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Correlation properties and respiratory frequency of ECG-derived heart rate variability during multiple intervals of prolonged running in female and male long-distance runners

##article.authors##

  • Thomas Gronwald Institute of Interdisciplinary Exercise Science and Sports Medicine, MSH Medical School Hamburg, Hamburg, Germany; G-Lab, Faculty of Applied Sport Sciences and Personality, BSP Business and Law School, Berlin, Germany https://orcid.org/0000-0001-5610-6013
  • Marcelle Schaffarczyk Institute of Interdisciplinary Exercise Science and Sports Medicine, MSH Medical School Hamburg, Hamburg, Germany
  • Dominik Fohrmann Institute of Interdisciplinary Exercise Science and Sports Medicine, MSH Medical School Hamburg, Hamburg, Germany
  • Olaf Hoos Center for Sports and Physical Education, Faculty of Human Sciences, Julius-Maximilians-University Wuerzburg, Wuerzburg, Germany
  • Karsten Hollander Institute of Interdisciplinary Exercise Science and Sports Medicine, MSH Medical School Hamburg, Hamburg, Germany

DOI:

https://doi.org/10.51224/SRXIV.448

Keywords:

HRV, DFAa1, autonomic nervous system, running economy, exercise prescription

Abstract

Aim: To evaluate alterations of the non-linear short-term scaling exponent alpha1 of detrended fluctuation analysis (DFAa1) of heart rate (HR) variability (HRV) as a sensitive marker for assessing global physiological demands during prolonged running intervals. Furthermore, agreement of ECG-derived respiratory frequency (EDR) compared to gas exchange-derived respiratory frequency (RF) was evaluated with the same chest belt device.

Methods: Fifteen trained female and male long-distance runners completed four running bouts over five minutes on a treadmill at marathon pace. During the last three minutes of each bout gas exchange data and a single-channel ECG for the determination of HR, DFAa1 of HRV, EDR and RF were analyzed. Additionally, blood lactate concentration (BLC) was determined and rating of perceived exertion (RPE) was requested.

Results: DFAa1, oxygen consumption, BLC, and RPE showed stable behaviors comparing the running intervals. Only HR (p<0.001, d=0.17) and RF (p=0.012, d=0.20) indicated slight increases with small effect sizes. Additionally, results point towards remarkable inter-individual differences in all internal load metrics. The comparison of EDR with RF during running revealed high correlations (r=0.80, p<0.001, ICC3,1=0.87) and low mean differences (1.8±4.4 breaths/min), but rather large limits of agreement with 10.4 to -6.8 breaths/min.

Conclusions: Results show the necessity of EDR methodology improvement before being used in a wide range of individuals and sports applications. Relationship of DFAa1 to other internal load metrics, including RF, in quasi-steady-state conditions bears the potential for further evaluation of exercise prescription and may enlighten decoupling mechanisms in exercise bouts of different type and duration.

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References

Bailón, R., Garatachea, N., de la Iglesia, I., Casajús, J. A., & Laguna, P. (2013). Influence of running stride frequency in heart rate variability analysis during treadmill exercise testing. IEEE transactions on bio-medical engineering, 60(7), 1796-1805.

Bland, J.M. & Altman, D.G. (1999). Measuring Agreement in Method Comparison Studies. Stat. Methods Med. Res., 8, 135-160.

Borg GA. Psychophysical bases of perceived exertion. Med Sci Sports Exerc. 1982;14(5):377-81.

Cartón-Llorente, A., Roche-Seruendo, L. E., Mainer-Pardos, E., Nobari, H., Rubio-Peirotén, A., Jaén-Carrillo, D., & García-Pinillos, F. (2022). Acute effects of a 60-min time trial on power-related parame-ters in trained endurance runners. BMC sports science, medicine & rehabilitation, 14(1), 142.

Chan, Y.H. (2003). Biostatistics 104: Correlational Analysis. Singapore Med. J., 44, 614-619.

Cohen, J. (1988). Statistical Power Analysis for the Behavioural Sciences. Hillsdale, MI, USA: Erlbaum.

