Have a personal or library account? Click to login

The important role of time series stationarity for agreement of ultra-short-term heart rate variability in ski mountaineers: a case series

Open Access
|Oct 2025

References

  1. Abu-Arafeh, A., Jordan, H. & Drummond, G. (2016). Reporting of method comparison studies: a review of advice, an assessment of current practice, and specific suggestions for future reports. Br J Anaesth. 117, 569–575. https://doi.org/10.1093/bja/aew320.
  2. Aubert, A.E., Seps, B. & Beckers, F. (2003). Heart rate variability in athletes. Sports Med. 33(12), 889–919. https://doi.org/10.2165/00007256-200333120-00003.
  3. Berry, N.T., Bechke, E., Shriver, L.H., Calkins, S.D., Keane, S.P., Shanahan, L. and Wideman, L. (2021). Heart Rate Dynamics During Acute Recovery From Maximal Aerobic Exercise in Young Adults. Front Physiol. 12, 627320. https://doi.org/10.3389/fphys.2021.627320.
  4. Berry, N.T., Wideman, L. and Rhea, C.K. (2020). Variability and Complexity of Non-stationary Functions: Methods for Post-exercise HRV. Nonlinear Dynamics Psychol Life Sci. 24, 367–387.
  5. Bonetti, D.L. and Hopkins, W.G. (2010). Variation in performance times of elite flat-water canoeists from race to race. Int J Sports Physiol Perform. 5, 210–217. https://doi.org/10.1123/ijspp.5.2.210.
  6. Bortolan, L., Savoldelli, A., Pellegrini, B., Modena, R., Sacchi, M., Holmberg, H.C. and Supej, M. (2021). Ski Mountaineering: Perspectives on a Novel Sport to Be Introduced at the 2026 Winter Olympic Games. Front Physiol. 12, 737249. https://doi.org/10.3389/fphys.2021.737249.
  7. Bourdillon, N., Schmitt, L., Yazdani, S., Vesin, J.M. and Millet, G.P. (2017). Minimal Window Duration for Accurate HRV Recording in Athletes. Front Neurosci. 11, 456. https://doi.org/10.3389/fnins.2017.00456.
  8. Buchheit, M. (2018). Magnitudes matter more than beetroot juice. Sport Perform. Sci. Rep. 1, 1–3.
  9. Chen, Y.S., Clemente, F.M., Bezerra, P. and Lu, Y.X. (2020). Ultra-short-term and Short-term Heart Rate Variability Recording during Training Camps and an International Tournament in U-20 National Futsal Players. Int J Environ Res Public Health. 17, 775. https://doi.org/10.3390/ijerph17030775.
  10. Chen, Y.S., Pagaduan, J.C., Bezerra, P., Crowley-McHattan, Z.J., Kuo, C.D. and Clemente, F.M. (2021). Agreement of Ultra-Short-Term Heart Rate Variability Recordings During Overseas Training Camps in Under-20 National Futsal Players. Front Psychol. 12, 621399. https://doi.org/10.3389/fpsyg.2021.621399.
  11. Esco, M.R. and Flatt, A.A. (2014). Ultra-short-term heart rate variability indexes at rest and post-exercise in athletes: evaluating the agreement with accepted recommendations. J Sports Sci Med. 13, 535–541.
  12. Esco, M.R., Williford, H.N., Flatt, A.A., Freeborn, T.J. and Nakamura, F.Y. (2018). Ultra-shortened time-domain HRV parameters at rest and following exercise in athletes: an alternative to frequency computation of sympathovagal balance. Eur J Appl Physiol. 118, 175–184. https://doi.org/10.1007/s00421-017-3759-x.
  13. Gąsior, J.S., Gąsienica-Józkowy, M., Młyńczak, M., Rosoł, M., Makuch, R., Baranowski, R. and Werner, B. (2024). Heart rate dynamics and asymmetry during sympathetic activity stimulation and post-stimulation recovery in ski mountaineers-a pilot exploratory study. Front Sports Act Living. 6, 1336034. https://doi.org/10.3389/fspor.2024.1336034.
  14. Hoffmann, B., Flatt, A.A., Silva, L.E.V., Młyńczak, M., Baranowski, R., Dziedzic, E., Werner, B. and Gąsior, J.S. (2020). A Pilot Study of the Reliability and Agreement of Heart Rate, Respiratory Rate and Short-Term Heart Rate Variability in Elite Modern Pentathlon Athletes. Diagnostics (Basel). 10, 833. https://doi.org/10.3390/diagnostics10100833.
  15. Iizuka, T., Ohiwa, N., Atomi, T., Shimizu, M. and Atomi, Y. (2020). Morning Heart Rate Variability as an Indication of Fatigue Status in Badminton Players during a Training Camp. Sports (Basel). 8, 147. https://doi.org/10.3390/sports8110147.
  16. Lee, J., Koh, D. and Ong, C.N. (1989). Statistical evaluation of agreement between two methods for measuring a quantitative variable. Comput Biol Med. 19, 61–70. https://doi.org/10.1016/0010-4825(89)90036-x.
