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Variation in Heart Rate During Submaximal Exercise: Implications for Monitoring Training
Abstract
A change in heart rate at a controlled submaximal exercise intensity is used as a marker of training status. However, the standard error of measurement has not been studied systematically, and therefore a change in heart rate, which can be considered relevant, has not been determined. Forty-four subjects (26.5 +/- 5.4 years; mean +/- standard deviation) participated in a submaximal running test at the same time of day for 5 consecutive days. Heart rates were determined during each of the 4 exercise intensities (2 minutes each) of increasing intensity and during the 1-minute recovery period after each stage. The repeatability of the heart rate on a day-to-day basis during the stages and recovery periods were high (intraclass correlation coefficient: 95% confidence interval R = 0.94- 0.99). The lowest variation in heart rate occurred in the fourth stage ( approximately 90% maximum heart rate) with heart rate varying 5 +/- 2 b.min(-1) (95% confidence interval for coefficient of variation = 1.1-1.4%). In conclusion, the standard error of measurement of submaximal heart rate is 1.1-1.4%. This magnitude of measurement error needs to be considered when heart rate is used as a marker of training status.
Supplementary resources (2)
... Por su parte, en un estudio elaborado porBarak et al. (2010) se eligió una intensidad del 80% de la FC pico para aplicar una carga de ejercicio SM en cicloergómetro. También se ha indicado que la variación de la FC durante un ejercicio SM parece estar entre 3 y 6 pulsaciones por minuto (Arts y Kuipers, 1994; Brisswalter y Legros, 1994; Lambert, 1998 enLamberts et al. 2004).A altas intensidades la FC coincide con la acumulación de lactato en sangre, lo que es usado paraestablecer zonas de intensidad (Arkinstall, 2001; Halson, 2002 en Achten y Jeukendrup, 2003). Se ha propuesto un método indirecto para determinar el umbral anaeróbico sólo basándose en la FC (Conconi, 1982 en Achten y Jeukendrup, 2003) en el cual se ha encontrado una relación lineal entre la ...
... ; Chien, 2000 enChen et al. 2006). Se supone que la FCR es más rápida cuando la condición aeróbica del sujeto es mejor, por lo tanto el porcentaje de la misma aumentaría cuando se eleve el nivel de condición física (Dennis y Noakes, 1998 enLamberts et al. 2004). Así, la FC se recupera más rápido en sujetos entrenados que en sujetos no entrenados luego de realizar ejercicio a intensidades similares (Bunc, 1988; Short y Sedlok, 1997 enLamberts et al. 2009).Se ha establecido un decaimiento exponencial para graficar la respuesta de la FC post-ejercicio la cual expresa claramente el comportamiento de dicha curva tras el esfuerzo SM, ya que el sistema parasimpático desencadenaría esta curva exponencial(Pierpont, 2000 en Borresen y Lambert, 2008). ...
... (Berry, 1992 enZaletel et al. 2009).En el ejercicio de corta duración y en estado estacionario existe una relación lineal entre la FC, el VO₂ máx. y la intensidad del ejercicio (Arts y Kuipers, 1994 enLamberts et al. 2004). Asimismo, en el ejercicio de intensidad moderada existe una relación lineal entre la FC y el VO₂ máx. ...
El objetivo de este estudio fue determinar el efecto de un programa de intervención en el desarrollo motor grueso, en un grupo de 46 niños y 31 niñas de párvulo, cuyas edades fluctúan entre 3 a 4 años de edad. Los niños fueron designados aleatoriamente en dos grupos: Grupo Control (GC n= 26), el cual recibió el programa regular de educación parvularia. Grupo experimental (GC n= 51), el cual recibe el programa regular de educación parvularia más una sesión semanal de 60 minutos de intervención
motriz, aplicada por un profesor de educación física, durante 12 semanas. Todos los participantes fueron evaluados con el “Test of Gross Motor Development” (TGMD-2), antes y después del estudio. Luego de los análisis realizados se concluye que el programa de intervención motriz, genero un aumento significativo en el desarrollo motor grueso, a favor del grupo experimental en las variables evaluadas en el TGMD-2, no así en la variable edad cronológica, donde no se observaron diferencias significativas. Además se observan diferencias significativas entre los varones y las damas, favoreciendo a los varones en el test locomotor y control de objetos, no así en las demás variables,
evaluadas por el TGMD-2, donde no se observaron diferencias significativas entre los varones y las damas.
