Real-Time Estimation of Aerobic Threshold and Exercise Intensity Distribution Using Fractal Correlation Properties of Heart Rate Variability: A Single-Case Field Application in a Former Olympic Triathlete

A non-linear heart rate variability (HRV) index based on fractal correlation properties called alpha1 of Detrended Fluctuation Analysis (DFA-alpha1), has been shown to change with endurance exercise intensity. Its unique advantage is that it provides information about current absolute exercise intensity without prior lactate or gas exchange testing. Therefore, real-time assessment of this metric during field conditions using a wearable monitoring device could directly provide a valuable exercise intensity distribution without prior laboratory testing for different applied field settings in endurance sports. Until of late no mobile based product could display DFA-alpha1 in real-time using off the shelf consumer products. Recently an app designed for iOS and Android devices, HRV Logger, was updated to assess DFA-alpha1 in real-time. This brief research report illustrates the potential merits of real-time monitoring of this metric for the purposes of aerobic threshold (AT) estimation and exercise intensity demarcation between low (zone 1) and moderate (zone 2) in a former Olympic triathlete. In a single-case feasibility study, three practically relevant scenarios were successfully evaluated in cycling, (1) estimation of a HRV threshold (HRVT) as an adequate proxy for AT using Kubios HRV software via a typical cycling stage test, (2) estimation of the HRVT during real-time monitoring using a cycling 6 min stage test, (3) a simulated 1 h training ride with enforcement of low intensity boundaries and real-time HRVT confirmation. This single-case field evaluation illustrates the potential of an easy-to-use and low cost real-time estimation of the aerobic threshold and exercise intensity distribution using fractal correlation properties of HRV. Furthermore, this approach may enhance the translation of science into endurance sports practice for future real-world settings.

Duration of functional stability to non-specific aerobic load in wrestlers

Objective: study the duration of establishment of functional stability to non-specific stress in wrestlers.Materials and Methods. Nineteen athletes in martial arts, mid-age 23 ± 3 years of age, participated in the study. The qualification level of the subjects ranged from first sport grade to Master of Sport. A series of sports training was organized within 4 weeks. Each train consisted of a smooth-running load of 40 minutes at a speed corresponding to the anaerobic exchange threshold (AET). The indicators of the duration of reaching the AET level by heart rate (HR), the power of the low frequency and high frequency component of the spectrum were analyzed.Results. The effect of urgent adaptation, in the form of an extension of the duration the heart rate on the anaerobic threshold level from 29 to 32 mines and the increase in the regulation of vegetative nervous system by increasing the total power of the spectrum observed on the third day of the training cycle. From the third to ninth days of the study, fatigue occurs, as can be seen from the lowering of the anaerobic threshold time to 21 minutes, as well as the lowering of the high-frequency part of the vegetative nervous system regulatory spectrum. The emergency adaptation ends by 9 days of observation, after four high-intensity exercises, which manifests itself in stabilizing the regulation of the heart rate, vegetative nervous system goes from a reflex level to a lower one — a humeral metabolic level. The time to reach the HR in the aerobic threshold will stabilize at 21–23 minutes.Conclusions. Functional stability to the non-specific aerobic load in the wrestlers emerged by the twentyseventh day of the study after ten highly intensive aerobic exercises, which confirmed by the results of the time dynamics of the tine of HR in aerobic threshold and analysis of spectrum results of HRV.

Influence of Artefact Correction and Recording Device Type on the Practical Application of a Non-Linear Heart Rate Variability Biomarker for Aerobic Threshold Determination

Recent study points to the value of a non-linear heart rate variability (HRV) biomarker using detrended fluctuation analysis (DFA a1) for aerobic threshold determination (HRVT). Significance of recording artefact, correction methods and device bias on DFA a1 during exercise and HRVT is unclear. Gas exchange and HRV data were obtained from 17 participants during an incremental treadmill run using both ECG and Polar H7 as recording devices. First, artefacts were randomly placed in the ECG time series to equal 1, 3 and 6% missed beats with correction by Kubios software’s automatic and medium threshold method. Based on linear regression, Bland Altman analysis and Wilcoxon paired testing, there was bias present with increasing artefact quantity. Regardless of artefact correction method, 1 to 3% missed beat artefact introduced small but discernible bias in raw DFA a1 measurements. At 6% artefact using medium correction, proportional bias was found (maximum 19%). Despite this bias, the mean HRVT determination was within 1 bpm across all artefact levels and correction modalities. Second, the HRVT ascertained from synchronous ECG vs. Polar H7 recordings did show an average bias of minus 4 bpm. Polar H7 results suggest that device related bias is possible but in the reverse direction as artefact related bias.

