%HRmax target heart rate is dependent on heart rate performance curve deflection

Using Free-Living Heart Rate Data as an Objective Method to Assess Physical Activity: A Scoping Review and Recommendations by the INTERLIVE-Network Targeting Consumer Wearables

Wearable technologies open up new avenues for the assessment of individual physical activity behaviour. Particularly, free-living heart rate (HR) data assessed by optical sensors are becoming widely available. However, while an abundancy of scientific information and guidance exists for the processing of raw acceleration data, no universal recommendations for the utilization of continuous HR recordings during free-living conditions are available. Towards Intelligent Health and Well-Being: Network of Physical Activity Assessment (INTERLIVE®) is a joint European initiative of six universities and one industrial partner. The consortium was founded in 2019 and strives towards developing best-practice recommendations in the context of consumer wearables and smartphones. The aim of this scoping review (following PRISMA-ScR procedures) and recommendations was to provide best-practice protocols for deriving individual physical activity profiles from continuous HR recordings by wearables. The recommendations were developed through an initial scoping review, grey literature searches of promotional material and user manuals of leading wearable manufacturers as well as evidence-informed discussions among the members of the INTERLIVE®-network. The scoping review was performed on the generic domains required for physical activity assessment, namely: (1) 'assessment of maximal heart rate', (2) 'determination of basal and/or resting heart rate' and (3) 'heart rate-derived intensity zones', for which we finally included a total of 72, 2 and 11 eligible papers, respectively. Gathering recent knowledge, we provide a decision tree and detailed recommendations for the analysis of free-living HR data to derive individual physical activity profiles. Moreover, we also provide examples of HR-metric calculations that help to illustrate data processing and reporting.

Exercise, cancer, and the cardiovascular system: clinical effects and mechanistic insights

Cardiovascular diseases and cancer are the leading causes of death in the Western world and share common risk factors. Reduced cardiorespiratory fitness (CRF) is a major determinant of cardiovascular morbidity and cancer survival. In this review we discuss cancer- induced disturbances of parenchymal, cellular, and mitochondrial function, which limit CRF and may be antagonized and attenuated through exercise training. We show the impact of CRF on cancer survival and its attenuating effects on cardiotoxicity of cancer-related treatment. Tailored exercise programs are not yet available for each tumor entity as several trials were performed in heterogeneous populations without adequate cardiopulmonary exercise testing (CPET) prior to exercise prescription and with a wide variation of exercise modalities. There is emerging evidence that exercise may be a crucial pillar in cancer treatment and a tool to mitigate cardiotoxic treatment effects. We discuss modalities of aerobic exercise and resistance training and their potential to improve CRF in cancer patients and provide an example of a periodization model for exercise training in cancer.

From data to decision: Machine learning determination of aerobic and anaerobic thresholds in athletes

Lactate analysis plays an important role in sports science and training decisions for optimising performance, endurance, and overall success in sports. Two parameters are widely used for these goals: aerobic (AeT) and anaerobic (AnT) thresholds. However, determining AeT proves more challenging than AnT threshold due to both physiological intricacies and practical considerations. Thus, the aim of this study was to determine AeT and AnT thresholds using machine learning modelling (ML) and to compare ML-obtained results with the parameters' values determined using conventional methods. ML seems to be highly useful due to its ability to handle complex, personalised data, identify nonlinear relationships, and provide accurate predictions. The 183 results of CardioPulmonary Exercise Test (CPET) accompanied by lactate and heart ratio analyses from amateur athletes were enrolled to the study and ML models using the following algorithms: Random Forest, XGBoost (Extreme Gradient Boosting), and LightGBM (Light Gradient Boosting Machine) and metrics: R2, mean absolute error (MAE), mean squared error (MSE) and root mean square error (RMSE). The regressors used belong to the group of ensemble learning algorithms that combine the predictions of multiple base models to improve overall performance and counteract overfitting to training data. Based on evaluation metrics, the following models give the best predictions: for AeT: Random Forest has an R2 value of 0.645, MAE of 4.630, MSE of 44.450, RMSE of 6.667; and for AnT: LightGBM has an R2 of 0.803, the highest among the models, MAE of 3.439, the lowest among the models, MSE of 20.953, and RMSE of 4.577. Outlined research experiments, a comprehensive review of existing literature in the field, and obtained results suggest that ML models can be trained to make personalised predictions based on an individual athlete's unique physiological response to exercise. Athletes exhibit significant variation in their AeT and AT, and ML can capture these individual differences, allowing for tailored training recommendations and performance optimization.

Relevance of Cardiovascular Exercise in Cancer and Cancer Therapy-Related Cardiac Dysfunction

PURPOSE OF THE REVIEW

Cancer therapy-related cardiac dysfunction (CTRCD) has been identified as a threat to overall and cancer-related survival. Although aerobic exercise training (AET) has been shown to improve cardiorespiratory fitness (CRF), the relationship between specific exercise regimens and cancer survival, heart failure development, and reduction of CTRCD is unclear. In this review, we discuss the impact of AET on molecular pathways and the current literature of sports in the field of cardio-oncology.

RECENT FINDINGS

Cardio-oncological exercise trials have focused on variations of AET intensity by using moderate continuous and high intensity interval training, which are applicable, safe, and effective approaches to improve CRF. AET increases CRF, reduces cardiovascular morbidity and heart failure hospitalization and should thus be implemented as an adjunct to standard cancer therapy, although its long-term effect on CTRCD remains unknown. Despite modulating diverse molecular pathways, it remains unknown which exercise regimen, including variations of AET duration and frequency, is most suited to facilitate peripheral and central adaptations to exercise and improve survival in cancer patients.

