Endurance training guided individually by daily heart rate variability measurements
Purpose of this study was to test utility of heart rate variability (HRV) in daily endurance exercise prescriptions. Twenty-six healthy, moderately fit males were randomized into predefined training group (TRA, n = 8), HRV-guided training group (HRV, n = 9), and control group (n = 9). Four-week training period consisted of running sessions lasting 40 min each at either low- or high-intensity level. TRA group trained on 6 days a week, with two sessions at low and four at high intensity. Individual training program for HRV group was based on individual changes in high-frequency R–R interval oscillations measured every morning. Increase or no change in HRV resulted in high-intensity training on that day. If there was significant decrease in HRV (below reference value [10-day mean-SD] or decreasing trend for 2 days), low-intensity training or rest was prescribed. Peak oxygen consumption (VO2peak) and maximal running velocity (Loadmax) were measured in maximal treadmill test before and after the training. In TRA group, Loadmax increased from 15.1 ± 1.3 to 15.7 ± 1.2 km h−1 (P = 0.004), whereas VO2peak did not change significantly (54 ± 4 pre and 55 ± 3 ml kg−1 min−1 post, P = 0.224). In HRV group, significant increases were observed in both Loadmax (from 15.5 ± 1.0 to 16.4 ± 1.0 km h−1, P < 0.001) and VO2peak (from 56 ± 4 to 60 ± 5 ml kg−1 min−1, P = 0.002). The change in Loadmax was significantly greater in HRV group compared to TRA group (0.5 ± 0.4 vs. 0.9 ± 0.2 km h−1, P = 0.048, adjusted for baseline values). No significant differences were observed in the changes of VO2peak between the groups. We concluded that cardiorespiratory fitness can be improved effectively by using HRV for daily training prescription.
KeywordsExercise training Vagal activity Autonomic nervous system Exercise prescription
Ministry of Education (Helsinki, Finland) is gratefully acknowledged for financial support. Special thanks to Heidi Jurvelin, MSc., for assistance during data processing.
- Adamson PB, Smith AL, Abraham WT, Kleckner KJ, Stadler RW, Shih A, Rhodes MM (2004) Continuous autonomic assessment in patients with symptomatic heart failure: prognostic value of heart rate variability measured by an implanted cardiac resynchronization device. Circulation 110(16):2389–2394PubMedCrossRefGoogle Scholar
- Banister EW (1991) Modeling elite athletic performance. In: Green HJ, McDougal JD, Wenger H (eds) Physiological testing of elite athletes. Human Kinetics, Champaign, IL, pp 403–424Google Scholar
- Bauer A, Kantelhardt JW, Barthel P, Schneider R, Mäkikallio T, Ulm K, Hnatkova K, Schomig A, Huikuri H, Bunde A, Malik M, Schmidt G (2006) Deceleration capacity of heart rate as a predictor of mortality after myocardial infarction: cohort study. Lancet 367(9523):1674–1681PubMedCrossRefGoogle Scholar
- Dietrich DF, Schindler C, Schwartz J, Barthelemy JC, Tschopp JM, Roche F, von Eckardstein A, Brandli O, Leuenberger P, Gold DR, Gaspoz JM, Ackermann-Liebrich U (2006) Heart rate variability in an ageing population and its association with lifestyle and cardiovascular risk factors: results of the SAPALDIA study. Europace 8(7):521–529CrossRefGoogle Scholar
- Kiviniemi AM, Hautala AJ, Seppänen T, Mäkikallio TH, Huikuri HV, Tulppo MP (2004) Saturation of high-frequency oscillations of R-R intervals in healthy subjects and patients after acute myocardial infarction during ambulatory conditions. Am J Physiol Heart Circ Physiol 287(5):H1921–H1927PubMedCrossRefGoogle Scholar
- Saltin B (1990) Maximal oxygen uptake: limitations and malleability. In: Nazar K, Terjung RL (eds) International perspectives in exercise physiology. Human Kinetics Publishers, Champaign, IL, pp 26–40Google Scholar
- Wasserman K, Hansen JE, Sue DY, Whipp BJ (1987) Principles of exercise testing and interpretation. Lea & Febinger, Philadelphia, PAGoogle Scholar