... The use of heart rate (HR) measures during submaximal running tests, including exercise heart rate (HR ex ) and heart rate recovery (HRR), is well documented (8,12,20,21,24,25,35). Although many running-based submaximal tests have been used to assess reliability, validity, or the usefulness of HR measures (1,4,(8)(9)(10)12,15,20,21,(23)(24)(25)27,31,37), these procedures have typically used long exercise durations or need prior warm-up because of their high intensity. ...
... The use of heart rate (HR) measures during submaximal running tests, including exercise heart rate (HR ex ) and heart rate recovery (HRR), is well documented (8,12,20,21,24,25,35). Although many running-based submaximal tests have been used to assess reliability, validity, or the usefulness of HR measures (1,4,(8)(9)(10)12,15,20,21,(23)(24)(25)27,31,37), these procedures have typically used long exercise durations or need prior warm-up because of their high intensity. Indeed, longer duration tests of $6 minutes with higher final running velocities (i.e., $14 km$h 21 ) typically provide better estimations of maximal intermittent capacity compared with shorter duration tests of #4 minutes (4,20,21,23,37). ...
... Similarly, the CV of HR ex during the SWT (CV = 1.4%) was in agreement with the reported range of 1.3-2.0% (4,9,25,31,37) but lower than other studies' reporting values of ;3-4% (10,12,21). ...
Two studies were conducted to assess the reliability and validity of a submaximal warm-up test (SWT) in professional soccer players. For the reliability study, 12 male players performed SWT over three trials, with one week between trials. For the validity study, 14 players of the same team performed SWT and 30-15 Intermittent Fitness Test (30-15IFT) 7 days apart. Week-to-week reliability in selected heart rate (HR) responses [exercise HR (HRex), HR recovery (HRR) expressed as the number of beats recovered within 1 min (HRR60s) and expressed as the mean HR during 1 min (HRpost1)], were determined using intraclass correlation coefficient (ICC) and typical error of measurement expressed as coefficient of variation (CV). The relationships between HR measures derived from SWT and the maximal speed reached at the 30-15IFT (VIFT) were used to assess validity. The range for ICC and CV values were 0.83 to 0.95 and 1.4 to 7.0% in all HR measures, respectively, with the HRex as the most reliable HR measure of SWT. Inverse large (r = -0.50, 90% confidence limits, CL (-0.78; -0.06)) and very large (r = -0.76, CL, -0.90; -0.45) relationships were observed between HRex and HRpost1 with VIFT in relative (expressed as the % of maximal HR) measures, respectively. SWT is a reliable and valid submaximal test to monitor high-intensity intermittent running fitness in professional soccer players. In addition, the test’s short duration (5-min) and simplicity mean that it can be used regularly to assess training status in high-level soccer players.
... Previous studies have demonstrated that HR at a fixed submaximal exercise intensity is augmented with increasing bout duration, in presence of overtraining or with a lack of conditioning, but conversely decreases as aerobic fitness improves [20,21]. Lamberts et al. [22] have shown that, under controlled conditions in which the training status does not change, submaximal HR might vary ±7 bpm when the exercise intensity is approximately 90% of HRmax. In our study, subjects performed intermittent training sessions (25-100% of PPO). ...
... Although high intensities were reached momentarily during the training sessions, HR was submaximal and relatively constant throughout the two-week period. Furthermore, the difference between the training session HR ranged from 1 to 5 bpm, which is within the magnitude of day-to-day variation previously suggested [22]. ...
