervals. Specifically, noradrenergic lesion induced an increase in mean volume (p ≤ 0.03), with no change of the mean breath-to-breath interval duration (p ≥ 0.06). MSSA of timing modes detected noradrenergic lesion-induced interdependent changes in the balance of eupneic (decrease; p ≤ 0.02), and tachypneic (an increase; p ≤ 0.02) breath intervals with respect to control. In terms of breath durations within each timing mode, there was a tendency toward prolongation of the eupneic (p ≤ 0.08) and bradypneic-apneic (p ≤ 0.06) intervals. These results demonstrate that MSSA is sensitive to subtle shifts in respiratory rhythmogenesis not detectable by simple respiratory pattern descriptive statistics. MSSA represents a potentially valuable new tool for investigations of respiratory pattern control. © 2008 Elsevier B.V. All rights reserved.

Objective: In this research we explored the (homeo)dynamic character of cardiorespiratory coupling (CRC) under the influence of different body posture and breathing regimes. Our tool for it was the pulse respiration quotient (PRQ), representing the number of heartbeat intervals per breathing cycle. We obtained non-integer PRQ values using our advanced Matlab® algorithm and applied it on the signals of 20 healthy subjects in four conditions: supine position with spontaneous breathing (Supin), standing with spontaneous breathing (Stand), supine position with slow (0.1 Hz) breathing (Supin01) and standing with slow (0.1 Hz) breathing (Stand01). Main results: Linear features of CRC (in PRQ signals) were dynamically very sensitive to posture and breathing rhythm perturbations. There are obvious increases in PRQ mean level and variability under the separated and joined influence of orthostasis and slow (0.1 Hz) breathing. This increase was most pronounced in Stand01 as the state of joint influences. Importantly, PRQ dynamic modification showed greater sensitivity to body posture and breathing regime changes than mean value and standard deviation of heart rhythm and breathing rhythm. In addition, as a consequence of prolonged supine position, we noticed the tendency to integer quantization of PRQ (especially after 14 min), in which the most common quantization number was 4:1 (demonstrated in other research reports as well). In orthostasis and slow breathing, quantization can also be observed, but shifted to other values. We postulate that these results manifest resonance effects induced by coupling patterns from sympathetic and parasympathetic adjustments (with the second as dominant factor). Significance: Our research confirms that cardiorespiratory coupling adaptability could be profoundly explored by precisely calculated PRQ parameter since cardiorespiratory regulation in healthy subjects is characterized by a high level of autonomic adaptability (responsiveness) to posture and breathing regime, although comparisons with pathological states has yet to be performed. We found Stand01 to be the most provoking state for the dynamic modification of PRQ (cardiorespiratory inducement). As such, Stand01 has the potential of using for PRQ tuning by conditioning the cardiorespiratory autonomic neural networks, e.g., in the cases where PRQ is disturbed by environmental (i.e., microgravity) or pathologic conditions. Copyright © 2022 Matić, Kalauzi, Moser, Platiša, Lazarević and Bojić.

Objective: In this research we explored the (homeo)dynamic character of cardiorespiratory coupling (CRC) under the influence of different body posture and breathing regimes. Our tool for it was the pulse respiration quotient (PRQ), representing the number of heartbeat intervals per breathing cycle. We obtained non-integer PRQ values using our advanced Matlab® algorithm and applied it on the signals of 20 healthy subjects in four conditions: supine position with spontaneous breathing (Supin), standing with spontaneous breathing (Stand), supine position with slow (0.1 Hz) breathing (Supin01) and standing with slow (0.1 Hz) breathing (Stand01). Main results: Linear features of CRC (in PRQ signals) were dynamically very sensitive to posture and breathing rhythm perturbations. There are obvious increases in PRQ mean level and variability under the separated and joined influence of orthostasis and slow (0.1 Hz) breathing. This increase was most pronounced in Stand01 as the state of joint influences. Importantly, PRQ dynamic modification showed greater sensitivity to body posture and breathing regime changes than mean value and standard deviation of heart rhythm and breathing rhythm. In addition, as a consequence of prolonged supine position, we noticed the tendency to integer quantization of PRQ (especially after 14 min), in which the most common quantization number was 4:1 (demonstrated in other research reports as well). In orthostasis and slow breathing, quantization can also be observed, but shifted to other values. We postulate that these results manifest resonance effects induced by coupling patterns from sympathetic and parasympathetic adjustments (with the second as dominant factor). Significance: Our research confirms that cardiorespiratory coupling adaptability could be profoundly explored by precisely calculated PRQ parameter since cardiorespiratory regulation in healthy subjects is characterized by a high level of autonomic adaptability (responsiveness) to posture and breathing regime, although comparisons with pathological states has yet to be performed. We found Stand01 to be the most provoking state for the dynamic modification of PRQ (cardiorespiratory inducement). As such, Stand01 has the potential of using for PRQ tuning by conditioning the cardiorespiratory autonomic neural networks, e.g., in the cases where PRQ is disturbed by environmental (i.e., microgravity) or pathologic conditions. Copyright © 2022 Matić, Kalauzi, Moser, Platiša, Lazarević and Bojić.