  17. Lindberg, K., Solberg, P., Bjørnsen, T., Helland, C., Rønnestad, B., Thorsen Frank, M., Haugen, T., Østerås, S., Kristoffersen, M., Midttun, M., Sæ-land, F., Eythorsdottir, I. and Paulsen G. (2022). Strength and Power Testing of Athletes: A Multicenter Study of Test-Retest Reliability. Int J Sports Physiol Perform. 27, 1103–1110. https://doi.org/10.1123/ijspp.2021-0558.
  18. Lundstrom, C.J., Foreman, N.A. and Biltz, G. (2023). Practices and Applications of Heart Rate Variability Monitoring in Endurance Athletes. Int J Sports Med. 44, 9–19. https://doi.org/10.1055/a-1864-9726.
  19. Magagnin, V., Bassani, T., Bari, V., Turiel, M., Maestri, R., Pinna, G.D. and Porta, A. (2011). Nonstationarities significantly distort short-term spectral, symbolic and entropy heart rate variability indices. Physiol Meas. 32, 1775–1786. https://doi.org/10.1088/0967-3334/32/11/S05.
  20. Mikielewicz, M., Gąsior, J.S. and Młyńczak, M. (2025). CoRRection – an open source software tool for RR intervals processing. Polish Journal of Medical Physics and Engineering 31, 10–19. https://doi.org/10.2478/pjmpe-2025-0002.
  21. Myles, P. S. and Cui, J. (2007). Using the Bland– Altman method to measure agreement with repeated measures. Br J Anaesth. 99, 309–311.
  22. Pereira, L.A., Flatt, A.A., Ramirez-Campillo, R., Loturco, I. and Nakamura, F.Y. (2016). Assessing Shortened Field-Based Heart-Rate-Variability-Data Acquisition in Team-Sport Athletes. Int J Sports Physiol Perform. 11, 154–158. https://doi.org/10.1123/ijspp.2015-0038.
  23. Piskorski, J. and Guzik, P. (2011). The structure of heart rate asymmetry: deceleration and acceleration runs. Physiol Meas. 32, 1011–1023. https://doi.org/10.1088/0967-3334/32/8/002.
  24. Ranganathan, P., Pramesh, C.S. and Aggarwal, R. (2017). Common pitfalls in statistical analysis: Measures of agreement. Perspect Clin Res. 8, 187–191. https://doi.org/10.4103/picr.PICR_123_17.
  25. Rhif, M., Ben Abbes, A., Farah, I.R., Martínez, B. and Sang, Y. (2019). Wavelet Transform Application for/in Non-Stationary Time-Series Analysis: A Review. Appl. Sci. 9, 1345. https://doi.org/10.3390/app9071345
  26. Schlitzer, G. (1995). Testing the stationarity of economic time series: further Monte Carlo evidence. Ricerche Economiche 49, 125–144. https://doi.org/10.1016/0035-5054(95)90019-5.
  27. Schneider, C., Hanakam, F., Wiewelhove, T., Döweling, A., Kellmann, M., Meyer, T., Pfeiffer, M., Ferrauti, A. (2018). Heart Rate Monitoring in Team Sports-A Conceptual Framework for Contextualizing Heart Rate Measures for Training and Recovery Prescription. Front Physiol. 9, 639. https://doi.org/10.3389/fphys.2018.00639.
  28. Schöffl, V.R., Bösl, T. and Lutter, C. (2022). Ski mountaineering: sports medical considerations for this new Olympic sport. Br J Sports Med. 56, 2–3. https://doi.org/10.1136/bjsports-2021-104846.
  29. Shaffer, F., Meehan, Z.M. and Zerr, C.L. (2020). A Critical Review of Ultra-Short-Term Heart Rate Variability Norms Research. Front Neurosci. 14, 594880. https://doi.org/10.3389/fnins.2020.594880.
  30. Silva, L.E.V., Fazan, R Jr. and Marin-Neto, J.A. (2020). PyBioS: A freeware computer software for analysis of cardiovascular signals. Comput Methods Programs Biomed. 197, 105718. https://doi.org/10.1016/j.cmpb.2020.105718.
  31. Tarvainen, M.P., Ranta-Aho, P.O. and Karjalainen, P.A. (2002). An advanced detrending method with application to HRV analysis. IEEE Trans Biomed Eng. 49, 172–175. https://doi.org/10.1109/10.979357.
  32. Weber, E.J., Molenaar, P.C. and van der Molen, M.W. (1992). A nonstationarity test for the spectral analysis of physiological time series with an application to respiratory sinus arrhythmia. Psychophysiology. 29, 55–65. https://doi.org/10.1111/j.1469-8986.1992.tb02011.x.
  33. Volpes, G., Barà, C., Busacca, A., Stivala, S., Javorka, M., Faes, L. and Pernice, R. (2022). Feasibility of Ultra-Short-Term Analysis of Heart Rate and Systolic Arterial Pressure Variability at Rest and during Stress via Time-Domain and Entropy-Based Measures. Sensors (Basel). 22, 9149. https://doi.org/10.3390/s22239149.
Language: English
Page range: 281 - 289
Submitted on: May 29, 2025
Accepted on: Sep 9, 2025
Published on: Oct 29, 2025
Published by: University of Physical Education in Warsaw
In partnership with: Paradigm Publishing Services
Publication frequency: 1 times per year

© 2025 Jakub S. Gąsior, Marcel Młyńczak, Maciej Rosoł, Maciej Gąsienica-Józkowy, Robert Makuch, Łukasz Małek, Bożena Werner, published by University of Physical Education in Warsaw
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.