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Kubios Threshold-Based Artefact Correction Affects Heart Rate Variability Parameters in Elite Athletes

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Abstract

Purpose

Kubios is an intuitive software intended to provide heart rate variability (HRV) processing. It is widely used to assess athletes’ readiness for new training sessions and autonomic balance responses to the training programme. However, Kubios’ filtering levels’ effect on artefact correction for elite athletes is still unclear. This study aims to assess the impact of different Kubios threshold-based artefact correction levels on the HRV-derived parameters in male and female elite athletes.

Methods

One hundred and seventeen elite athletes (55 females) from 21 Olympic sports participated in this study. All participants underwent an HRV recording in the morning after 24 h of no intense exercise, caffeine, and alcohol consumption. The heart rate signals were acquired with the Polar V800 monitor, and time and frequency domain-derived variables were calculated with and without Kubios’ five levels of filtering.

Results

Kubios filtering levels significantly affected the HRV results in both time and frequency domains in female and male elite athletes. “Medium”, “Strong”, and “Very Strong” filtering resulted in an interpolation larger than 5% (above recommended by the software developers) in 3.4%, 28.2%, and 95% of the entire group data, respectively. Moreover, the “Very Strong” filter significantly lowered HRV variables and promoted mean values exceeding the 5% interpolation for females (33.35%) and males (38.17%).

Conclusion

The “Very Low” and “Low” threshold-based artefact correction levels were more suitable for processing HRV data from female and male elite athletes when Kubios was used.

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Data Availability

The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.

References

  1. Alcantara JMA, Plaza-Florido A, Amaro-Gahete FJ, Acosta FM, Migueles JH, Molina-Garcia P, Sacha J, Sanchez-Delgado G, Martinez-Tellez B. Impact of using different levels of threshold-based artefact correction on the quantification of heart rate variability in three independent human cohorts. J Clin Med. 2020;9(2):325. https://doi.org/10.3390/jcm9020325.

    Article  PubMed  PubMed Central  Google Scholar 

  2. Antelmi I, De Paula RS, Shinzato AR, Peres CA, Mansur AJ, Grupi CJ. Influence of age, gender, body mass index, and functional capacity on heart rate variability in a cohort of subjects without heart disease. Am J Cardiol. 2004;93(3):381–5. https://doi.org/10.1016/j.amjcard.2003.09.065.

    Article  PubMed  Google Scholar 

  3. Aranda C, De La Cruz B, Naranjo J. Effects of different automatic filters on the analysis of heart rate variability with Kubios HRV software. Arch Med del Deport. 2017;34(4):196–200.

    Google Scholar 

  4. Azevedo LF, Perlingeiro PS, Hachul DT, Gomes-Santos IL, Brum PC, Allison TG, Negrão CE, De Matos LDNJ. Sport modality affects bradycardia level and its mechanisms of control in professional athletes. Int J Sports Med. 2014;35(11):954–9. https://doi.org/10.1055/s-0033-1364024.

    Article  CAS  PubMed  Google Scholar 

  5. Bourdillon N, Yazdani S, Vesin J-M, Schmitt L, Millet GP. RMSSD is more sensitive to artifacts than frequency-domain parameters: implication in athletes’ monitoring. J Sport Sci Med. 2022;21(2):260–6. https://doi.org/10.52082/jssm.2022.260.

    Article  Google Scholar 

  6. Buchheit M. Monitoring training status with HR measures: do all roads lead to Rome? Front Physiol. 2014;5:1–19. https://doi.org/10.3389/fphys.2014.00073.

    Article  Google Scholar 

  7. Catai AM, Pastre CM, Godoy MF, Silva E, Takahashi ACM, Vanderlei LCM. Heart rate variability: are you using it properly? Standardisation checklist of procedures. Brazilian J Phys Ther. 2020;24(2):91–102. https://doi.org/10.1016/j.bjpt.2019.02.006.