Fohrmann, D., Schafarczyk, M., Menge, C., Willwacher, S., Gronwald, T. & Hollander, K. (2024). Biomechanical Factors Associated with Changes in Running Economy in Long-Distance Runners Using Advanced Footwear Technology. In review.

Garber, C. E., Blissmer, B., Deschenes, M. R., Franklin, B. A., Lamonte, M. J., Lee, I. M., Nieman, D. C., Swain, D. P., & American College of Sports Medicine (2011). American College of Sports Medicine position stand. Quantity and quality of exercise for developing and maintaining cardiorespiratory, musculoskeletal, and neuromotor fitness in apparently healthy adults: guidance for prescribing exercise. Medicine and science in sports and exercise, 43(7), 1334-1359.

Gronwald, T., & Hoos, O. (2020). Correlation properties of heart rate variability during endurance exercise: A systematic review. Annals of noninvasive electrocardiology : the official journal of the International Society for Holter and Noninvasive Electrocardiology, Inc, 25(1), e12697.

Gronwald, T., Berk, S., Altini, M., Mourot, L., Hoos, O., & Rogers, B. (2021b). Real-Time Estimation of Aerobic Threshold and Exercise Intensity Distribution Using Fractal Correlation Properties of Heart Rate Variability: A Single-Case Field Application in a Former Olympic Triathlete. Frontiers in sports and active living, 3, 668812.

Gronwald, T., Hoos, O., & Hottenrott, K. (2019). Effects of Acute Normobaric Hypoxia on Non-linear Dynamics of Cardiac Autonomic Activity During Constant Workload Cycling Exercise. Frontiers in physiology, 10, 999.

Gronwald., T. Horn, L., Schaffarczyk, M. & Hoos, O. (2024). Correlation properties of heart rate variability for exercise prescription during prolonged running at constant speeds: A randomized cross-over trial. European Journal of Sports Science, accepted.

Gronwald, T., Ludyga, S., Hoos, O., & Hottenrott, K. (2018). Non-linear dynamics of cardiac autonomic activity during cycling exercise with varied cadence. Human movement science, 60, 225-233.

Gronwald, T., Rogers, B., & Hoos, O. (2020). Fractal Correlation Properties of Heart Rate Variability: A New Biomarker for Intensity Distribution in Endurance Exercise and Training Prescription? Frontiers in physiology, 11, 550572.

Gronwald, T., Rogers, B., Hottenrott, L., Hoos, O., & Hottenrott, K. (2021a). Correlation Properties of Heart Rate Variability during a Marathon Race in Recreational Runners: Potential Biomarker of Complex Regulation during Endurance Exercise. Journal of sports science & medicine, 20(4), 557-563.

Gronwald, T., Törpel, A., Herold, F., & Budde, H. (2020). Perspective of Dose and Response for Individualized Physical Exercise and Training Prescription. Journal of functional morphology and kinesiology, 5(3), 48.

Hautala, A. J., Mäkikallio, T. H., Seppänen, T., Huikuri, H. V., & Tulppo, M. P. (2003). Short-term correlation properties of R-R interval dynamics at different exercise intensity levels. Clinical physiology and functional imaging, 23(4), 215–223.

Hottenrott, L., Hottenrott, K. & Gronwald, T. (2020). Physiology and fast marathons: Interpersonal synchronization in pacing strategies and locomotor-respiratory and -cardiac coupling as potential factors influencing marathon running performance. Journal of Applied Physiology, 128 (4), 1077

Lipponen, J. A., & Tarvainen, M. P. (2019). A robust algorithm for heart rate variability time series artefact correction using novel beat classification. Journal of medical engineering & technology, 43(3), 173-181.

Lipponen, J.A. & Tarvainen, M.P. (2021). Accuracy of Kubios HRV software respiratory rate estimation algorithms. White paper accessed on April 24th 2024: https://www.kubios.com/downloads/RESP_white_paper.pdf

Ludbrook J. (2010). Confidence in Altman-Bland plots: a critical review of the method of differences. Clinical and experimental pharmacology & physiology, 37(2), 143–149.