Pattern of the heart rate performance curve in maximal graded treadmill running from 1100 healthy 18-65 Years old men and women: the 4HAIE study

Introduction: The heart rate performance curve (HRPC) in maximal incremental cycle ergometer exercise demonstrated three different patterns such as downward, linear or inverse versions. The downward pattern was found to be the most common and therefore termed regular. These patterns were shown to differently influence exercise prescription, but no data are available for running. This study investigated the deflection of the HRPC in maximal graded treadmill tests (GXT) of the 4HAIE study. Methods: Additional to maximal values, the first and second ventilatory thresholds as well as the degree and the direction of the HRPC deflection (k_HR) were determined from 1,100 individuals (489 women) GXTs. HRPC deflection was categorized as downward (k_HR < -0.1), linear (-0.1 ≤ k_HR ≤ 0.1) or inverse (k_HR > 0.1) curves. Four (even split) age- and two (median split) performance-groups were used to investigate the effects of age and performance on the distribution of regular (= downward deflection) and non-regular (= linear or inverse course) HR curves for male and female subjects. Results: Men (age: 36.8 ± 11.9 years, BMI: 25.0 ± 3.3 kg m^-2, VO_2max: 46.4 ± 9.4 mL min^-1. kg^-1) and women (age: 36.2 ± 11.9 years, BMI: 23.3 ± 3.7 kg m^-2, VO_2max: 37.4 ± 7.8 mL min^-1. kg^-1) presented 556/449 (91/92%) downward deflecting, 10/8 (2/2%) linear and 45/32 (7/6%) inverse HRPC´s. Chi-squared analysis revealed a significantly higher number of non-regular HRPC´s in the low-performance group and with increasing age. Binary logistic regression revealed that the odds ratio (OR) to show a non-regular HRPC is significantly affected by maximum performance (OR = 0.840, 95% CI = 0.754-0.936, p = 0.002) and age (OR = 1.042, 95% CI = 1.020-1.064, p < 0.001) but not sex. Discussion: As in cycle ergometer exercise, three different patterns for the HRPC were identified from the maximal graded treadmill exercise with the highest frequency of regular downward deflecting curves. Older subjects and subjects with a lower performance level had a higher probability to show a non-regular linear or inverted curve which needs to be considered for exercise prescription.

Unraveling the mystery of isocaloric endurance training - Influence of exercise modality, biological sex, and physical fitness

BACKGROUND

A sedentary lifestyle with low energy expenditure (EE) is associated with chronic diseases and mortality. Barriers such as "lack of time" or "lack of motivation" are common reasons why physical exercise is neglected in the general population. To optimize EE in the time available, time-efficient but also enjoyable types of exercise are required. We therefore used an isocaloric approach to systematically investigate the effects of six different endurance exercise modalities on metabolic, mechanical, cardiorespiratory, and subjective variables in relation to biological sex and physical fitness.

METHODS

Out of 104, 92 healthy participants (21 recreationally trained and 18 trained females, 25 recreationally trained and 28 trained males) were subjected to physiological exercise testing to determine the exercise intensities for six exercise modalities, i.e., three different high-intensity interval training (HIIT) protocols (5 × 4 min, 15 × 1 min, 30 × 30 sec intervals), threshold (THR), speed endurance production (SEP), and low-intensity training (LIT). One of three HIIT sessions served as the reference for the subsequent isocaloric exercise modalities which were completed in randomized order. Metabolic and mechanical variables, i.e., EE during exercise, time to isocaloric EE (T_iso), relative and absolute fat contribution, post-exercise oxygen consumption (EPOC), mechanical energy, as well as cardiorespiratory and subjective variables, i.e., heart rate, oxygen uptake response, rating of perceived exertion, and enjoyment were assessed. Data were analyzed using a 6 × 2 × 2 repeated-measures ANOVA.

RESULTS

All three versions of HIIT and THR achieved the same EE during exercise for the same training duration. We found that LIT had a 1.6-fold (p < 0.001) and SEP a 1.3-fold (p < 0.001) longer T_iso compared to HIIT with no effects of biological sex (p = 0.42, _pη² = 0.01) or physical fitness (p = 0.09, _pη² = 0.04). There was a main effect of exercise modality on EPOC (p < 0.001, _pη² = 0.76) with highest values for HIIT 30 × 30 (p = 0.032) and lowest for LIT (p < 0.001). The highest relative and absolute amounts of fatty acids were measured during LIT (p < 0.001), and the lowest values were obtained during HIIT modalities. HIIT 30 × 30 was the most enjoyable version of HIIT (p = 0.007), while THR was the least enjoyable exercise modality (p = 0.008).

CONCLUSION

HIIT modalities are time-saving and enjoyable, regardless of sex and physical fitness. The results illustrate the relationship between exercise modality and metabolic, physiological, and subjective responses, and are thus of great interest to healthy individuals seeking time-saving and enjoyable exercise options.

Aerobic Training for Healthy Men and Women: Determining Intensities by Different Equations

The aim of this study is to develop equations for aerobic exercise prescription for the intensities of 50, 60, 70 and 80% in healthy subjects of both sexes.

METHOD

This is a cross-sectional study with convenience sampling drawn from a database of 228 healthy subjects who were randomized into the regression group (GR: 197 subjects (male = 143 and female = 54)) and cross-validation group (CVG: 31 individuals [men = 20 and women = 11]). Kohavi's assumptions were followed in relation to cross-validation and bootstrap for precision estimation and model selection. The GR was used to build the estimation equations from the multiple linear regression. The CVG was determined to analyze the validity in the estimation equations. The equations to determine the intensities were constructed by means of multiple regression, the independent variables were determined by the stepwise method, observing the significance level of p < 0.05.

RESULTS

The reliability level of Cronbach's alpha of the multiple linear regression equations was moderate for the intensity of 50% (0.51); for the intensities of 60, 70 and 80%, it corresponded to 0.50, 0.53 and 0.57, respectively.

CONCLUSION

The results show that it is possible to apply the equations in the determination of aerobic exercise intensities for healthy individuals. However, the need for further studies in other populations to prove the reliability of the proposed equations is evident.

