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Cairo B, Bari V, Gelpi F, De Maria B, Porta A. Assessing cardiorespiratory interactions via lagged joint symbolic dynamics during spontaneous and controlled breathing. FRONTIERS IN NETWORK PHYSIOLOGY 2023; 3:1211848. [PMID: 37602202 PMCID: PMC10436098 DOI: 10.3389/fnetp.2023.1211848] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/25/2023] [Accepted: 07/13/2023] [Indexed: 08/22/2023]
Abstract
Introduction: Joint symbolic analysis (JSA) can be utilized to describe interactions between time series while accounting for time scales and nonlinear features. JSA is based on the computation of the rate of occurrence of joint patterns built after symbolization. Lagged JSA (LJSA) is obtained from the more classical JSA by introducing a delay/lead between patterns built over the two series and combined to form the joint scheme, thus monitoring coordinated patterns at different lags. Methods: In the present study, we applied LJSA for the assessment of cardiorespiratory coupling (CRC) from heart period (HP) variability and respiratory activity (R) in 19 healthy subjects (age: 27-35 years; 8 males, 11 females) during spontaneous breathing (SB) and controlled breathing (CB). The R rate of CB was selected to be indistinguishable from that of SB, namely, 15 breaths·minute-1 (CB15), or slower than SB, namely, 10 breaths·minute-1 (CB10), but in both cases, very rapid interactions between heart rate and R were known to be present. The ability of the LJSA approach to follow variations of the coupling strength was tested over a unidirectionally or bidirectionally coupled stochastic process and using surrogate data to test the null hypothesis of uncoupling. Results: We found that: i) the analysis of surrogate data proved that HP and R were significantly coupled in any experimental condition, and coupling was not more likely to occur at a specific time lag; ii) CB10 reduced CRC strength at the fastest time scales while increasing that at intermediate time scales, thus leaving the overall CRC strength unvaried; iii) despite exhibiting similar R rates and respiratory sinus arrhythmia, SB and CB15 induced different cardiorespiratory interactions; iv) no dominant temporal scheme was observed with relevant contributions of HP patterns either leading or lagging R. Discussion: LJSA is a useful methodology to explore HP-R dynamic interactions while accounting for time shifts and scales.
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Affiliation(s)
- Beatrice Cairo
- Department of Biomedical Sciences for Health, University of Milan, Milan, Italy
| | - Vlasta Bari
- Department of Biomedical Sciences for Health, University of Milan, Milan, Italy
- Department of Cardiothoracic, Vascular Anesthesia and Intensive Care, IRCCS Policlinico San Donato Milanese, Milan, Italy
| | - Francesca Gelpi
- Department of Biomedical Sciences for Health, University of Milan, Milan, Italy
| | | | - Alberto Porta
- Department of Biomedical Sciences for Health, University of Milan, Milan, Italy
- Department of Cardiothoracic, Vascular Anesthesia and Intensive Care, IRCCS Policlinico San Donato Milanese, Milan, Italy
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Cairo B, Bari V, de Abreu RM, Gelpi F, De Maria B, Catai AM, Porta A. Characterization of Multiple Regimes of Cardiorespiratory Phase Synchronization in Athletes Undergoing Inspiratory Muscle Training. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2023; 2023:1-4. [PMID: 38083759 DOI: 10.1109/embc40787.2023.10339951] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/18/2023]
Abstract
Cardiorespiratory phase synchronization (CRPS) is defined as the stable occurrence of n heartbeats within m respiratory cycles according to the n:m phase locking ratio (PLR). Since CRPS is an intermittent phenomenon where different phase synchronization regimes and epochs of phase unlocking can alternate within the same recording, an index of CRPS ideally should assess all potential PLRs present in the recording. However, traditional approaches compute the synchronization index (SYNC%) over a single n:m PLR, namely the one that maximizes CRPS. In the present work, we tested a synchronization index assessing the total percentage of heartbeats coupled to the inspiratory onset regardless of phase locking regimes (SYNC%sum) and we compared its efficacy to the more traditional SYNC%. Analysis was carried out in a cohort of 25 male amateur cyclists (age: 20-40 yrs) undergoing inspiratory muscle training (IMT) at different intensities. CRPS was assessed before and after the IMT protocol, during an experimental condition known to modify CRPS, namely active standing (STAND). We found that after a moderate intensity IMT at 60% of the maximal inspiratory pressure, SYNC%sum could detect the decrease in CRPS following STAND. This result was not visible using the more traditional SYNC%. Therefore, we stress the significant presence of different phase locking regimes in athletes and the importance of accounting for multiple PLRs in CRPS analysis.Clinical Relevance- Multiple phase locking regimes contribute significantly to cardiorespiratory control in amateur cyclists especially after inspiratory muscle training of moderate intensity.
