Farklı Tükenme Aralıkları ve Matematiksel Model Kullanımının Kritik Güç Tahminlerine Etkisi

Year 2021, Volume: 32 Issue: 3, 151 - 166, 27.09.2021

Mahdi Norouzı Refik Çabuk Görkem Aybars Balcı Hakan As Özgür Özkaya

https://doi.org/10.17644/sbd.931304

Cited By: 2

Abstract

Tahmin edilen kritik güç (KG) düzeyi, tercih edilen matematiksel model ve farklı tükenme zaman aralıklarına bağlı olarak %5-20 oranında farklılaşır. Bu oranlarda farklılaşan tahminler, KG ile ilişkili bir takım çelişkili sonuçlar yaratır. Bu çalışmanın amacı üç farklı tükenme aralığı (kısa: 2-10 dakika; orta: 2-15 dakika; uzun: 2-20 dakika) kullanılarak, her bir aralık için beş farklı matematiksel model (doğrusal toplam iş (KG1), doğrusal 1/zaman (KG2), doğrusal olmayan 2-parametreli (KG3), doğrusal olmayan 3-parametreli (KG4), ve üstel (KG5)), yoluyla elde edilen KG tahminlerinden hangisi ya da hangilerinin maksimal laktat dengesi (MLD), ventilasyon eşiği (VE), solunumsal kompanzasyon noktası (SKN) ve/veya kritik eşikle (KE) ilişkili olduğunu değerlendirmektir. Çalışmaya 10 iyi antrene erkek bisiklet sporcusu gönüllü olarak katılmıştır. Sporcuların VE ve SKN düzeyleri kademeli rampa testleriyle belirlenmiştir. Maksimal oksijen kullanımı, zirve güç çıktısı, MLD, KE ve KG’yi hesaplamak için farklı günlerde sabit iş oranlarında testler uygulanmıştır. Elde edilen veriler geçerlilik analizleri ile sınanmıştır. Kullanılan matematiksel model ve tükenme aralıkları değiştikçe elde edilen KG düzeyleri %20’ye kadar farklılaşmıştır. KG4 dışındaki diğer KG düzeyleri MLD ve VE’ye karşılık gelen iş oranlarından daha yüksektir (p<0,05). Kısa tükenme aralıklarıyla bulunan KG5 değeri, KE ve SKN iş oranlarına karşılık gelmiştir (p>0,05; tahmini standart hata ~%4 ve r>0,95). Tercih edilen tükenme aralığı fark etmeksizin diğer matematiksel modellerden elde edilen KG’ler herhangi bir anaerobik eşik indeksini tahmin etmede yetersizdir (p<0,05). Sonuç olarak, yalnızca kısa tükenme aralığıyla belirlenen KG5 düzeyinin, KE ve SKN iş oranlarını tahmin etmede kullanılabileceği gösterilmiştir. Diğer eşik indekslerinin KG yoluyla tahmin edilmesi uygun değildir.

Keywords

kritik eşik, kritik güç, maksimal laktat dengesi, solunumsal kompenzasyon noktası, ventilasyon eşiği

Project Number

2017.004

Thanks

Ege Üniversitesi BAP

The Effect of Using Different Exhaustion Intervals and Mathematical Models on Critical Power Estimations

Abstract

Predicted critical power (CP) varies up to 5-20% depending on the preferred mathematical model and different time to exhaustion intervals. Those differentiation rates related to CP estimations cause some contradictory results. The aim of this study was to evaluate the relationship between CP predictions obtained from three different exhaustion approaches (short: 2-10 minutes; medium: 2-15 minutes; long: 2-20 minutes) using five mathematical models (linear total work (CP1), linear 1/time (CP2), nonlinear 2-parameter (CP3), nonlinear 3-parameter (CP4) and exponential (CP5)), and other indices such as maximal lactate steady-state (MLSS), ventilatory threshold (VT), respiratory compensation point (RCP) and critical threshold (CT). 10 well trained male cyclists voluntarily participated in the study. VT and RCP levels of the athletes were determined by incremental ramp tests. Constant work rate exercises were applied on different days to determine maximal oxygen uptake, peak power output, MLSS, CT and CP. Obtained data were tested by validity analysis. As mathematical models and exhaustion intervals changed, the CP predictions varied up to 20%. Except the CP4, other CP estimations were higher than the work rates corresponding to the MLSS and VT (p<0.05). The CP5, which was estimated by short exhaustion interval, corresponded to the work rates belonging to the CT and RCP (p>0.05; standard error of estimate ~4% and r>0.95). Regardless of the preferred exhaustion interval, CP predictions obtained from the other mathematical models were insufficient to estimate any of anaerobic threshold indices (p<0.05). As a result, the CP5 estimated by short exhaustion interval can be used to predict the work rates corresponded to the CT and RCP. It was not appropriate to estimate the other threshold intensities by the CP. 

