@article{SperlichMatzkaHolmberg2023, author = {Sperlich, Billy and Matzka, Manuel and Holmberg, Hans-Christer}, title = {The proportional distribution of training by elite endurance athletes at different intensities during different phases of the season}, series = {Frontiers in Sports and Active Living}, volume = {5}, journal = {Frontiers in Sports and Active Living}, doi = {10.3389/fspor.2023.1258585}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-357988}, year = {2023}, abstract = {The present review examines retrospective analyses of training intensity distribution (TID), i.e., the proportion of training at moderate (Zone 1, Z1), heavy (Z2) and severe (Z3) intensity by elite-to-world-class endurance athletes during different phases of the season. In addition, we discuss potential implications of our findings for research in this field, as well as for training by these athletes. Altogether, we included 175 TIDs, of which 120 quantified exercise intensity on the basis of heart rate and measured time-in-zone or employed variations of the session goal approach, with demarcation of zones of exercise intensity based on physiological parameters. Notably, 49\% of the TIDs were single-case studies, predominantly concerning cross-country skiing and/or the biathlon. Eighty-nine TIDs were pyramidal (Z1 > Z2 > Z3), 65 polarized (Z1 > Z3 > Z2) and 8 "threshold" (Z2 > Z1 = Z3). However, these relative numbers varied between sports and the particular phases of the season. In 91\% (n = 160) of the TIDs >60\% of the endurance exercise was of low intensity. Regardless of the approach to quantification or phase of the season, cyclists and swimmers were found to perform a lower proportion of exercise in Z1 (<72\%) and higher proportion in Z2 (>16\%) than athletes involved in the triathlon, speed skating, rowing, running, cross-country skiing or biathlon (>80\% in Z1 and <12\% in Z2 in all these cases). For most of the athletes their proportion of heavy-to-severe exercise was higher during the period of competition than during the preparatory phase, although with considerable variability between sports. In conclusion, the existing literature in this area does not allow general conclusions to be drawn. The methods utilized for quantification vary widely and, moreover, contextual information concerning the mode of exercise, environmental conditions, and biomechanical aspects of the exercise is often lacking. Therefore, we recommend a more comprehensive approach in connection with future investigations on the TIDs of athletes involved in different endurance sports.}, language = {en} } @article{KaufmannGronwaldHeroldetal.2023, author = {Kaufmann, Sebastian and Gronwald, Thomas and Herold, Fabian and Hoos, Olaf}, title = {Heart Rate Variability-Derived Thresholds for Exercise Intensity Prescription in Endurance Sports: A Systematic Review of Interrelations and Agreement with Different Ventilatory and Blood Lactate Thresholds}, series = {Sports Medicine - Open}, volume = {9}, journal = {Sports Medicine - Open}, doi = {10.1186/s40798-023-00607-2}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-357957}, year = {2023}, abstract = {Background Exercise intensities are prescribed using specific intensity zones (moderate, heavy, and severe) determined by a 'lower' and a 'higher' threshold. Typically, ventilatory (VT) or blood lactate thresholds (LT), and critical power/speed concepts (CP/CS) are used. Various heart rate variability-derived thresholds (HRVTs) using different HRV indices may constitute applicable alternatives, but a systematic review of the proximity of HRVTs to established threshold concepts is lacking. Objective This systematic review aims to provide an overview of studies that determined HRVTs during endurance exercise in healthy adults in comparison with a reference VT and/or LT concept. Methods A systematic literature search for studies determining HRVTs in healthy individuals during endurance exercise and comparing them with VTs or LTs was conducted in Scopus, PubMed and Web of Science (until January 2022). Studies claiming to describe similar physiological boundaries to delineate moderate from heavy (HRVTlow vs. VTlow and/or LTlow), and heavy from severe intensity zone (HRVThigh vs. VThigh and/or LThigh) were grouped and their results synthesized. Results Twenty-seven included studies (461 participants) showed a mean difference in relative HR between HRVTlow and VTlow of - 0.6\%bpm in weighted means and 0.02\%bpm between HRVTlow and LTlow. Bias between HR at HRVTlow and VTlow was 1 bpm (limits of agreement (LoA): - 10.9 to 12.8 bpm) and 2.7 bpm (LoA: - 20.4 to 25.8 bpm) between HRVTlow and LTlow. Mean difference in HR between HRVThigh and VThigh was 0.3\%bpm in weighted means and 2.9\%bpm between HRVThigh and LThigh while bias between HR at HRVThigh and VThigh was - 4 bpm (LoA: - 17.9 to 9.9 bpm) and 2.5 bpm (LoA: - 12.1 to 17.1 bpm) between HRVThigh and LThigh. Conclusion HRVTlow seems to be a promising approach for the determination of a 'lower' threshold comparable to VTlow and potentially for HRVThigh compared to VThigh, although the latter needs further empirical evaluation. LoA for both intensity zone boundaries indicates bias of HRVTs on an individual level. Taken together, HRVTs can be a promising alternative for prescribing exercise intensity in healthy, male athletes undertaking endurance activities but due to the heterogeneity of study design, threshold concepts, standardization, and lack of female participants, further research is necessary to draw more robust and nuanced conclusions.