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Cardiorespiratory coupling in mechanically ventilated patients studied via synchrogram analysis. Med Biol Eng Comput 2023; 61:1329-1341. [PMID: 36698031 DOI: 10.1007/s11517-023-02784-4] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2022] [Accepted: 01/15/2023] [Indexed: 01/27/2023]
Abstract
Respiration and cardiac activity are strictly interconnected with reciprocal influences. They act as weakly coupled oscillators showing varying degrees of phase synchronization and their interactions are affected by mechanical ventilation. The study aims at differentiating the impact of three ventilatory modes on the cardiorespiratory phase coupling in critically ill patients. The coupling between respiration and heartbeat was studied through cardiorespiratory phase synchronization analysis carried out via synchrogram during pressure control ventilation (PCV), pressure support ventilation (PSV), and neurally adjusted ventilatory assist (NAVA) in critically ill patients. Twenty patients were studied under all the three ventilatory modes. Cardiorespiratory phase synchronization changed significantly across ventilatory modes. The highest synchronization degree was found during PCV session, while the lowest one with NAVA. The percentage of all epochs featuring synchronization regardless of the phase locking ratio was higher with PCV (median: 33.9%, first-third quartile: 21.3-39.3) than PSV (median: 15.7%; first-third quartile: 10.9-27.8) and NAVA (median: 3.7%; first-third quartile: 3.3-19.2). PCV induces a significant amount of cardiorespiratory phase synchronization in critically ill mechanically ventilated patients. Synchronization induced by patient-driven ventilatory modes was weaker, reaching the minimum with NAVA. Findings can be explained as a result of the more regular and powerful solicitation of the cardiorespiratory system induced by PCV. The degree of phase synchronization between cardiac and respiratory activities in mechanically ventilated humans depends on the ventilatory mode.
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Porta A, Bari V, Gelpi F, Cairo B, De Maria B, Tonon D, Rossato G, Faes L. Comparing Cross-Sample Entropy and K-Nearest-Neighbor Cross-Predictability Approaches for the Evaluation of Cardiorespiratory and Cerebrovascular Dynamic Interactions. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2022; 2022:127-130. [PMID: 36085935 DOI: 10.1109/embc48229.2022.9871239] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Quantification of the cardiorespiratory and cerebrovascular couplings is a relevant clinical issue given that their changes are considered signs of pathological status. The inherent nonlinearity of mechanisms underlying cardiorespiratory and cerebrovascular links requires nonlinear tools for their reliable evaluation. In the present study we compare two nonlinear methods for the assessment of coupling strength between two time series, namely cross-sample entropy (CSampEn) and k-nearest-neighbor cross-predictability (KNNCP). CSampEn uses a strategy that fixes the pattern length, while KNNCP optimizes the pattern length to maximize cross-predictability. CSampEn and KNNCP were applied to the beat-to-beat series of heart period (HP) and respiration (R) during a controlled breathing protocol with the aim at assessing cardiorespiratory coupling and to the beat-to-beat series of mean cerebral blood flow (MCBF) and mean arterial pressure (MAP) during an orthostatic stressor with the aim at evaluating cerebrovascular coupling. Although both the methods have the possibility to quantify the degree of HP-R and MCBF-MAP association, they exhibited different statistical power and even diverse trends in response to the considered physiological challenges. CSampEn and KNNCP are not interchangeable and should be utilized in association more than in alternative for the quantification of the HP-R and MCBF-MAP coupling strength. Clinical Relevance - This study proves that cross-entropy and cross-predictability might lead to different conclusions about cardiorespiratory and cerebrovascular couplings.