    Article  Google Scholar 

  8. Cohen J. Statistical power analysis for the behavioral sciences. 2nd ed. Hillsdale: Lawrence Erlbaum; 1988.

    Google Scholar 

  9. Cooke WH, Carter JR. Strength training does not affect vagal? Cardiac control or cardiovagal baroreflex sensitivity in young healthy subjects. Eur J Appl Physiol. 2005;93(5–6):719–25. https://doi.org/10.1007/s00421-004-1243-x.

    Article  PubMed  Google Scholar 

  10. Gamelin FX, Berthoin S, Bosquet L. Validity of the polar S810 heart rate monitor to measure R-R intervals at rest. Med Sci Sport Exerc. 2006;38(5):887–93. https://doi.org/10.1249/01.mss.0000218135.79476.9c.

    Article  Google Scholar 

  11. Giles D, Draper N, Neil W. Validity of the polar V800 heart rate monitor to measure RR intervals at rest. Eur J Appl Physiol. 2016;116(3):563–71. https://doi.org/10.1007/s00421-015-3303-9.

    Article  PubMed  Google Scholar 

  12. Hernández-Vicente A, Hernando D, Marín-Puyalto J, Vicente-Rodríguez G, Garatachea N, Pueyo E, Bailón R. Validity of the polar H7 heart rate sensor for heart rate variability analysis during exercise in different age, body composition and fitness level groups. Sensors. 2021;21(3):902. https://doi.org/10.3390/s21030902.

    Article  PubMed  PubMed Central  ADS  Google Scholar 

  13. Hinde K, White G, Armstrong N. Wearable devices suitable for monitoring twenty four hour heart rate variability in military populations. Sensors. 2021;21(4):1061. https://doi.org/10.3390/s21041061.

    Article  PubMed  PubMed Central  ADS  Google Scholar 

  14. Jensen-Urstad K, Storck N, Bouvier F, Ericson M, Lindbland LE, Jensen-Urstad M. Heart rate variability in healthy subjects is related to age and gender. Acta Physiol Scand. 1997;160(3):235–41. https://doi.org/10.1046/j.1365-201X.1997.00142.x.

    Article  CAS  PubMed  Google Scholar 

  15. Kiviniemi AM, Hautala AJ, Kinnunen H, Tulppo MP. Endurance training guided individually by daily heart rate variability measurements. Eur J Appl Physiol. 2007;101(6):743–51. https://doi.org/10.1007/s00421-007-0552-2.

    Article  PubMed  Google Scholar 

  16. Kiviniemi AM, Hautala AJ, Kinnunen H, Nissila J, Virtanen P, Karjalainen J, Tulppo MP. Daily exercise prescription on the basis of HR variability among men and women. Med Sci Sport Exerc. 2010;42(7):1355–63. https://doi.org/10.1249/MSS.0b013e3181cd5f39.

    Article  Google Scholar 

  17. Malik M, Bigger JT, Camm AJ, Kleiger RE, Malliani A, Moss AJ, Schwartz PJ. Heart rate variability: standards of measurement, physiological interpretation, and clinical use. Eur Heart J. 1996;17(3):354–81. https://doi.org/10.1093/oxfordjournals.eurheartj.a014868.

    Article  Google Scholar 

  18. Michels N, Clays E, De Buyzere M, Huybrechts I, Marild S, Vanaelst B, De Henauw S, Sioen I. Determinants and reference values of short-term heart rate variability in children. Eur J Appl Physiol. 2013;113(6):1477–88. https://doi.org/10.1007/s00421-012-2572-9.

    Article  PubMed  Google Scholar 

  19. Morales J, Garcia V, García-Massó X, Salvá P, Escobar R, Buscà B. The use of heart rate variability in assessing precompetitive stress in high-standard judo athletes. Int J Sports Med. 2012;34(02):144–51. https://doi.org/10.1055/s-0032-1323719.

    Article  PubMed  Google Scholar 

  20. Plaza-Florido A, Alcantara JMA, Amaro-Gahete FJ, Sacha J, Ortega FB. Cardiovascular risk factors and heart rate variability: impact of the level of the threshold-based artefact correction used to process the heart rate variability signal. J Med Syst. 2021;45(1):2. https://doi.org/10.1007/s10916-020-01673-9.