Our aim was to model the dependence of respiratory sinus arrhythmia (RSA) on the respiratory waveform and to elucidate underlying mechanisms of cardiorespiratory coupling. In 30 subjects, RR interval and respiratory signal were recorded during spontaneous and paced (0.1. Hz/0.15. Hz) breathing and their relationship was modeled by a first order linear differential equation.This model has two parameters: a0 (related to the instantaneous degree of abdominal expansion) and a1 (referring to the speed of abdominal expansion). Assuming that a0 represents slowly adapting pulmonary stretch receptors (SARs) and a1 SARs in coordination with other stretch receptors and central integrative coupling; then pulmonary stretch receptors relaying the instantaneous lung volume are the major factor determining cardiovagal output during inspiration.The model's results depended on breathing frequency with the least error occurring during slow paced breathing. The role of vagal afferent neurons in cardiorespiratory coupling may relate to neurocardiovascular diseases in which weakened coupling among venous return, arterial pressure, heart rate and respiration produces cardiovagal instability. © 2014 Published by Elsevier B.V.

Our aim was to model the dependence of respiratory sinus arrhythmia (RSA) on the respiratory waveform and to elucidate underlying mechanisms of cardiorespiratory coupling. In 30 subjects, RR interval and respiratory signal were recorded during spontaneous and paced (0.1. Hz/0.15. Hz) breathing and their relationship was modeled by a first order linear differential equation.This model has two parameters: a0 (related to the instantaneous degree of abdominal expansion) and a1 (referring to the speed of abdominal expansion). Assuming that a0 represents slowly adapting pulmonary stretch receptors (SARs) and a1 SARs in coordination with other stretch receptors and central integrative coupling; then pulmonary stretch receptors relaying the instantaneous lung volume are the major factor determining cardiovagal output during inspiration.The model's results depended on breathing frequency with the least error occurring during slow paced breathing. The role of vagal afferent neurons in cardiorespiratory coupling may relate to neurocardiovascular diseases in which weakened coupling among venous return, arterial pressure, heart rate and respiration produces cardiovagal instability. © 2014 Published by Elsevier B.V.

Objective: We explored the physiological background of the non-linear operating mode of cardiorespiratory oscillators as the fundamental question of cardiorespiratory homeodynamics and as a prerequisite for the understanding of neurocardiovascular diseases. We investigated 20 healthy human subjects for changes using electrocardiac RR interval (RRI) and respiratory signal (Resp) Detrended Fluctuation Analysis (DFA, α1RRI, α2RRI, α1Resp, α2Resp), Multiple Scaling Entropy (MSERRI1−4, MSERRI5−10, MSEResp1−4, MSEResp5−10), spectral coherence (CohRRI−Resp), cross DFA (ρ1 and ρ2) and cross MSE (XMSE1−4 and XMSE5−10) indices in four physiological conditions: supine with spontaneous breathing, standing with spontaneous breathing, supine with 0.1 Hz breathing and standing with 0.1 Hz breathing. Main results: Standing is primarily characterized by the change of RRI parameters, insensitivity to change with respiratory parameters, decrease of CohRRI−Resp and insensitivity to change of in ρ1, ρ2, XMSE1−4, and XMSE5−10. Slow breathing in supine position was characterized by the change of the linear and non-linear parameters of both signals, reflecting the dominant vagal RRI modulation and the impact of slow 0.1 Hz breathing on Resp parameters. CohRRI−Resp did not change with respect to supine position, while ρ1 increased. Slow breathing in standing reflected the qualitatively specific state of autonomic regulation with striking impact on both cardiac and respiratory parameters, with specific patterns of cardiorespiratory coupling. Significance: Our results show that cardiac and respiratory short term and long term complexity parameters have different, state dependent patterns. Sympathovagal non-linear interactions are dependent on the pattern of their activation, having different scaling properties when individually activated with respect to the state of their joint activation. All investigated states induced a change of α1 vs. α2 relationship, which can be accurately expressed by the proposed measure—inter-fractal angle θ. Short scale (α1 vs. MSE1−4) and long scale (α2 vs. MSE5−10) complexity measures had reciprocal interrelation in standing with 0.1 Hz breathing, with specific cardiorespiratory coupling pattern (ρ1 vs. XMSE1−4). These results support the hypothesis of hierarchical organization of cardiorespiratory complexity mechanisms and their recruitment in ascendant manner with respect to the increase of behavioral challenge complexity. Specific and comprehensive cardiorespiratory regulation in standing with 0.1 Hz breathing suggests this state as the potentially most beneficial maneuver for cardiorespiratory conditioning. © Copyright © 2020 Matić, Platiša, Kalauzi and Bojić.