P6324Contribution of muscle efficiency in heart failure patients post phase 2 cardiac rehabilitation

Background Muscle efficiency (ME), can help explain the observed improvement in patients without increase in oxygen uptake (VO2) after cardiac rehabilitation programme (CRP). The better use of energy, independent to the oxygen delivery to muscle, may improve the functional capacity in Heart failure (HF) patients. Our aim was to evaluate the contribution of muscle efficiency improvement after CR on functional capacity. Methods We analyse consecutive patients data that had their phase 2 CR concluded, with HF as admission indication with no medical therapy changes and CRT implantation during this period. The aetiology of HF and biometric data, functional class, BNP, Minnesotta and EuroQol questionnaires and cardiorespiratory test pre and post 4 months of CRP were collected. The average of the exercise load in the first two and last two training sessions were recorded. ME was calculated at peak exercise during cardiopulmonary exercise test in pre and post CRP (see formula above). Results From 55 HF patients sequentially admitted in our CRP, during the last 24 months, 45 were included, since 2 were transplanted, 1 died and the 7 didn't concluded the program or not had all the data mentioned in the methods. The mean age was 60,5±10,3 years and 78% were male. Ischemic aetiology with depressed ejection fraction (64%) was the main admission indication, followed by cardiomyopathies (18%). Betablockers, ACEi or ARBs or ARNi and MRA were taken in 91%, 93%, 46%, respectively. ICD and CRT were previously implanted in 44% of the patients. Comparing pre and post CRP VO2 at peak exercise and aerobic threshold levels no statically differences were found. In this cohort 27 (60%) patients increased ME. At the end of the CRP, this group had a higher improvement in METs (p=0,021), higher gain in lean mass (p=0,041), in EuroQoL (p=0,002) and in physical dimension of Minnesotta questionnaire (p=0,032), when compared with patients that didn't improve the ME in at least 5%. In 22 patients that increased ME, the VO2 at aerobic threshold level didn't improve by at least 5% and in this group the same benefits were confirmed. Formula of Muscle Efficiency Conclusions The improvement in exercise load reached in the post CRP cardiopulmonary test, independently of possible cardiac output changes (VO2 peak), seems to be explained in part by the increase in ME improvement.

Applicability of Dmax Method on Heart Rate Variability to Estimate the Lactate Thresholds in Male Runners

Introduction. The purpose of this study was to evaluate the application of the Dmax method on heart rate variability (HRV) to estimate the lactate thresholds (LT), during a maximal incremental running test (MIRT). Methods. Nineteen male runners performed two MIRTs, with the initial speed at 8 km·h−1 and increments of 1 km·h−1 every 3 minutes, until exhaustion. Measures of HRV and blood lactate concentrations were obtained, and lactate (LT1 and LT2) and HRV (HRVTDMAX1 and HRVTDMAX2) thresholds were identified. ANOVA with Scheffe’s post hoc test, effect sizes (d), the bias ± 95% limits of agreement (LoA), standard error of the estimate (SEE), Pearson’s (r), and intraclass correlation coefficient (ICC) were calculated to assess validity. Results. No significant differences were observed between HRVTDMAX1 and LT1 when expressed for speed (12.1 ± 1.4 km·h−1 and 11.2 ± 2.1 km·h−1; p=0.55; d = 0.45; r = 0.46; bias ± LoA = 0.8 ± 3.7 km·h−1; SEE = 1.2 km·h−1 (95% CI, 0.9–1.9)). Significant differences were observed between HRVTDMAX2 and LT2 when expressed for speed (12.0 ± 1.2 km·h−1 and 14.1 ± 2.5 km·h−1; p=0.00; d = 1.21; r = 0.48; bias ± LoA = −1.0 ± 1.8 km·h−1; SEE = 1.1 km·h−1 (95% CI, 0.8–1.6)), respectively. Reproducibility values were found for the LT1 (ICC = 0.90; bias ± LoA = −0.7 ± 2.0 km·h−1), LT2 (ICC = 0.97; bias ± LoA = −0.1 ± 1.1 km·h−1), HRVTDMAX1 (ICC = 0.48; bias ± LoA = −0.2 ± 3.4 km·h−1), and HRVTDMAX2 (ICC = 0.30; bias ± LoA = 0.3 ± 3.5 km·h−1). Conclusions. The Dmax method applied over a HRV dataset allowed the identification of LT1 that is close to aerobic threshold, during a MIRT.