    Article  CAS  Google Scholar 

  21. Plews DJ, Laursen PB, Kilding AE, Buchheit M. Heart rate variability in elite triathletes, is variation in variability the key to effective training? A case comparison. Eur J Appl Physiol. 2012;112(11):3729–41. https://doi.org/10.1007/s00421-012-2354-4.

    Article  PubMed  Google Scholar 

  22. Plews DJ, Laursen PB, Stanley J, Kilding AE, Buchheit M. Training adaptation and heart rate variability in elite endurance athletes: opening the door to effective monitoring. Sport Med. 2013;43(9):773–81. https://doi.org/10.1007/s00421-012-2354-4.

    Article  Google Scholar 

  23. Saleem S, Hussain MM, Majeed SMI, Khan MA. Gender differences of heart rate variability in healthy volunteers. J Pak Med Assoc. 2012;62(5):422–5.

    PubMed  Google Scholar 

  24. Salo MA, Huikuri HV, Seppanen T. Ectopic beats in heart rate variability analysis: effects of editing on time and frequency domain measures. Ann Noninvasive Electrocardiol. 2001;6(1):5–17. https://doi.org/10.1111/j.1542-474X.2001.tb00080.x.

    Article  CAS  PubMed  Google Scholar 

  25. Shaffer F, Ginsberg JP. An overview of heart rate variability metrics and norms. Front Public Heal. 2017;5:1–17. https://doi.org/10.3389/fpubh.2017.00258.

    Article  Google Scholar 

  26. Tarvainen MP, Niskanen J-P, Lipponen JA, Ranta-aho PO, Karjalainen PA. Kubios HRV—heart rate variability analysis software. Comput Methods Programs Biomed. 2014;113(1):210–20. https://doi.org/10.1016/j.cmpb.2013.07.024.

    Article  PubMed  Google Scholar 

  27. Umetani K, Singer DH, McCraty R, Atkinson M. Twenty-four hour time domain heart rate variability and heart rate: relations to age and gender over nine decades. J Am Coll Cardiol. 1998;31(3):593–601. https://doi.org/10.1016/S0735-1097(97)00554-8.

    Article  CAS  PubMed  Google Scholar 

  28. Voss A, Schroeder R, Heitmann A, Peters A, Perz S. Short-term heart rate variability—influence of gender and age in healthy subjects. Hernandez A V, editor. PLoS ONE. 2015;10(3):e0118308. https://doi.org/10.1371/journal.pone.0118308.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Young FLS, Leicht AS. Short-term stability of resting heart rate variability: influence of position and gender. Appl Physiol Nutr Metab. 2011;36(2):210–8. https://doi.org/10.1139/h10-103.

    Article  PubMed  Google Scholar 

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Acknowledgements

We are very thankful to the athletes who made this study possible.

Funding

The study was supported by the Brazil Olympic Committee and the Brazilian Funding Authority for Studies and Projects (FINEP).

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Authors and Affiliations

  1. Olympic Laboratory, Brazil Olympic Committee, Av. Embaixador Abelardo Bueno s/n Parque Aquático Maria Lenk, Rio de Janeiro, CEP 22775-040, Brazil

    Alex Itaborahy, Raul Freire & Matheus Hausen

Authors
  1. Alex Itaborahy
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  2. Raul Freire
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  3. Matheus Hausen
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Contributions

All authors contributed to the study’s conception and design. AI, RF, and MH performed material preparation, data collection, and analysis. AI wrote the first draft of the manuscript and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Alex Itaborahy.

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Conflict of Interest

The authors declare that the results were reported honestly and without inappropriate data manipulation. They also declare no conflicts of interest.

Ethical Approval

The study was approved by the Research Ethics Committee of the Rio de Janeiro Municipal Health Secretariat and was conducted following the Declaration of Helsinki (revision of 2013).

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Itaborahy, A., Freire, R. & Hausen, M. Kubios Threshold-Based Artefact Correction Affects Heart Rate Variability Parameters in Elite Athletes. J. of SCI. IN SPORT AND EXERCISE 6, 52–60 (2024). https://doi.org/10.1007/s42978-022-00210-z

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