Objective: We explored the physiological background of the non-linear operating mode of cardiorespiratory oscillators as the fundamental question of cardiorespiratory homeodynamics and as a prerequisite for the understanding of neurocardiovascular diseases. We investigated 20 healthy human subjects for changes using electrocardiac RR interval (RRI) and respiratory signal (Resp) Detrended Fluctuation Analysis (DFA, α1RRI, α2RRI, α1Resp, α2Resp), Multiple Scaling Entropy (MSERRI1−4, MSERRI5−10, MSEResp1−4, MSEResp5−10), spectral coherence (CohRRI−Resp), cross DFA (ρ1 and ρ2) and cross MSE (XMSE1−4 and XMSE5−10) indices in four physiological conditions: supine with spontaneous breathing, standing with spontaneous breathing, supine with 0.1 Hz breathing and standing with 0.1 Hz breathing. Main results: Standing is primarily characterized by the change of RRI parameters, insensitivity to change with respiratory parameters, decrease of CohRRI−Resp and insensitivity to change of in ρ1, ρ2, XMSE1−4, and XMSE5−10. Slow breathing in supine position was characterized by the change of the linear and non-linear parameters of both signals, reflecting the dominant vagal RRI modulation and the impact of slow 0.1 Hz breathing on Resp parameters. CohRRI−Resp did not change with respect to supine position, while ρ1 increased. Slow breathing in standing reflected the qualitatively specific state of autonomic regulation with striking impact on both cardiac and respiratory parameters, with specific patterns of cardiorespiratory coupling. Significance: Our results show that cardiac and respiratory short term and long term complexity parameters have different, state dependent patterns. Sympathovagal non-linear interactions are dependent on the pattern of their activation, having different scaling properties when individually activated with respect to the state of their joint activation. All investigated states induced a change of α1 vs. α2 relationship, which can be accurately expressed by the proposed measure—inter-fractal angle θ. Short scale (α1 vs. MSE1−4) and long scale (α2 vs. MSE5−10) complexity measures had reciprocal interrelation in standing with 0.1 Hz breathing, with specific cardiorespiratory coupling pattern (ρ1 vs. XMSE1−4). These results support the hypothesis of hierarchical organization of cardiorespiratory complexity mechanisms and their recruitment in ascendant manner with respect to the increase of behavioral challenge complexity. Specific and comprehensive cardiorespiratory regulation in standing with 0.1 Hz breathing suggests this state as the potentially most beneficial maneuver for cardiorespiratory conditioning. © Copyright © 2020 Matić, Platiša, Kalauzi and Bojić.

Objectives: In order to reveal their structure, Poincaré plots (PP) of electrocardiogram (ECG) RR intervals (RRI) were studied as linear edge planar directed graphs, obtained by connecting all their sequential points. We were also aimed at studying their graph complexity properties. Methods: RRI signals were subjected to a series of different window length (WL) Moving Average Low Pass (MALP) filters. For each filtered graph, four standard PP descriptors: Pearson's coefficient, SD1, SD2, and SD2/SD1 were calculated, as well as four new graph complexity measures: mean angle between adjacent graph edges; mean number of edge crossings; directional complexity and directional entropy. This approach was applied to signals of twenty young healthy subjects, recorded in four experimental conditions – combination of two body postures (supine and standing) and two breathing regimes (spontaneous and slow 0.1 Hz). Results: We found that PP graphs consist of two superimposed components: one originating from Respiratory Sinus Arrhythmia (RSA) oscillations, the other from slow variations (SV) of the RRI time series. This result was further corroborated by observing the transformation of a PP cloud shape occurring in filtered graphs. When applied to subjects, the outcome was that three measures significantly differentiated the two breathing regimes in the RSA region of the WL domain, while four other measures were able to differentiate two body postures in the SV WL region. Discussion: After obtaining these results in healthy, we expect to successfully apply this approach to patients suffering from different pathological conditions. © 2022 Elsevier Ltd

Objectives: In order to reveal their structure, Poincaré plots (PP) of electrocardiogram (ECG) RR intervals (RRI) were studied as linear edge planar directed graphs, obtained by connecting all their sequential points. We were also aimed at studying their graph complexity properties. Methods: RRI signals were subjected to a series of different window length (WL) Moving Average Low Pass (MALP) filters. For each filtered graph, four standard PP descriptors: Pearson's coefficient, SD1, SD2, and SD2/SD1 were calculated, as well as four new graph complexity measures: mean angle between adjacent graph edges; mean number of edge crossings; directional complexity and directional entropy. This approach was applied to signals of twenty young healthy subjects, recorded in four experimental conditions – combination of two body postures (supine and standing) and two breathing regimes (spontaneous and slow 0.1 Hz). Results: We found that PP graphs consist of two superimposed components: one originating from Respiratory Sinus Arrhythmia (RSA) oscillations, the other from slow variations (SV) of the RRI time series. This result was further corroborated by observing the transformation of a PP cloud shape occurring in filtered graphs. When applied to subjects, the outcome was that three measures significantly differentiated the two breathing regimes in the RSA region of the WL domain, while four other measures were able to differentiate two body postures in the SV WL region. Discussion: After obtaining these results in healthy, we expect to successfully apply this approach to patients suffering from different pathological conditions. © 2022 Elsevier Ltd