Exercise duration: Independent effects on acute physiologic responses and the need for an individualized prescription

An individualization of exercise prescription is implemented mainly in terms of intensity but not for duration. To survey the need for an individualized exercise duration prescription, we investigated acute physiologic responses during constant‐load exercise of maximal duration (t_max) and determined so‐called duration thresholds. Differences between absolute (min) and relative terms (% t_max) of exercise duration were analyzed. Healthy young and trained male and female participants (n = 11) performed an incremental exercise test and one t_max constant‐load exercise test at a target intensity of 10% of maximal power output below the second lactate turn point (LTP₂). Blood lactate, heart rate, and spirometric data were measured during all tests. t_max was markedly different across subjects (69.6 ± 14.8 min; range: 40–90 min). However, distinct duration phases separated by duration thresholds (DTh) were found in most measured variables. These duration thresholds (except DTh1) were significantly related to t_max (DTh2: r² = 0.90, p < 0.0001; DTh3: r² = 0.98, p < 0.0001) and showed substantial interindividual differences if expressed in absolute terms (DTh2: 24.8 ± 6.0 min; DTh3: 47.4 ± 10.6 min) but not in relative terms (DTh2: 35.4 ± 2.7% t_max; DTh3: 67.9 ± 2.4% t_max). Our data showed that (1) maximal duration was individually different despite the same relative intensity, (2) duration thresholds that were related to t_max could be determined in most measured variables, and (3) duration thresholds were comparable between subjects if expressed in relative terms. We therefore conclude that duration needs to be concerned as an independent variable of exercise prescription.

Graded peak cycle ergometer test for cognitively impaired patients with Parkinson's disease: a pilot study

BACKGROUND

Cognitive decline affects up to 50% of patients with Parkinson's disease (PD) in the course of the disease and may be amenable to exercise interventions. To accurately set adequate training intensities, standardized exercise testing is required but such testing takes considerable time and effort. The aim of this pilot study was to investigate the feasibility of a graded peak cycle ergometer exercise test in cognitively impaired patients with Parkinson's Disease (PD), and to define whether age-predicted maximal heart rate (HRmax) matched measured HRmax.

METHODS

A convenience sample of seven patients with PD (Hoehn and Yahr: 2-4, and cognitive impairment (Montreal Cognitive Assessment (MoCA) ≤ 26) completed a graded peak cycle ergometer test to voluntary exhaustion. Borg Rating of Perceived Exertion was used to record the individual's perception of exertion. Pre-defined age-predicted HRmax (calculated as 208-(0.7 × age) was compared with the measured HRmax using Bland-Altman plot and a two-one-sided test.

RESULTS

All PD patients completed the graded exercise test between 8-12 minutes, showing therefore 100% compliance to the test protocol. No adverse events occurred. Predicted HRmax and measured HRmax did not differ.

CONCLUSION

We demonstrate feasibility of graded peak cycle ergometer testing in PD patients with cognitive impairment. The good correspondence of age-predicted HRmax equation with measured HRmax, in this small sample, may in the future provide clinicians with a tool to define training intensities in cognitively impaired PD, without cardiac disease. However, further research is needed to confirm these results.

Pattern of the Heart Rate Performance Curve in Subjects with Beta-Blocker Treatment and Healthy Controls

(1): Heart rate performance curve (HRPC) in incremental exercise was shown to be not uniform, causing false intensity estimation applying percentages of maximal heart rate (HR_max). HRPC variations are mediated by β-adrenergic receptor sensitivity. The aim was to study age and sex dependent differences in HRPC patterns in adults with β-blocker treatment (BB) and healthy controls (C). (2): A total of 535 (102 female) BB individuals were matched 1:1 for age and sex (male 59 ± 11 yrs, female 61 ± 11 yrs) in C. From the maximum incremental cycle ergometer exercise a first and second heart rate (HR) threshold (Th1 and Th2) was determined. Based on the degree of the deflection (kHR), HRPCs were categorized as regular (downward deflection (kHR > 0.1)) and non-regular (upward deflection (kHR < 0.1), linear time course). (3): Logistic regression analysis revealed a higher odds ratio to present a non-regular curve in BB compared to C (females showed three times higher odds). The odds for non-regular HRPC in BB versus C decreased with older age (OR interaction = 0.97, CI = 0.94-0.99). Maximal and submaximal performance and HR variables were significantly lower in BB (p < 0.05). %HR_max was significantly lower in BB versus C at Th2 (male: 77.2 ± 7.3% vs. 80.8 ± 5.0%; female: 79.2 ± 5.1% vs. 84.0 ± 4.3%). %P_max at Th2 was similar in BB and C. (4): The HRPC pattern in incremental cycle ergometer exercise is different in individuals receiving β-blocker treatment compared to healthy individuals. The effects were also dependent on age and sex. Relative HR values at Th2 varied substantially depending on treatment. Thus, the percentage of Pmax seems to be a stable and independent indicator for exercise intensity prescription.

Agreement between heart rate deflection point and maximal lactate steady state in young adults with different body masses

We examined the agreement between heart rate deflection point (HRDP) variables with maximal lactate steady state (MLSS) in a sample of young males categorized to different body mass statuses using body mass index (BMI) cut-off points. One hundred and eighteen young males (19.9 ± 4.4 years) underwent a standard running incremental protocol with individualized speed increment between 0.3 and 1.0 km/h for HRDP determination. HRDP was determined using the modified Dmax method called S.Dmax. MLSS was determined using 2-5 series of constant-speed treadmill runs. Heart rate (HR) and blood lactate concentration (La) were measured in all tests. MLSS was defined as the maximal running speed yielding a La increase of less than 1 mmol/L during the last 20 min. Good agreement was observed between HRDP and MLSS for HR for all participants (±1.96; 95% CI = -11.5 to +9.2 b/min, ICC = 0.88; P < 0.001). Good agreement was observed between HRDP and MLSS for speed for all participants (±1.96; 95% CI = -0.40 to +0.42 km/h, ICC = 0.98; P < 0.001). The same findings were observed when participants were categorized in different body mass groups. In conclusion, HRDP can be used as a simple, non-invasive and time-efficient method to objectively determine submaximal aerobic performance in nonathletic young adult men with varying body mass status, according to the chosen standards for HRDP determination.