}, language = {en} } @article{RogersGilesDraperetal.2021, author = {Rogers, Bruce and Giles, David and Draper, Nick and Hoos, Olaf and Gronwald, Thomas}, title = {A New Detection Method Defining the Aerobic Threshold for Endurance Exercise and Training Prescription Based on Fractal Correlation Properties of Heart Rate Variability}, series = {Frontiers in Physiology}, volume = {11}, journal = {Frontiers in Physiology}, issn = {1664-042X}, doi = {10.3389/fphys.2020.596567}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-222601}, year = {2021}, abstract = {The short-term scaling exponent alpha1 of detrended fluctuation analysis (DFA a1), a nonlinear index of heart rate variability (HRV) based on fractal correlation properties, has been shown to steadily change with increasing exercise intensity. To date, no study has specifically examined using the behavior of this index as a method for defining a low intensity exercise zone. The aim of this report is to compare both oxygen intake (VO\(_{2}\)) and heart rate (HR) reached at the first ventilatory threshold (VT1), a well-established delimiter of low intensity exercise, to those derived from a predefined DFA a1 transitional value. Gas exchange and HRV data were obtained from 15 participants during an incremental treadmill run. Comparison of both VO\(_{2}\) and HR reached at VT1 defined by gas exchange (VT1 GAS) was made to those parameters derived from analysis of DFA a1 reaching a value of 0.75 (HRVT). Based on Bland Altman analysis, linear regression, intraclass correlation (ICC) and t testing, there was strong agreement between VT1 GAS and HRVT as measured by both HR and VO\(_{2}\). Mean VT1 GAS was reached at 39.8 ml/kg/min with a HR of 152 bpm compared to mean HRVT which was reached at 40.1 ml/kg/min with a HR of 154 bpm. Strong linear relationships were seen between test modalities, with Pearson's r values of 0.99 (p < 0.001) and.97 (p < 0.001) for VO\(_{2}\) and HR comparisons, respectively. Intraclass correlation between VT1 GAS and HRVT was 0.99 for VO\(_{2}\) and 0.96 for HR. In addition, comparison of VT1 GAS and HRVT showed no differences by t testing, also supporting the method validity. In conclusion, it appears that reaching a DFA a1 value of 0.75 on an incremental treadmill test is closely associated with crossing the first ventilatory threshold. As training intensity below the first ventilatory threshold is felt to have great importance for endurance sport, utilization of DFA a1 activity may provide guidance for a valid low training zone.}, language = {en} } @article{GronwaldRogersHoos2020, author = {Gronwald, Thomas and Rogers, Bruce and Hoos, Olaf}, title = {Fractal Correlation Properties of Heart Rate Variability: A New Biomarker for Intensity Distribution in Endurance Exercise and Training Prescription?}, series = {Frontiers in Physiology}, volume = {11}, journal = {Frontiers in Physiology}, issn = {1664-042X}, doi = {10.3389/fphys.2020.550572}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-212429}, year = {2020}, abstract = {Exercise and training prescription in endurance-type sports has a strong theoretical background with various practical applications based on threshold concepts. Given the challenges and pitfalls of determining individual training zones on the basis of subsystem indicators (e.g., blood lactate concentration, respiratory parameters), the question arises whether there are alternatives for intensity distribution demarcation. Considering that training in a low intensity zone substantially contributes to the performance outcome of endurance athletes and exceeding intensity targets based on a misleading aerobic threshold can lead to negative performance and recovery effects, it would be desirable to find a parameter that could be derived via non-invasive, low cost and commonly available wearable devices. In this regard, analytics conducted from non-linear dynamics of heart rate variability (HRV) have been adapted to gain further insights into the complex cardiovascular regulation during endurance-type exercise. Considering the reciprocal antagonistic behavior and the interaction of the sympathetic and parasympathetic branch of the autonomic nervous system from low to high exercise intensities, it may be promising to use an approach that utilizes information about the regulation quality of the organismic system to determine training-intensity distribution. Detrended fluctuation analysis of HRV and its short-term scaling exponent alpha1 (DFA-alpha1) seems suitable for applied sport-specific settings including exercise from low to high intensities. DFA-alpha1 may be taken as an indicator for exercise prescription and intensity distribution monitoring in endurance-type sports. The present perspective illustrates the potential of DFA-alpha1 for diagnostic and monitoring purposes as a "global" system parameter and proxy for organismic demands.}, language = {en} }