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Cairo B, de Abreu RM, Bari V, Gelpi F, De Maria B, Rehder-Santos P, Sakaguchi CA, da Silva CD, De Favari Signini É, Catai AM, Porta A. Optimizing phase variability threshold for automated synchrogram analysis of cardiorespiratory interactions in amateur cyclists. PHILOSOPHICAL TRANSACTIONS. SERIES A, MATHEMATICAL, PHYSICAL, AND ENGINEERING SCIENCES 2021; 379:20200251. [PMID: 34689616 DOI: 10.1098/rsta.2020.0251] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 10/29/2020] [Indexed: 06/13/2023]
Abstract
We propose a procedure suitable for automated synchrogram analysis for setting the threshold below which phase variability between two marker event series is of such a negligible amount that the null hypothesis of phase desynchronization can be rejected. The procedure exploits the principle of maximizing the likelihood of detecting phase synchronization epochs and it is grounded on a surrogate data approach testing the null hypothesis of phase uncoupling. The approach was applied to assess cardiorespiratory phase interactions between heartbeat and inspiratory onset in amateur cyclists before and after 11-week inspiratory muscle training (IMT) at different intensities and compared to a more traditional approach to set phase variability threshold. The proposed procedure was able to detect the decrease in cardiorespiratory phase locking strength during vagal withdrawal induced by the modification of posture from supine to standing. IMT had very limited effects on cardiorespiratory phase synchronization strength and this result held regardless of the training intensity. In amateur athletes training, the inspiratory muscles did not limit the decrease in cardiorespiratory phase synchronization observed in the upright position as a likely consequence of the modest impact of this respiratory exercise, regardless of its intensity, on cardiac vagal control. This article is part of the theme issue 'Advanced computation in cardiovascular physiology: new challenges and opportunities'.
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Affiliation(s)
- Beatrice Cairo
- Department of Biomedical Sciences for Health, University of Milan, Milan 20133, Italy
| | - Raphael Martins de Abreu
- Department of Physical Therapy, Federal University of São Carlos, São Carlos, São Paulo 13565-905, Brazil
| | - Vlasta Bari
- Department of Cardiothoracic, Vascular Anesthesia and Intensive Care, IRCCS Policlinico San Donato, San Donato Milanese, Milan 20097, Italy
| | - Francesca Gelpi
- Department of Cardiothoracic, Vascular Anesthesia and Intensive Care, IRCCS Policlinico San Donato, San Donato Milanese, Milan 20097, Italy
| | | | - Patrícia Rehder-Santos
- Department of Physical Therapy, Federal University of São Carlos, São Carlos, São Paulo 13565-905, Brazil
| | - Camila Akemi Sakaguchi
- Department of Physical Therapy, Federal University of São Carlos, São Carlos, São Paulo 13565-905, Brazil
| | - Claudio Donisete da Silva
- Department of Physical Therapy, Federal University of São Carlos, São Carlos, São Paulo 13565-905, Brazil
| | - Étore De Favari Signini
- Department of Physical Therapy, Federal University of São Carlos, São Carlos, São Paulo 13565-905, Brazil
| | - Aparecida Maria Catai
- Department of Physical Therapy, Federal University of São Carlos, São Carlos, São Paulo 13565-905, Brazil
| | - Alberto Porta
- Department of Biomedical Sciences for Health, University of Milan, Milan 20133, Italy
- Department of Cardiothoracic, Vascular Anesthesia and Intensive Care, IRCCS Policlinico San Donato, San Donato Milanese, Milan 20097, Italy
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Morales Tellez JF, Moeyersons J, Testelmans D, Buyse B, Borzée P, Van Hoof C, Groenendaal W, Van Huffel S, Varon C. Technical aspects of cardiorespiratory estimation using subspace projections and cross entropy. Physiol Meas 2021; 42. [PMID: 34571494 DOI: 10.1088/1361-6579/ac2a70] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2021] [Accepted: 09/27/2021] [Indexed: 11/12/2022]
Abstract
BACKGROUND Respiratory sinus arrhythmia (RSA) is a form of cardiorespiratory coupling. Its quantification has been suggested as a biomarker to diagnose different diseases. Two state-of-the-art methods, based on subspace projections and entropy, are used to estimate the RSA strength and are evaluated in this paper. Their computation requires the selection of a model order, and their performance is strongly related to the temporal and spectral characteristics of the cardiorespiratory signals. OBJECTIVE To evaluate the robustness of the RSA estimates to the selection of model order, delays, changes of phase and irregular heartbeats as well as to give recommendations for their interpretation on each case. APPROACH Simulations were used to evaluate the model order selection when calculating the RSA estimates explained before, as well as 3 different scenarios that can occur in signals acquired in non-controlled environments and/or from patient populations: the presence of irregular heartbeats; the occurrence of delays between heart rate variability (HRV) and respiratory signals; and the changes over time of the phase between HRV and respiratory signals. MAIN RESULTS It was found that using a single model order for all the calculations suffices to characterize the RSA estimates correctly. In addition, the RSA estimation in signals containing more than 5 irregular heartbeats in a period of 5 minutes might be misleading. Regarding the delays between HRV and respiratory signals, both estimates are robust. For the last scenario, the two approaches tolerate phase changes up to 54°, as long as this lasts less than one fifth of the recording duration. SIGNIFICANCE Guidelines are given to compute the RSA estimates in non-controlled environments and patient populations.