The Feasibility of High-Intensity Interval Training in Patients with Intensive Care Unit-Acquired Weakness Syndrome Following Long-Term Invasive Ventilation

Background

Intensive care unit-acquired weakness syndrome (ICUAWS) can be a consequence of long-term mechanical ventilation. Despite recommendations of early patient mobilisation, little is known about the feasibility, safety and benefit of interval training in early rehabilitation facilities (ERF) after long-term invasive ventilation.

Methods and Results

We retrospectively analysed two established training protocols of bicycle ergometry in ERF patients after long-term (> 7 days) invasive ventilation (n = 46). Patients conducted moderate continuous (MCT, n = 24, mean age 70.3 ± 10.1 years) or high-intensity interval training (HIIT, n = 22, mean age 63.6 ± 12.6 years). The intensity of training was monitored with the BORG CR10 scale (intense phases ≥ 7/10 and moderate phases ≤ 4/10 points). The primary outcome was improvement (∆-values) of six-minute-walk-test (6 MWT), while the secondary outcomes were improvement of vital capacity (VC_max), forced expiratory volume in 1 s (FEV₁), maximal inspiratory pressure (PI_max) and functional capabilities (functional independence assessment measure, FIM/FAM and Barthel scores) after 3 weeks of training. No adverse events were observed. There was a trend towards a greater improvement of 6 MWT in HIIT than MCT (159.5 ± 64.9 m vs. 120.4 ± 60.4 m; p = .057), despite more days of invasive ventilation (39.6 ± 16.8 days vs. 26.8 ± 16.2 days; p = .009). VC_max (∆0.5l ± 0.6 vs. ∆0.5l ± 0.3; p = .462), FEV₁ (∆0.2l ± 0.3 vs. ∆0.3l ± 0.2; p = .218) PI_max (∆0.8 ± 1.1 kPa vs. ∆0.7 ± 1.3pts; p = .918) and functional status (FIM/FAM: ∆29.0 ± 14.8pts vs. ∆30.9 ± 16.0pts; p = .707; Barthel: ∆28.9 ± 16.0 pts vs. ∆25.0 ± 10.5pts; p = .341) improved in HIIT and MCT.

Conclusions

We demonstrate the feasibility and safety of HIIT in the early rehabilitation of ICUAWS patients. Larger trials are necessary to find adequate dosage of HIIT in ICUAWS patients.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40798-021-00299-6.

The First Lactate Threshold Is a Limit for Heavy Occupational Work

Long-term heavy physical work often leads to early retirement and disability pension due to chronic overload, with a need to define upper limits. The aim of this study was to evaluate the value of the first lactate threshold (LTP₁) as a physiological marker for heavy occupational work. A total of 188 male and 52 female workers performed an incremental cycle ergometer test to determine maximal exercise performance and the first and second lactate (LTP₁; LTP₂) and ventilatory thresholds (VT₁; VT₂). Heart rate (HR) recordings were obtained during one eight-hour shift (HR_8h) and oxygen uptake was measured during 20 minutes of a representative work phase. Energy expenditure (EE) was calculated from gas-exchange measures. Maximal power output (P_max), maximal oxygen consumption (VO_{2 max}) and power output at LTP₁ and LTP₂ were significantly different between male and female workers. HR_8h was not significantly different between male and female workers. A significant relationship was found between P_max and power output at LTP₁. HR_8h as a percentage of maximum HR significantly declined with increasing performance (P_max:r = −0.56; p < 0.01; P_LTP1:r = −0.49; p < 0.01). Despite different cardio-respiratory fitness-levels; 95.4% of all workers performed their usual work below LTP₁. It is therefore suggested that LTP₁ represents the upper limit for sustained heavy occupational work; which supports its use to determine work capability and assessing the limits of heavy occupational work.

Intensity Thresholds and Maximal Lactate Steady State in Small Muscle Group Exercise

The aim of our study is to determine the first (LTP₁) and the second (LTP₂) lactate turn points during an incremental bicep curl test and to verify these turn points by ventilatory turn points (VT₁ and VT₂) and constant-load exercise tests. Twelve subjects performed a one-arm incremental bicep curl exercise (IET) after a one repetition maximum (1RM) test to calculate the step rate for the incremental exercise (1RM/45). Workload was increased every min at a rate of 30 reps/min until maximum. To verify LTPs, VT₁ and VT₂ were determined from spirometric data, and 30 min constant-load tests (CL) were performed at 5% P_max below and above turn points. Peak load in IET was 5.3 ± 0.9 kg (La_max: 2.20 ± 0.40 mmol·L⁻¹; HR_max: 135 ± 15 b·min⁻¹; VO_2max: 1.15 ± 0.30 L·min⁻¹). LTP₁ was detected at 1.9 ± 0.6 kg (La: 0.86 ± 0.36 mmol·L⁻¹; HR 90 ± 13 b·min⁻¹; VO₂: 0.50 ± 0.05 L·min⁻¹) and LTP₂ at 3.8 ± 0.7 kg (La: 1.38 ± 0.37 mmol·L⁻¹; 106 ± 10 b·min⁻¹; VO₂: 0.62 ± 0.11 L·min⁻¹). Constant-load tests showed a lactate steady-state in all tests except above LTP₂, with early termination after 16.5 ± 9.1 min. LTP₁ and LTP₂ could be determined in IET, which were not significantly different from VT₁/VT₂. Constant-load exercise validated the three-phase concept, and a steady-state was found at resting values below VT₁ and in all other tests except above LTP₂. It is suggested that the three-phase model is also applicable to small muscle group exercise.