Keywords

Critical threshold, critical power, maximal lactate steady state, respiratory compensation point, ventilatory threshold

Project Number

2017.004

References

• 1. Atkinson, G., ve Nevill, A. M. (1998). Statistical methods for assessing measurement error (reliability) in variables relevant to sports medicine. Sports Medicine, 26(4), 217–238. https://doi.org/10.2165/00007256-199826040-00002
• 2. Beneke, R. (2003). Methodological aspects of maximal lactate steady state-implications for performance testing. European Journal of Applied Physiology, 89(1), 95–99. https://doi.org/10.1007/s00421-002-0783-1
• 3. Bergstrom, H. C., Housh, T. J., Zuniga, J. M., Traylor, D. A., Camic, C. L., Lewis, R. W., Schmidt, R. J., ve Johnson, G. O. (2013). The relationships among critical power determined from a 3-min all-out test, respiratory compensation point, gas exchange threshold, and ventilatory threshold. Research Quarterly for Exercise and Sport, 84(2), 232–238. https://doi.org/10.1080/02701367.2013.784723
• 4. Billat, V. L., Binsse, V., Petit, B., ve Koralsztein, J. P. (1998). High level runners are able to mantain a VO2max steady state below VO2max in all out run over their critical velocity. Archives of Physiology and Biochemistry, 106(1), 38–45. https://doi.org/10.1076/apab.106.1.38.4396
• 5. Billat, V. L., Morton, R. H., Blondel, N., Berthoin, S., Bocquet, V., Koralsztein, J. P. ve Barstow, T. J. (2000). Oxygen kinetics and modelling of time to exhaustion whilst running at various velocities at maximal oxygen uptake. European Journal of Applied Physiology, 82(3), 178–187. https://doi.org/10.1007/s004210050670
• 6. Binder, R. K., Wonisch, M., Corra, U., Cohen-Solal, A., Vanhees, L., Saner, H., ve Schmid, J. P. (2008). Methodological approach to the first and second lactate threshold in incremental cardiopulmonary exercise testing. European Journal of Cardiovascular Prevention & Rehabilitation, 15(6), 726–734. https://doi.org/10.1097/HJR.0b013e328304fed4
• 7. Black, M. I., Jones, A. M., Bailey, S. J. ve Vanhatalo, A. (2015). Self-pacing increases critical power and improves performance during severe-intensity exercise. Applied physiology, nutrition, and metabolism, 40(7), 662–670. https://doi.org/10.1139/apnm-2014-0442
• 8. Bland, J. M., ve Altman, D. G. (1986). Statistical methods for assessing agreement between two methods of clinical measurement. The Lancet, 327(8476), 307–310. https://doi.org/10.1016/S0140-6736(86)90837-8
• 9. Boone, J., Koppo, K., ve Bouckaert, J. (2008). The VO2 response to submaximal ramp cycle exercise: Influence of ramp slope and training status. Respiratory Physiology and Neurobiology, 161(3), 291–297. https://doi.org/10.1016/j.resp.2008.03.008
• 10. Brickley, G., Doust, J., ve Williams, C. (2002). Physiological responses during exercise to exhaustion at critical power. European journal of applied physiology, 88(1-2), 146– 151. https://doi.org/10.1007/s00421-002-0706-1
• 11. Buchheit, M. ve Laursen, P. B. (2013). High-intensity interval training, solutions to the programming puzzle: Part I: cardiopulmonary emphasis. Sports Med, 43(5), 313–338. https://doi.org/10.1007/s40279-013-0029-x
• 12. Bull, A. J., Housh, T. J., Johnson, G. O., ve Perry, S. R. (2000). Effect of mathematical modeling on the estimation of critical power. Medicine and Science in Sports and Exercise, 32(2), 526–530. https://doi.org/10.1097/00005768-200002000-00040
• 13. Caen, K., Vermeire, K., Bourgois, J. G., ve Boone, J. (2018). Exercise Thresholds on Trial: Are They Really Equivalent? Medicine and Science in Sports and Exercise, 50(6), 1277–1284. https://doi.org/10.1249/MSS.0000000000001547
• 14. Craig, J. C., Vanhatalo, A., Burnley, M., Jones, A. M., ve Poole, D. C. (2019). Critical Power: Possibly the Most Important Fatigue Threshold in Exercise Physiology. In J. Zoladz (Ed.), Muscle and Exercise Physiology (pp. 159–181). Elsevier, London. https://doi.org/10.1016/B978-0-12-814593-7.00008-6