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Affiliation(s)
- John Fredy Morales Tellez
- ESAT - STADIUS, Stadius Centre for Dynamical Systems, Signal Processing and Data Analytics, KU Leuven, Leuven, Flanders, BELGIUM
| | - Jonathan Moeyersons
- Department of Electrical Engineering (ESAT), KU Leuven, Leuven, Flanders, BELGIUM
| | - Dries Testelmans
- Department of Pneumology, KU Leuven University Hospitals Leuven, Leuven, BELGIUM
| | - Bertien Buyse
- Department of Respiratory Diseases, KUL UZ Gasthuisberg, Leuven, Flanders, BELGIUM
| | - Pascal Borzée
- Department of Pneumology, KU Leuven University Hospitals Leuven, Leuven, BELGIUM
| | | | | | - Sabine Van Huffel
- Department of Electrical Engineering (ESAT), KU Leuven, Leuven, Flanders, BELGIUM
| | - Carolina Varon
- Department of Electrical Engineering (ESAT), KU Leuven, Leuven, Flanders, BELGIUM
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de Abreu RM, Catai AM, Cairo B, Rehder-Santos P, da Silva CD, Signini ÉDF, Sakaguchi CA, Porta A. A Transfer Entropy Approach for the Assessment of the Impact of Inspiratory Muscle Training on the Cardiorespiratory Coupling of Amateur Cyclists. Front Physiol 2020; 11:134. [PMID: 32158402 PMCID: PMC7052290 DOI: 10.3389/fphys.2020.00134] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2019] [Accepted: 02/07/2020] [Indexed: 12/23/2022] Open
Abstract
The strength of cardiorespiratory interactions diminishes with age. Physical exercise can reduce the rate of this trend. Inspiratory muscle training (IMT) is a technique capable of improving cardiorespiratory interactions. This study evaluates the effect of IMT on cardiorespiratory coupling in amateur cyclists. Thirty male young healthy cyclists underwent a sham IMT of very low intensity (SHAM, n = 9), an IMT of moderate intensity at 60% of the maximal inspiratory pressure (MIP60, n = 10) and an IMT of high intensity at the critical inspiratory pressure (CIP, n = 11). Electrocardiogram, non-invasive arterial pressure, and thoracic respiratory movement (RM) were recorded before (PRE) and after (POST) training at rest in supine position (REST) and during active standing (STAND). The beat-to-beat series of heart period (HP) and systolic arterial pressure (SAP) were analyzed with the RM signal via a traditional non-causal approach, such as squared coherence function, and via a causal model-based transfer entropy (TE) approach. Cardiorespiratory coupling was quantified via the HP-RM squared coherence at the respiratory rate (K 2 HP-R M), the unconditioned TE from RM to HP (TER M → HP) and the TE from RM to HP conditioned on SAP (TER M → HP| SAP). In PRE condition we found that STAND led to a decrease of TER M → HP| SAP. After SHAM and CIP training this tendency was confirmed, while MIP60 inverted it by empowering cardiorespiratory coupling. This behavior was observed in presence of unvaried SAP mean and with usual responses of the baroreflex control and HP mean to STAND. TER M → HP and K 2 HP- RM were not able to detect the post-training increase of cardiorespiratory coupling strength during STAND, thus suggesting that conditioning out SAP is important for the assessment of cardiorespiratory interactions. Since the usual response of HP mean, SAP mean and baroreflex sensitivity to postural stressor were observed after MIP60 training, we conclude that the post-training increase of cardiorespiratory coupling during STAND in MIP60 group might be the genuine effect of some rearrangements at the level of central respiratory network and its interactions with sympathetic drive and vagal activity.