Heart Rate Performance Curve Is Dependent on Age, Sex, and Performance

Introduction: The Heart Rate Performance Curve (HRPC) is neither linear nor uniform and related to ß1-adrenoceptor sensitivity. As aging and exercise influence ß1-adrenoceptors we suggested age, sex and performance effects on the HRPC. Aim of the study was to examine the effects of aging on the deflection of the HRPC in maximal incremental cycle ergometer exercise (CE) in a large cohort of healthy subjects.

Methods: Heart rate (HR) data of 2,980 men (51 ± 15 years) and 1,944 women (52 ± 14 years) were classified into age groups (≤20 up to >80 years). We analyzed age and performance (P_low 25%-quartile and P_high 75%-quartile of age predicted power) effects on HR_max and on the degree (k) and the type (regular downward deflection k > 0.1, linear −0.1 ≤ k ≤ 0.1 and atypical upward deflection k < −0.1) of the HRPC.

Results:k-values decreased significantly with age in men and women and were significantly higher in women. Atypical HRPC's increased by a linear trend from ≤20 to 70 years (m) respectively 80 years (w) from 10 to 43% (m) and 9 to 30% (w). HR_max of all age groups was lower in P_low and overall number of atypical HRPC's was 21% (m) and 16% (w) higher compared to P_high.

Conclusion: Aging increased the number of atypical HRPC's with upward deflection in CE tests, which influences exercise intensity prescription especially when using fixed percentages of HR_max. Changes in HRPC's were affected by sex and performance, where women generally and subjects with higher performance presented less atypical HRPC's even at older age.

Physiological and Perceived Exertion Responses during Exercise: Effect of β-blockade

PURPOSE

This study investigated the effect of β-blockade on physiological and perceived exertion (RPE) responses during incremental treadmill exercise.

METHODS

Sixteen healthy participants (n = 8 men; age, 25.3 ± 4.6 yr) performed a maximal treadmill exercise test after ingestion of 100 mg metoprolol or placebo, with a double-blind, randomized, and counterbalanced design. Heart rate (HR), ventilatory, and gas exchange variables were measured continuously, and participants reported RPE at the end of each minute. Physiological and RPE responses during each condition were compared at the ventilatory threshold (VT), respiratory compensation point, and at maximal exercise using repeated-measures ANOVA. Linear regression modeled relationships between perceived exertion and physiological variables.

RESULTS

The HR and V˙O2 at the VT, respiratory compensation point, and maximal exercise were all significantly lower after β-blockade (P < 0.05). However, when standardized to within condition peak values, differences were no longer significant. The RPE associated with VT was higher after β-blockade (12.9 ± 1.0 vs 12.3 ± 1.2, P < 0.05) but lower at maximal exercise (19.1 ± 0.6 vs 19.4 ± 0.5, P < 0.05). Increases in RPE relative to HR were greater after β-blockade and remained significant when expressed relative to peak HR. There was no difference in the growth of the relationship between RPE and V˙O2 across conditions, although the origin of the relationship was higher with β-blockade.

CONCLUSIONS

Although β-blockade resulted in a significant reduction in exercising HR and V˙O2, the RPE for a given relative intensity remained unchanged. The relationship between RPE and V˙O2 was not affected by β-blockade. The results provide evidence that RPE is a useful and reliable measure for exercise testing and prescription in patients prescribed β-blockade therapy.

Exercise-based cardiac rehabilitation is associated with a normalization of the heart rate performance curve deflection

The heart rate (HR) rises with increased power output, whereby in most healthy individuals, the slope of HR levels off with higher intensity. This corresponds to a downward deflection of the heart rate performance curve (HRPC). Conversely, in patients after myocardial infarction, an upward HRPC deflection is frequently observed that is especially pronounced in patients with compromised left ventricular ejection fraction. To investigate whether regular endurance training during cardiac rehabilitation might normalize HRPC, data of 128 male patients were analyzed. All patients performed three exercise tests: at baseline, after 6 weeks, and after 1 year. Ninety‐six patients exercised regularly according to guidelines for 1 year (training group, TG), and 32 stopped after 6 weeks (control group, CG). Similarly, upward‐deflected HRPCs were observed at baseline and after 6 weeks in both groups. After 1 year, TG patients had less upward‐deflected HRPCs compared with CG ones, corresponding to a partial normalization. Greater changes in HRPC deflection were associated with larger improvements in cardiorespiratory fitness. Our results might indicate improved myocardial function due to long‐term rehabilitation. Further, HRPC alterations over time should be considered when prescribing exercise intensities using a target HR, as deflection flattening might render the intensity of corresponding exercise insufficient.

Different Heart Rate Patterns During Cardio-Pulmonary Exercise (CPX) Testing in Individuals With Type 1 Diabetes