Mateo-March, M., Moya-Ramón, M., Javaloyes, A., Sánchez-Muñoz, C., & Clemente-Suárez, V. J. (2023). Validity of detrended fluctuation analysis of heart rate variability to determine intensity thresholds in elite cyclists. European journal of sport science, 23(4), 580–587.

Maunder, E., Seiler, S., Mildenhall, M. J., Kilding, A. E., & Plews, D. J. (2021). The Importance of 'Durability' in the Physiological Profiling of Endurance Athletes. Sports medicine (Auckland, N.Z.), 51(8), 1619–1628.

Meyler, S., Bottoms, L., Wellsted, D., & Muniz-Pumares, D. (2023). Variability in exercise tolerance and physiological responses to exercise prescribed relative to physiological thresholds and to maximum oxygen uptake. Experimental physiology, 108(4), 581–594.

Nicolò, A., & Sacchetti, M. (2023). Differential control of respiratory frequency and tidal volume during exer-cise. European journal of applied physiology, 123(2), 215–242.

Nicolò, A., Massaroni, C., & Passfield, L. (2017). Respiratory Frequency during Exercise: The Neglected Physio-logical Measure. Frontiers in physiology, 8, 922.

Nicolò, A., Massaroni, C., Schena, E., & Sacchetti, M. (2020). The Importance of Respiratory Rate Monitoring: From Healthcare to Sport and Exercise. Sensors (Basel, Switzerland), 20(21), 6396.

Niizeki, K., Kawahara, K., & Miyamoto, Y. (1993). Interaction among cardiac, respiratory, and locomotor rhythms during cardiolocomotor synchronization. Journal of applied physiology (Bethesda, Md. : 1985), 75(4), 1815-1821.

Passfield, L., Murias, J. M., Sacchetti, M., & Nicolò, A. (2022). Validity of the Training-Load Concept. International journal of sports physiology and performance, 17(4), 507-514.

Peng, C. K., Havlin, S., Stanley, H. E., & Goldberger, A. L. (1995). Quantification of scaling exponents and crossover phenomena in nonstationary heartbeat time series. Chaos (Woodbury, N.Y.), 5(1), 82-87.

Perrey, S., Grappe, F., Girard, A., Bringard, A., Groslambert, A., Bertucci, W., & Rouillon, J. D. (2003). Physiological and metabolic responses of triathletes to a simulated 30-min time-trial in cycling at self-selected intensity. International journal of sports medicine, 24(2), 138-143.

Persson P. B. (1996). Modulation of cardiovascular control mechanisms and their interaction. Physiological reviews, 76(1), 193-244.

Rogers, B., & Gronwald, T. (2022). Fractal Correlation Properties of Heart Rate Variability as a Biomarker for Intensity Distribution and Training Prescription in Endurance Exercise: An Update. Frontiers in physiology, 13, 879071.

Rogers, B., Giles, D., Draper, N., Hoos, O., & Gronwald, T. (2021b). A New Detection Method Defining the Aerobic Threshold for Endurance Exercise and Training Prescription Based on Fractal Correlation Properties of Heart Rate Variability. Frontiers in physiology, 11, 596567.

Rogers, B., Giles, D., Draper, N., Mourot, L., & Gronwald, T. (2021a). Detection of the Anaerobic Threshold in Endurance Sports: Validation of a New Method Using Correlation Properties of Heart Rate Variability. Journal of functional morphology and kinesiology, 6(2), 38.

Rogers, B., Mourot, L., Doucende, G., & Gronwald, T. (2021c). Fractal correlation properties of heart rate variability as a biomarker of endurance exercise fatigue in ultramarathon runners. Physiological reports, 9(14), e14956.

Rogers, B., Schaffarczyk, M., & Gronwald, T. (2022a). Estimation of Respiratory Frequency in Women and Men by Kubios HRV Software Using the Polar H10 or Movesense Medical ECG Sensor during an Exercise Ramp. Sensors (Basel, Switzerland), 22(19), 7156.