• 15. de Aguiar, R. A., Turnes, T., de Oliveira Cruz, R. S., ve Caputo, F. (2013). Fast-start strategy increases the time spent above 95% VO2max during severe-intensity intermittent running exercise. European Journal of Applied Physiology, 113(4), 941–949. https://doi.org/10.1007/s00421-012-2508-4
• 16. Dekerle, J., Baron, B., Dupont, L., Vanvelcenaher, J., ve Pelayo, P. (2003). Maximal lactate steady state, respiratory compensation threshold and critical power. European Journal of Applied Physiology, 89(3), 281–288. https://doi.org/10.1007/s00421-002-0786-y
• 17. Dupont, G., Blondel, N., Lensel, G., ve Berthoin, S. (2002). Critical velocity and time spent at a high level of for short intermittent runs at supramaximal velocities. Canadian journal of applied physiology, 27(2), 103–115. https://doi.org/10.1139/h02-008
• 18. Faude, O., Kindermann, W., ve Meyer, T. (2009). Lactate threshold concepts: How valid are they? Sports Medicine, 39(6), 469–490. https://doi.org/10.2165/00007256-200939060-00003
• 19. Felippe, L. C., Ferreira, G. A., Learsi, S. K., Boari, D., Bertuzzi, R., ve Lima-Silva, A. E. (2018). Caffeine increases both total work performed above critical power and peripheral fatigue during a 4-km cycling time trial. Journal of Applied Physiology, 124(6), 1491–1501. https://doi.org/10.1152/japplphysiol.00930.2017
• 20. Fukuba, Y., Miura, A., Endo, M., Kan, A., Yanagawa, K., ve Whipp, B. J. (2003). The curvature constant parameter of the power-duration curve for varied-power exercise. Medicine and Science in Sports and Exercise, 35(8), 1413–1418. https://doi.org/10.1249/01.MSS.0000079047.84364.70
• 21. Galán-Rioja, M. Á., González-Mohíno, F., Poole, D. C., ve González-Ravé, J. M. (2020). Relative proximity of critical power and metabolic/ventilatory thresholds: Systematic review and meta-analysis. Sports Medicine, 50(10), 1771–1783. https://doi.org/10.1007/s40279-020-01314-8
• 22. Hill, D. W. (1993). The critical power concept. Sports Medicine, 16(4), 237–254. https://doi.org/10.2165/00007256-199316040-00003
• 23. Hill, D. W., Williams, C. S., ve Burg, S. E. (1997). Responses to exercise at 92% and 100% of the velocity associated with VO2max. International journal of sports medicine, 18(05), 325-329. https://doi.org/10.1055/s-2007-972641
• 24. Hopkins, W. G., Edmond, I. M., Hamilton, B. H., Mac Farlane, D. J., ve Ross, B. H. (1989). Relation between power and endurance for treadmill running of short duration. Ergonomics, 32(12), 1565–1571. https://doi.org/10.1080/00140138908966925
• 25. Howley, E. T., Bassett, D. R., ve Welch, H. G. (1995). Criteria for maximal oxygen uptake: review and commentary. Medicine and Science in Sports and Exercise, 27(9), 1292–1301.
• 26. Jeukendrup, A. E., Craig, N. P., ve Hawley, J. A. (2000). The bioenergetics of World Class Cycling. Journal of science and medicine in sport, 3(4), 414–433. https://doi.org/10.1016/s1440-2440(00)80008-0
• 27. Jones, A. M., Burnley, M., Black, M. I., Poole, D. C., ve Vanhatalo, A. (2019). The maximal metabolic steady state: redefining the ‘gold standard.’ Physiological Reports, 7(10), e14098. https://doi.org/10.14814/phy2.14098
• 28. Jones, A. M. ve Vanhatalo, A. (2019). The ‘critical power’ concept: Applications to sports performance with a focus on intermittent high-intensity exercise. Sports Medicine, 47(1), 65–78. https://doi.org/10.1007/s40279-017-0688-0
• 29. Jones, A. M., Vanhatalo, A., Burnley, M., Morton, R. H., ve Poole, D. C. (2010). Critical power: implications for determination of VO2max and exercise tolerance. Medicine and Science in Sports and Exercise, 42(10), 1876–1890. https://doi.org/10.1249/MSS.0b013e3181d9cf7f