To investigate the heart rate during cardio-pulmonary exercise (CPX) testing in individuals with type 1 diabetes (T1D) compared to healthy (CON) individuals. Fourteen people (seven individuals with T1D and seven CON individuals) performed a CPX test until volitional exhaustion to determine the first and second lactate turn points (LTP₁ and LTP₂), ventilatory thresholds (VT₁ and VT₂), and the heart rate turn point. For these thresholds cardio-respiratory variables and percentages of maximum heart rate, heart rate reserve, maximum oxygen uptake and oxygen uptake reserve, and maximum power output were compared between groups. Additionally, the degree and direction of the deflection of the heart rate to performance curve (k_HR) were compared between groups. Individuals with T1D had similar heart rate at LTP₁ (mean difference) -11, [(95% confidence interval) -27 to 4 b.min^-1], at VT₁ (-12, -8 to 33 b.min^-1) and at LTP₂ (-7, -13 to 26 b.min^-1), at VT₂ (-7, -13 to 28 b.min^-1), and at the heart rate turn point (-5, -14 to 24 b.min^-1) (p = 0.22). Heart rate expressed as percentage of maximum heart rate at LTP₁, VT₁, LTP₂, VT₂ and the heart rate turn point as well as expressed as percentages of heart rate reserve at LTP₂, VT₂ and the heart rate turn point was lower in individuals with T1D (p < 0.05). k_HR was lower in T1D compared to CON individuals (0.11 ± 0.25 vs. 0.51 ± 0.32, p = 0.02). Our findings demonstrate that there are clear differences in the heart rate response during CPX testing in individuals with T1D compared to CON individuals. We suggest using submaximal markers to prescribe exercise intensity in people with T1D, as the heart rate at thresholds is influenced by k_HR. Clinical Trial Identifier: NCT02075567 (https://clinicaltrials.gov/ct2/show/NCT02075567).

Intensity- and Duration-Based Options to Regulate Endurance Training

The regulation of endurance training is usually based on the prescription of exercise intensity. Exercise duration, another important variable of training load, is rarely prescribed by individual measures and mostly set from experience. As the specific exercise duration for any intensity plays a substantial role regarding the different kind of cellular stressors, degree, and kind of fatigue as well as training effects, concepts integrating the prescription of both intensity and duration within one model are needed. An according recent approach was the critical power concept which seems to have a physiological basis; however, the mathematical approach of this concept does not allow applying the three zones/two threshold model of metabolism and its different physiological consequences. Here we show the combination of exercise intensity and duration prescription on an individual basis applying the power/speed to distance/time relationship. The concept is based on both the differentiation of intensities by two lactate or gas exchange variables derived turn points, and on the relationship between power (or velocity) and duration (or distance). The turn points define three zones of intensities with distinct acute metabolic, hormonal, and cardio-respiratory responses for endurance exercise. A maximal duration exists for any single power or velocity such as described in the power-duration relationship. Using percentages of the maximal duration allows regulating fatigue, recovery time, and adaptation for any single endurance training session. Four domains of duration with respect to induced fatigue can be derived from maximal duration obtained by the power-duration curve. For any micro-cycle, target intensities and durations may be chosen on an individual basis. The model described here is the first conceptual framework of integrating physiologically defined intensities and fatigue related durations to optimize high-performance exercise training.

Effects of High-Intensity Interval Exercise versus Moderate Continuous Exercise on Glucose Homeostasis and Hormone Response in Patients with Type 1 Diabetes Mellitus Using Novel Ultra-Long-Acting Insulin

Introduction

We investigated blood glucose (BG) and hormone response to aerobic high-intensity interval exercise (HIIE) and moderate continuous exercise (CON) matched for mean load and duration in type 1 diabetes mellitus (T1DM).

Material and Methods

Seven trained male subjects with T1DM performed a maximal incremental exercise test and HIIE and CON at 3 different mean intensities below (A) and above (B) the first lactate turn point and below the second lactate turn point (C) on a cycle ergometer. Subjects were adjusted to ultra-long-acting insulin Degludec (Tresiba/ Novo Nordisk, Denmark). Before exercise, standardized meals were administered, and short-acting insulin dose was reduced by 25% (A), 50% (B), and 75% (C) dependent on mean exercise intensity. During exercise, BG, adrenaline, noradrenaline, dopamine, cortisol, glucagon, and insulin-like growth factor-1, blood lactate, heart rate, and gas exchange variables were measured. For 24 h after exercise, interstitial glucose was measured by continuous glucose monitoring system.

Results

BG decrease during HIIE was significantly smaller for B (p = 0.024) and tended to be smaller for A and C compared to CON. No differences were found for post-exercise interstitial glucose, acute hormone response, and carbohydrate utilization between HIIE and CON for A, B, and C. In HIIE, blood lactate for A (p = 0.006) and B (p = 0.004) and respiratory exchange ratio for A (p = 0.003) and B (p = 0.003) were significantly higher compared to CON but not for C.

Conclusion

Hypoglycemia did not occur during or after HIIE and CON when using ultra-long-acting insulin and applying our methodological approach for exercise prescription. HIIE led to a smaller BG decrease compared to CON, although both exercises modes were matched for mean load and duration, even despite markedly higher peak workloads applied in HIIE. Therefore, HIIE and CON could be safely performed in T1DM.

Trial Registration

ClinicalTrials.gov NCT02075567 http://www.clinicaltrials.gov/ct2/show/NCT02075567

Identification and agreement of first turn point by mathematical analysis applied to heart rate, carbon dioxide output and electromyography

Background

The second heart rate (HR) turn point has been extensively studied, however there are few studies determining the first HR turn point. Also, the use of mathematical and statistical models for determining changes in dynamic characteristics of physiological variables during an incremental cardiopulmonary test has been suggested.

Objectives

To determine the first turn point by analysis of HR, surface electromyography (sEMG), and carbon dioxide output () using two mathematical models and to compare the results to those of the visual method.

Method

Ten sedentary middle-aged men (53.9±3.2 years old) were submitted to cardiopulmonary exercise testing on an electromagnetic cycle ergometer until exhaustion. Ventilatory variables, HR, and sEMG of the vastus lateralis were obtained in real time. Three methods were used to determine the first turn point: 1) visual analysis based on loss of parallelism between and oxygen uptake (); 2) the linear-linear model, based on fitting the curves to the set of data (Lin-Lin ); 3) a bi-segmental linear regression of Hinkley' s algorithm applied to HR (HMM-HR), (HMM- ), and sEMG data (HMM-RMS).

Results

There were no differences between workload, HR, and ventilatory variable values at the first ventilatory turn point as determined by the five studied parameters (p>0.05). The Bland-Altman plot showed an even distribution of the visual analysis method with Lin-Lin , HMM-HR, HMM-CO_2, and HMM-RMS.