Rating of perceived exertion (RPE) and session RPE (sRPE) are reliable tools for predicting exercise intensity and are alternatives to more technological and physiological measurements, such as blood lactate (HLa) concentration, oxygen consumption and heart rate (HR). As sRPE may also convey some insights into accumulated fatigue, the purpose of this study was to examine the effects of progressive fatigue in response to heavier-than-normal training on sRPE, with absolute training intensity held constant, and determine its validity as marker of fatigue. Twelve young adults performed eight interval workouts over a two-week period. The percentage of maximal HR (%HRmax), HLa, RPE and sRPE were measured for each session. The HLa/RPE ratio was calculated as an index of fatigue. Multilevel regression analysis showed significant differences for %HRmax (p = 0.004), HLa concentration (p = 0.0001), RPE (p < 0.0001), HLa/RPE ratio (p = 0.0002) and sRPE (p < 0.0001) across sessions. Non-linear regression analysis revealed a very large negative relationship between HLa/RPE ratio and sRPE (r = −0.70, p < 0.0001). These results support the hypothesis that sRPE is a sensitive tool that provides information on accumulated fatigue, in addition to training intensity. Exercise scientists without access to HLa measurements may now be able to gain insights into accumulated fatigue during periods of increased training by using sRPE.
... In normoxia, the intraclass correlation coefficients (ICC) for submaximal and maximal HR could be considered as high, since they have been reported to be greater than 0.9, the higher the HR, the lower the variation (Lamberts et al., 2004;Tulumen et al., 2011). But expressed in bpm, the day-to-day variations in submaximal HR could be estimated to around 5-8 bpm (Lamberts et al., 2004). ...
... In normoxia, the intraclass correlation coefficients (ICC) for submaximal and maximal HR could be considered as high, since they have been reported to be greater than 0.9, the higher the HR, the lower the variation (Lamberts et al., 2004;Tulumen et al., 2011). But expressed in bpm, the day-to-day variations in submaximal HR could be estimated to around 5-8 bpm (Lamberts et al., 2004). It means that the difference in HR max between normoxia and hypoxia that could be expected at 2,500 m (Figure 2 and specific example given above) could be hidden by the spontaneous fluctuations of HR for a given training load. ...
The use of exercise intervention in hypoxia has grown in popularity amongst patients, with encouraging results compared to similar intervention in normoxia. The prescription of exercise for patients largely rely on heart rate recordings (percentage of maximal heart rate (HRmax) or heart rate reserve). It is known that HRmax decreases with high altitude and the duration of the stay (acclimatization). At an altitude typically chosen for training (2,000-3,500 m) conflicting results have been found. Whether or not this decrease exists or not is of importance since the results of previous studies assessing hypoxic training based on HR may be biased due to improper intensity. By pooling the results of 86 studies, this literature review emphasizes that HRmax decreases progressively with increasing hypoxia. The dose–response is roughly linear and starts at a low altitude, but with large inter-study variabilities. Sex or age does not seem to be a major contributor in the HRmax decline with altitude. Rather, it seems that the greater the reduction in arterial oxygen saturation, the greater the reduction in HRmax, due to an over activity of the parasympathetic nervous system. Only a few studies reported HRmax at sea/low level and altitude with patients. Altogether, due to very different experimental design, it is difficult to draw firm conclusions in these different clinical categories of people. Hence, forthcoming studies in specific groups of patients are required to properly evaluate (1) the HRmax change during acute hypoxia and the contributing factors, and (2) the physiological and clinical effects of exercise training in hypoxia with adequate prescription of exercise training intensity if based on heart rate.
... Outstanding aerobic endurance-i.e., the capacity to sustain a very high fraction of VO 2max for a given duration-can be associated with a combination of several factors, including a high percentage of type I muscle fibres, the capacity to store large amounts of muscle and/or liver glycogen, the capacity to spare carbohydrates in reserve by using more fatty acids as energy substrates, and the capacity to efficiently dissipate heat [8,9]. Similarly, cardiorespiratory fitness can also be influenced by socio-demographic features, such as sex [10][11][12], athletic performance [13] or age [14], but the available information is inconsistent, mainly because the mode of exercise (its intensity and duration [15]) can also affect physiological response. Therefore, taking into account that field incremental running tests play a key role in the training prescription and monitoring processes in recreational runners, and the non-consensus about the influence of socio-demographic differences on the physiological impact of these tests, the main purpose of this study is to describe the acute cardiovascular and thermoregulatory responses to an incremental running test in recreationally trained endurance runners, as well as to determine the influence of sex, athletic performance and age differences on that response. ...
... However, the available information is highly controversial. Although Arena et al. [12] observed similar results to the current study-faster recovery in males-, Antelmi et al. [11] found just the opposite, while Lamberts et al. [10] did not report gender-based differences. In a systematic review, Daanen et al. [18] pointed out more influencing factors on HRrec after exercise-age, training status, mode of exercise or possible accumulation of exhaustion-, which could be the rationale of differences previously reported. ...