Rogers, B., Schaffarczyk, M., Clauß, M., Mourot, L., & Gronwald, T. (2022b). The Movesense Medical Sensor Chest Belt Device as Single Channel ECG for RR Interval Detection and HRV Analysis during Resting State and Incremental Exercise: A Cross-Sectional Validation Study. Sensors (Basel, Switzerland), 22(5), 2032.

Santos, R. V., Almeida, A. L., Caperuto, E. C., Martins, E., Jr, & Costa Rosa, L. F. (2006). Effects of a 30-km race upon salivary lactate correlation with blood lactate. Comparative biochemistry and physiology. Part B, Biochemistry & molecular biology, 145(1), 114-117.

Schaffarczyk, M., Rogers, B., Reer, R., & Gronwald, T. (2022). Fractal correlation properties of HRV as a noninvasive biomarker to assess the physiological status of triathletes during simulated warm-up sessions at low exercise intensity: a pilot study. BMC sports science, medicine & rehabilitation, 14(1), 203.

Schaffarczyk, M., Rogers, B., Reer, R., & Gronwald, T. (2023). Validation of a non-linear index of heart rate variability to determine aerobic and anaerobic thresholds during incremental cycling exercise in women. European journal of applied physiology, 123(2), 299-309.

Schwalm, L., Fohrmann, D., Schaffarczyk, M., Gronwald, T., Willwacher, S. & Hollander, K. (2024). Habituation does not change running economy in advanced footwear technology. International Journal of Sports Physiology and Performance, accepted.

Sempere-Ruiz, N., Sarabia, J. M., Baladzhaeva, S., & Moya-Ramón, M. (2024). Reliability and validity of a non-linear index of heart rate variability to determine intensity thresholds. Frontiers in physiology, 15, 1329360.

Smyth, B., Maunder, E., Meyler, S., Hunter, B., & Muniz-Pumares, D. (2022). Decoupling of Internal and External Workload During a Marathon: An Analysis of Durability in 82,303 Recreational Runners. Sports medicine (Auckland, N.Z.), 52(9), 2283-2295.

Spiriev, B. (2022). World Athletics Scoring Tables of Athletics. World Athletics. Accessed 23-02-2024, 2024. Table accessed on April 24th 2024: https://worldathletics.org/news/news/scoring-tables-2022

Tanaka, H., Monahan, K. D., & Seals, D. R. (2001). Age-predicted maximal heart rate revisited. Journal of the American College of Cardiology, 37(1), 153-156.

Tipton, M. J., Harper, A., Paton, J. F. R., & Costello, J. T. (2017). The human ventilatory response to stress: rate or depth? The Journal of physiology, 595(17), 5729-5752.

Van Hooren, B., Bongers, B. C., Rogers, B., & Gronwald, T. (2023a). The Between-Day Reliability of Correlation Properties of Heart Rate Variability During Running. Applied psychophysiology and biofeedback, 48(4), 453-460.

Van Hooren, B., Mennen, B., Gronwald, T., Bongers, B. C., & Rogers, B. (2023b). Correlation properties of heart rate variability to assess the first ventilatory threshold and fatigue in runners. Journal of sports sciences, 1-10. Advance online publication.

Vitazkova, D., Foltan, E., Kosnacova, H., Micjan, M., Donoval, M., Kuzma, A., Kopani, M., & Vavrinsky, E. (2024). Advances in Respiratory Monitoring: A Comprehensive Review of Wearable and Remote Technologies. Biosensors, 14(2), 90.

White, D. W., & Raven, P. B. (2014). Autonomic neural control of heart rate during dynamic exercise: revisi-ted. The Journal of physiology, 592(12), 2491-2500.

Zuccarelli, L., Porcelli, S., Rasica, L., Marzorati, M., & Grassi, B. (2018). Comparison between Slow Components of HR and V˙O2 Kinetics: Functional Significance. Medicine and science in sports and exercise, 50(8), 1649-1657.

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2024-09-07