Conclusion

The proposed mathematical models were effective in determining the first turn point since they detected the linear pattern change and the deflection point of , HR responses, and sEMG.

Programming exercise intensity in patients on beta-blocker treatment: the importance of choosing an appropriate method

AIM

To verify the usefulness of current recommended level of target exercise heart rate (HR) and of different HR-based methods for calculating target HR in patients with and without beta-blocker treatment.

METHODS

We studied 53 patients not treated with beta-blocker and 159 patients on beta-blocker treatment. All patients underwent a maximal exercise test with gas analysis, and first ventilatory threshold (VT1 or aerobic threshold), second ventilatory threshold (VT2 or anaerobic threshold), time of exercise, maximum load, metabolic parameters, HR at rest (HRrest), HRpeak, HR at VT1 (HRVT1) and at VT2 (HRVT2), and 75, 80, and 85% of HRmax (HR75%, HR80%, HR85%) were calculated. Exercise HR was also determined using the Karvonen formula, applying 60, 70, and 80% of the heart rate reserve (HRR) (HRKarv0.6, HRKarv0.7, and HRKarv0.8).

RESULTS

This study included 102 patients on a beta-blocker and 39 not treated with negative cronotropic effect drugs. Maximum load, metabolic parameters, HRrest, HRpeak, HRVT1, and HRVT2 were significantly lower in patients on beta-blocker treatment. The proportion of patients with a HR75%, HR80%, HR85%, ​​HRKarv0.6, HRKarv0.7, and HRKarv0.8 <VT1 and >VT2 was very high and depended on whether patients were on beta-blocker treatment.

CONCLUSIONS

Prescribed exercise intensity should be within VT1 and VT2, so that the efficacy and safety is guaranteed. If determining VT1 and VT2 is not possible, HR-based methods can be used, but with caution. In fact, there will be always a proportion of patients training below VT1 or above VT2. On the other hand, recommendations for patients on a beta-blocker should be different from patients not receiving a beta-blocker. Patients not treated with a beta-blocker should exercise at HRKarv0.7 or at HR85%. In patients on a beta-blocker, we recommend preferentially a target HR of HRKarv0.6 or HR80%.

Energy expenditure and sex differences of golf playing

The purpose of the study was to assess the average physical intensity and energy expenditure during a single round of golf on hilly and flat courses in a heterogeneous group of healthy men and women of varying age and golf handicap. Forty-two males and 24 females completed an incremental cycle-ergometer exercise test to determine exercise performance markers. The heart rate (HR), duration, distance, walking speed, ascent and descent were measured via a global positioning system (GPS)/HR monitor during the game and energy expenditure was calculated. Playing 9 or 18-holes of golf, independent of the golf course design, the average HR was not significantly different between sexes or the subgroups. The intensities were light with respect to the percentage of maximal HR and metabolic equivalents of task (METs). Total energy expenditure of all participants was not significantly different for hilly (834 ± 344 kcal) vs. flat courses (833 ± 295 kcal) whereas male players expended significantly greater energy than female players (926 ± 292 vs. 556 ± 180 kcal), but did not have significantly greater relative energy expenditure (2.8 ± 0.8 vs. 2.2 ± 0.7 METs). As a high volume physical activity, playing golf is suggested to yield health benefits. Since the intensity was well below recommended limits, golf may have health related benefits unrelated to the intensity level of the activity.

Analysis of heart rate deflection points to predict the anaerobic threshold by a computerized method

Many studies have used the heart rate deflection points (HRDPs) during incremental exercise tests, because of their strong correlation with the anaerobic threshold. The aim of this study was to evaluate the profile of the HRDPs identified by a computerized method and compare them with ventilatory and lactate thresholds. Twenty-four professional soccer players (age, 22 ± 5 years; body mass, 74 ± 7 kg; height 177 ± 7 cm) volunteered for the study. The subjects completed a Bruce-protocol incremental treadmill exercise test to volitional fatigue. Heart rate (HR) and alveolar gas exchange were recorded continuously at ≥1 Hz during exercise testing. Subsequently, the time course of the HR was fit by a computer algorithm, and a set of lines yielding the lowest pooled residual sum of squares was chosen as the best fit. This procedure defined 2 HRDPs (HRDP1 and HRDP2). The HR break points averaged 43.9 ± 5.9 and 89.7 ± 7.5% of the VO2peak. The HRDP1 showed a poor correlation with ventilatory threshold (VT; r = 0.50), but HRDP2 was highly correlated to the respiratory compensation (RC) point (r = 0.98). Neither HRDP1 nor HRDP2 was correlated with LT1 (at VO2 = 2.26 ± 0.72 L·min(-1); r = 0.26) or LT2 (2.79 ± 0.59 L·min(-1); r = 0.49), respectively. LT1 and LT2 also were not well correlated with VT (2.93 ± 0.68 L·min(-1); r = 0.20) or RC (3.82 ± 0.60 L·min(-1); r = 0.58), respectively. Although the HR deflection points were not correlated to LT, HRDP2 could be identified in all the subjects and was strongly correlated with RC, consistent with a relationship to cardiorespiratory fatigue and endurance performance.

The mathematical analysis of the heart rate and blood lactate curves during incremental exercise testing

This paper describes a new mathematical approach for the analysis of HR (heart rate) and BL (blood lactate) curves during incremental exercise testing using a HR/BL curve and its derivatives, taking into account the native shape of all curves, without any linear approximation. Using this approach the results indicate the appearance of three characteristic points (A, B and C) on the HR/BL curve. The point A on the HR/BL curve which is the value that corresponds to the load (12.73 ± 0.46 km h-1) at which BL starts to increase above the resting levels (0.9 ± 0.06 mM), and is analogous to Lactate Turn Point 1 (LTP1). The point C on the HR/BL curve which corresponds to a BL of approximately 4mM, and is analogous to LTP2. The point B on the HR/BL curve, which corresponds to the load (16.32 ± 0.49 km h-1) at which the moderate increase turns into a more pronounced increase in BL. This point has not been previously recognized in literature. We speculate this point represents attenuation of left ventricular ejection fraction (LVEF) increase, accompanied by the decrease in diastolic time duration during incremental exercise testing. Proposed mathematical approach allows precise determination of lactate turnpoints during incremental exercise testing.