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Affiliation(s)
| | - Aparecida Maria Catai
- Department of Physical Therapy, Federal University of São Carlos, São Carlos, Brazil
| | - Beatrice Cairo
- Department of Biomedical Sciences for Health, University of Milan, Milan, Italy
| | | | | | | | | | - Alberto Porta
- Department of Biomedical Sciences for Health, University of Milan, Milan, Italy
- Department of Cardiothoracic – Vascular Anesthesia and Intensive Care, IRCCS Policlinico San Donato, Milan, Italy
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Müller V, Delius JAM, Lindenberger U. Hyper-Frequency Network Topology Changes During Choral Singing. Front Physiol 2019; 10:207. [PMID: 30899229 PMCID: PMC6416178 DOI: 10.3389/fphys.2019.00207] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2018] [Accepted: 02/18/2019] [Indexed: 01/08/2023] Open
Abstract
Choral singing requires the coordination of physiological subsystems within and across individuals. Previously, we suggested that the choir functions as a superordinate system that imposes boundary conditions on the dynamic features of the individual singers and found reliable differences in the network topography by analyzing within- and cross-frequency couplings (WFC and CFC, respectively). Here, we further refine our analyses to investigate hyper-frequency network (HFN) topology structures (i.e., the layout or arrangement of connections) using a graph-theoretical approach. In a sample of eleven singers and one conductor engaged in choral singing (aged between 23 and 56 years, and including five men and seven women), we calculated phase coupling (WFC and CFC) between respiratory, cardiac, and vocalizing subsystems across ten frequencies of interest. All these couplings were used for construction of HFN with nodes being a combination of frequency components and subsystems across choir participants. With regard to the network topology measures, we found that clustering coefficients (CCs) as well as local and global efficiency were highest and characteristic path lengths, correspondingly, were shortest when the choir sang a canon in parts as compared to singing it in unison. Furthermore, these metrics revealed a significant relationship to individual heart rate, as an indicator of arousal, and to an index of heart rate variability indicated by the LF/HF ratio (low and high frequency, respectively), and reflecting the balance between sympathetic and parasympathetic activity. In addition, we found that the CC and local efficiency for groups singing the same canon part were higher than for groups of singers constructed randomly post hoc, indicating stronger neighbor–neighbor connections in the former. We conclude that network topology dynamics are a crucial determinant of group behavior and may represent a potent biomarker for social interaction.
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Affiliation(s)
- Viktor Müller
- Center for Lifespan Psychology, Max Planck Institute for Human Development, Berlin, Germany
| | - Julia A M Delius
- Center for Lifespan Psychology, Max Planck Institute for Human Development, Berlin, Germany
| | - Ulman Lindenberger
- Center for Lifespan Psychology, Max Planck Institute for Human Development, Berlin, Germany.,Max Planck UCL Centre for Computational Psychiatry and Ageing Research, London, United Kingdom.,Max Planck UCL Centre for Computational Psychiatry and Ageing Research, Berlin, Germany
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Paced Breathing Increases the Redundancy of Cardiorespiratory Control in Healthy Individuals and Chronic Heart Failure Patients. ENTROPY 2018; 20:e20120949. [PMID: 33266673 PMCID: PMC7512533 DOI: 10.3390/e20120949] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/18/2018] [Revised: 12/04/2018] [Accepted: 12/06/2018] [Indexed: 11/17/2022]
Abstract
Synergy and redundancy are concepts that suggest, respectively, adaptability and fault tolerance of systems with complex behavior. This study computes redundancy/synergy in bivariate systems formed by a target X and a driver Y according to the predictive information decomposition approach and partial information decomposition framework based on the minimal mutual information principle. The two approaches assess the redundancy/synergy of past of X and Y in reducing the uncertainty of the current state of X. The methods were applied to evaluate the interactions between heart and respiration in healthy young subjects (n = 19) during controlled breathing at 10, 15 and 20 breaths/minute and in two groups of chronic heart failure patients during paced respiration at 6 (n = 9) and 15 (n = 20) breaths/minutes from spontaneous beat-to-beat fluctuations of heart period and respiratory signal. Both methods suggested that slowing respiratory rate below the spontaneous frequency increases redundancy of cardiorespiratory control in both healthy and pathological groups, thus possibly improving fault tolerance of the cardiorespiratory control. The two methods provide markers complementary to respiratory sinus arrhythmia and the strength of the linear coupling between heart period variability and respiration in describing the physiology of the cardiorespiratory reflex suitable to be exploited in various pathophysiological settings.