• 30. Karsten, B., Jobson, S. A., Hopker, J., Stevens, L., ve Beedie, C. (2015). Validity and reliability of critical power field testing. European Journal of Applied Physiology, 115(1), 197–204. https://doi.org/10.1007/s00421-014-3001-z
• 31. Keir, D. A., Fontana, F. Y., Robertson, T. C., Murias, J. M., Paterson, D. H., Kowalchuk, J. M., ve Pogliaghi, S. (2015). Exercise Intensity Thresholds: Identifying the Boundaries of Sustainable Performance. Medicine and Science in Sports and Exercise, 47(9), 1932–1940. https://doi.org/10.1249/MSS.0000000000000613
• 32. Leo, J. A., Sabapathy, S., Simmonds, M. J., ve Cross, T. J. (2017). The respiratory compensation point is not a valid surrogate for critical power. Medicine and Science in Sports and Exercise, 49(7), 1452–1460. https://doi.org/10.1249/MSS.0000000000001226
• 33. Mattioni Maturana, F., Fontana, F. Y., Pogliaghi, S., Passfield, L., ve Murias, J. M. (2018). Critical power: How different protocols and models affect its determination. Journal of Science and Medicine in Sport, 21(7), 742–747. https://doi.org/10.1016/j.jsams.2017.11.015
• 34. Mattioni Maturana, F., Keir, D. A., McLay, K. M., ve Murias, J. M. (2017). Critical power testing or self-selected cycling: Which one is the best predictor of maximal metabolic steady-state? Journal of Science and Medicine in Sport, 20(8), 795–799. https://doi.org/10.1016/j.jsams.2016.11.023
• 35. Monod, H., ve Scherrer, J. (1965). The work capacity of a synergic muscular group. Ergonomics, 8(3), 329–338. https://doi.org/10.1080/00140136508930810
• 36. Morgan, P., Vanhatalo, A., Bowtell, J. L., Jones, A, M., ve Bailey, S. J. (2019). Acetaminophen ingestion improves muscle activation and performance during a 3-min all-out cycling test. Applied Physiology, Nutrition and Metabolism, 44(4), 434–442
• 37. Moritani, T., Ata, A. N., Devries, H. A., ve Muro, M. (1981). Critical power as a measure of physical work capacity and anaerobic threshold. Ergonomics, 24(5), 339–350. https://doi.org/10.1080/00140138108924856
• 38. Morton, R. H. (2006). The critical power and related whole-body bioenergetic models. European Journal of Applied Physiology, 96(4), 339–354. https://doi.org/10.1007/s00421-005-0088-2
• 39. Morton, R. H. (1996). A 3-parameter critical power model. Ergonomics, 39(4), 611–619. https://doi.org/10.1080/00140139608964484
• 40. Ozkaya, O., Balci, G. A., As, H., Cabuk, R., ve Norouzi, M. (2020). Grey Zone: A gap between heavy and severe exercise domain. The Journal of Strength and Conditioning Research, Basım aşamasında. https://doi.org/10.1519/JSC.0000000000003427
• 41. Pringle, J., ve Jones, A. (2002). Maximal lactate steady state, critical power and EMG during cycling. European Journal of Applied Physiology, 88(3), 214–226. https://doi.org/10.1007/s00421-002-0703-4
• 42. Sawyer, B. J., Morton, R. H., Womack, C. J., ve Gaesser, G. A. (2012). VO2max may not be reached during exercise to exhaustion above critical power. Medicine and Science in Sports and Exercise, 44(8), 1533–1538. https://doi.org/10.1249/MSS.0b013e31824d2587
• 43. Vanhatalo, A., Doust, J. H., ve Burnley, M. (2007). Determination of critical power using a 3- min all-out cycling test. Medicine and science in sports and exercise, 39(3), 548–555. https://doi.org/10.1249/mss.0b013e31802dd3e6
• 44. Wakefield, B. R., ve Glaister, M. (2009). Influence of Work-Interval Intensity and Duration on Time Spent at a High Percentage of V ̇O2max During Intermittent Supramaximal Exercise. Journal of strength and conditioning research, 23(9), 2548–2554. https://doi.org/10.1519/JSC.0b013e3181bc19b1
• 45. Wassertheil, S., ve Cohen, J. (1970). Statistical Power Analysis for the Behavioral Sciences. Biometrics, 26(3), 588. https://doi.org/10.2307/2529115
• 46. Whipp, B. J., Huntsman, D. J., Stoner, N., Lamarra, N., ve Wasserman, K. (1982). A constant which determines the duration of tolerance of high-intensity work. Federation Proceedings, 41(5), 1591.