Special needs to prescribe exercise intensity for scientific studies

There is clear evidence regarding the health benefits of physical activity. These benefits follow a dose-response relationship with a particular respect to exercise intensity. Guidelines for exercise testing and prescription have been established to provide optimal standards for exercise training. A wide range of intensities is used to prescribe exercise, but this approach is limited. Usually percentages of maximal oxygen uptake (VO₂) or heart rate (HR) are applied to set exercise training intensity but this approach yields substantially variable metabolic and cardiocirculatory responses. Heterogeneous acute responses and training effects are explained by the nonuniform heart rate performance curve during incremental exercise which significantly alters the calculations of %HR_max and %HRR target HR data. Similar limitations hold true for using %VO_2max and %VO₂R. The solution of these shortcomings is to strictly apply objective submaximal markers such as thresholds or turn points and to tailor exercise training within defined regions.

Value of the Application of the Heart Rate Performance Curve in Sports

The heart rate performance curve (HRPC) has been shown to be nonlinearly related to work load. This phenomenon has been used to determine a defection point and to be related to the lactate anaerobic threshold. The original method was heavily criticized, and the method was challenged by several authors. However, some authors also demonstrated a high value for this method’s application in various sports conditions. Unfortunately, the HRPC was shown to be not uniform and three different patterns were found. Basic investigations have shown a dependence of the HR-defection on beta1-receptor sensitivity, which gave a plausible explanation of the phenomenon. Important details regarding the testing protocol and the method of turn point determination are given in this review. As a conclusion, we may state that based on numerous studies the method is plausible and valid to determine aerobic exercise performance in various laboratory ergometer and specific sports-related field conditions. Standard protocol conditions adjusted to the exercise performance level of subjects and a computer-supported determination of turn points are necessary to obtain reliable results. Large-scale investigations to validate the heart rate turn point with maximal lactate steady state are still needed. However, from the available literature, the application of this noninvasive method can be recommended to determine aerobic exercise performance in various sports. This noninvasive test is easy to perform repeatedly, which gives interesting possibilities for the monitoring of training adaptation in the short term, such as altitude training or specifc taper forms.

Beta1-adrenoceptor mediated origin of the heart rate performance curve deflection

PURPOSE

The deflection of the HR performance curve (HRPC) has been described as an objective marker of submaximal exercise performance. HR response to incremental cycle ergometer exercise is shown to be neither linear nor uniform and a physiological explanation of the deflection phenomenon is lacking. We hypothesized that differences in the beta1-adrenoceptor site are the source of these differences. The aim of the study was to investigate the influence of the highly selective beta1-adrenoceptor (beta1-AR) antagonist bisoprolol (Bi) on the HRPC in young healthy male subjects with different HR response patterns.

METHODS

Sixteen subjects were treated in randomized order with Bi or a placebo (Pl) in two separate trials. HR response during incremental cycle ergometer exercise was compared between the two trials. Blood lactate concentration (La) and ventilatory variables were measured throughout both tests.

RESULTS

Bi changed the direction of the HRPC more in subjects with a regular, s-shaped response pattern under placebo than those with a nonregular or linear pattern. The influence of Bi on the HR at the second lactate turn point was significantly related (R = 0.78; P < 0.001) to the pattern of the HRPC in Pl conditions.

CONCLUSION

We suggest that differences between the subjects with regular s-shaped versus nonregular HRPC may be due to differences at the beta1-AR site. The origin of the HRPC deflection is mediated in part by the beta1-AR sensitivity.

Influence of beta-blocker use on percentage of target heart rate exercise prescription

BACKGROUND

Exercise is recommended for cardiac patients irrespective of beta-blockers. Percentages of maximal heart rate (%HRmax) and heart rate reserve (%HRR) are widely used to determine training intensities. The purpose of this study was to investigate the influence of chronic cardioselective beta blockade on the %HRmax and %HRR model.

METHODS

Ten healthy male subjects randomly received oral placebo or beta-blocker bisoprolol (5 mg/day) for 2 weeks using a double-blind, crossover design. In the second week, the subjects performed a cardiopulmonary exercise test until exhaustion to determine the aerobic (AeT) and anaerobic (AnT) threshold.

RESULTS

No significant differences were found for absolute and relative values of oxygen consumption, power output and ratings of perceived exertion at AeT, AnT and maximum workload. Mean HR was significantly (P<0.05) lower at rest (-15 +/- 5 bpm), AeT (-19 +/- 8 bpm), AnT (-22 +/- 10 bpm) and maximal workload (-19 +/- 11 bpm) with bisoprolol compared to placebo. Percentage of maximal heart rate (%HRmax) was significantly (P<0.05) reduced at rest (43 versus 39%), AeT (64 versus 60%) and AnT (86 versus 82%), a trend for a reduction was found for %HRR at AnT (75 versus 71%, P=0.07).

CONCLUSIONS

Exercise prescription using %HRmax or %HRR methods are of limited accuracy for patients taking beta-blockers. Although %HRmax and %HRR are easy to determine and therefore attractive, we suggest that the most precise exercise prescription would depend on AeT and AnT. Percentages of maximal oxygen consumption or maximal workload or ratings of perceived exertion may be suggested as a substitute. Alternatively, upper limits for %HRmax and %HRR should be lower for patients taking beta-blockers.