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Młyńczak M, Krysztofiak H. Discovery of Causal Paths in Cardiorespiratory Parameters: A Time-Independent Approach in Elite Athletes. Front Physiol 2018; 9:1455. [PMID: 30425645 PMCID: PMC6218878 DOI: 10.3389/fphys.2018.01455] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2018] [Accepted: 09/25/2018] [Indexed: 12/11/2022] Open
Abstract
Training of elite athletes requires regular physiological and medical monitoring to plan the schedule, intensity and volume of training, and subsequent recovery. In sports medicine, ECG-based analyses are well-established. However, they rarely consider the correspondence of respiratory and cardiac activity. Given such mutual influence, we hypothesize that athlete monitoring might be developed with causal inference and that detailed, time-related techniques should be preceded by a more general, time-independent approach that considers the whole group of participants and parameters describing whole signals. The aim of this study was to discover general causal paths among cardiac and respiratory variables in elite athletes in two body positions (supine and standing), at rest. ECG and impedance pneumography signals were obtained from 100 elite athletes. The mean heart rate, the root-mean-square difference of successive RR intervals (RMSSD), its natural logarithm (lnRMSSD), the mean respiratory rate (RR), the breathing activity coefficients, and the resulting breathing regularity (BR) were estimated. Several causal discovery frameworks were applied, comprising Generalized Correlations (GC), Causal Additive Modeling (CAM), Fast Greedy Equivalence Search (FGES), Greedy Fast Causal Inference (GFCI), and two score-based Bayesian network learning algorithms: Hill-Climbing (HC) and Tabu Search. The discovery of cardiorespiratory paths appears ambiguous. The main, still mild, rules best supported by data are: for supine - tidal volume causes heart activity variation, which causes average heart activity, which causes respiratory timing; and for standing - normalized respiratory activity variation causes average heart activity. The presented approach allows data-driven and time-independent analysis of elite athletes as a particular population, without considering prior knowledge. However, the results seem to be consistent with the medical background. Causality inference is an interesting mathematical approach to the analysis of biological responses, which are complex. One can use it to profile athletes and plan appropriate training. In the next step, we plan to expand the study using time-related causality analyses.
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Affiliation(s)
- Marcel Młyńczak
- Institute of Metrology and Biomedical Engineering, Faculty of Mechatronics, Warsaw University of Technology, Warsaw, Poland
| | - Hubert Krysztofiak
- Department of Applied Physiology, Mossakowski Medical Research Centre, Polish Academy of Sciences, Warsaw, Poland
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Krause H, Kraemer JF, Penzel T, Kurths J, Wessel N. On the difference of cardiorespiratory synchronisation and coordination. CHAOS (WOODBURY, N.Y.) 2017; 27:093933. [PMID: 28964129 DOI: 10.1063/1.4999352] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/15/2017] [Accepted: 05/18/2017] [Indexed: 06/07/2023]
Abstract
Cardiorespiratory phase synchronisation (CRS) is a type of cardiorespiratory coupling that manifests through a prediliction for heart beats to occur at specific points relative to the phase of the respiratory cycle. It has been under investigation for nearly 20 years, and while it seems to be mostly occurring in relaxed states such as deep sleep and anesthesia, no clear clinical implications have been established. Cardiorespiratory coordination (CRC) is a recent development in this field where the relationship between the respiratory onset and heart beat is analysed in the time domain and the possible relationship of each heart beat is considered for both the previous and the next respiratory onset. This ostensibly closely related effect must not only show relevant information content but also do so independent of CRS in order to be relevant for future studies. In this paper, we investigate CRC and its relation to CRS mainly using graphical and statistical methods on two exemplary datasets: measurements from a pregnant woman participating in a preeclampsia study and those from a man suffering from sleep apnea. We show fundamental differences between the results of both approaches and are able to show a formerly unknown dependency between the heart activity and respiratory rate, potentially indicating heartbeat-initiated inspiration. Despite their differences, methods developed for the quantification of CRS can be adapted to CRC. Completing the comparison is an investigation into the relationship between CRC and respiratory sinus arrhythmia. Similar to previous results for CRS, the two effects are found to be orthogonal, meaning that they can be observed independently or in conjunction.
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Affiliation(s)
- Harald Krause
- AG NLD - Cardiovascular Physics, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Jan F Kraemer
- AG NLD - Cardiovascular Physics, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Thomas Penzel
- AG NLD - Cardiovascular Physics, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Jürgen Kurths
- AG NLD - Cardiovascular Physics, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Niels Wessel
- AG NLD - Cardiovascular Physics, Humboldt-Universität zu Berlin, Berlin, Germany
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12
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Penzel T, Porta A, Stefanovska A, Wessel N. Recent advances in physiological oscillations. Physiol Meas 2017; 38:E1-E7. [PMID: 28452338 DOI: 10.1088/1361-6579/aa6780] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Affiliation(s)
- Thomas Penzel
- Sleep Medicine Center, Charité-Universitätsmedizin, Berlin, Germany. International Clinical Research Center, St. Annes University Hospital Brno, Brno, Czechia
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