Objective: To describe the acute cardiovascular and thermoregulatory responses to an incremental running test in recreationally trained endurance runners, as well as to determine the influence of sex, athletic performance and age differences on that response. Equipment and methods: Seventy-six recreationally trained endurance runners, 45 men and 31 women, participated in this study. An incremental running test was performed, and the cardiovascular-peak (HRpeak), recovery heart rate (HRrec) and thermoregulatory responses (tympanic temperature) were monitored during the protocol. The rate of perceived exertion (RPE) was also recorded. Results: Cluster analysis was grouped according to the athletic performance, in terms of estimated VO2max, and according to age. The ANOVA between groups (by sex, athletic performance and age) revealed no significant differences in thermoregulatory response or RPE (P ≥0.05). As for the cardiovascular response, significant differences were found according to sex in HRrec (P <0.01) and average heart rate (P <0.05), whilst HRpeak significantly differed according to age (P <0.001). Conclusions: The obtained results showed that sex and age are influencing factors on cardiovascular response to an incremental running test in recreational endurance runners, whilst athletic performance does not. Likewise, the acute thermoregulation response during these types of running exercises did not differ according to sex, athletic performance or age.
... It has been suggested that overtraining causes a disturbance in autonomic control [93] which will be reflected in recovery heart rate. In accordance with this, we have designed a submaximal shuttle test comprising 4 stages of increasing intensity interspersed with recovery periods [94]. In this test the subjects are asked to run between two lines, drawn 20 meters apart on a rubberised indoor floor. ...
... Furthermore, the test is easy to administer and about 20 athletes can do the test simultaneously. The test has a high reliability and low standard error of measurement (1.1%) [94]. For the information to be useful, the test needs to be done on a weekly basis, so that a profile for each player can be established. ...
Training can be described as a process that induces biological adaptations The basic principle of training is that training (breakdown) is followed by rest (recovery) which results in an improvement in performance. An imbalance in the training load and recovery time can result in symptoms of fatigue. If the imbalance between training and rest persists, the athlete may develop serious symptoms of fatigue that will affect the ability to sustain a high training volume and will have a negative effect on performance. While it is important for a coach to have a training plan, it is also important to be able to adjust the plan based on how the athlete is adapting. A coach needs to be able to answer a series of questions in order to make decisions about training prescription. Information to assist the coach in answering these questions can be acquired from various measurements including perception of effort, session RPE, recovery scales, Profile of Mood States (POMS), Daily Analysis of Life Demands for Athletes (DALDA), assessment of muscle soreness and recovery heart rate. This information can guide decision-making about training and reduce the risk of under or overtraining.
... Although part of our included studies [25,46], taken together with previous research in endurance athletes [76,77], have highlighted an improved absolute reliability (i.e., reduced TE) at higher SMFT intensities, one of the key findings of the current meta-analysis was that SMFT exercise intensity (expressed as HRex) had no effect upon absolute and relative reliability estimates (Figs. 3 and 4, panel B). Indeed, we found somewhat improved estimates of absolute reliability (TE) in lower versus higher intensities, but these differences were clearly trivial (ln diff = 0.06 [95% CI -0.02 to 0.15] for every 5-point % increase in exercise intensity). ...
Background
Submaximal fitness tests (SMFT) are a pragmatic approach for evaluating athlete’s physiological state, due to their time-efficient nature, low physiological burden and relative ease of administration in team sports settings. While a variety of outcome measures can be collected during SMFT, exercise heart rate (HRex) is the most popular. Understanding the measurement properties of HRex can support the interpretation of data and assist in decision making regarding athlete’s current physiological state and training effects.
Objectives
The aims of our systematic review and meta-analysis were to: (1) establish meta-analytic estimates of SMFT HRex reliability and convergent validity and (2) examine the moderating influence of athlete and protocol characteristics on the magnitude of these measurement properties.
Methods
We conducted a systematic literature search with MEDLINE, Scopus and Web of Science databases for studies published up until January 2022 since records began. Studies were considered for inclusion when they included team sports athletes and the reliability and/or convergent validity of SMFT HRex was investigated. Reliability statistics included the group mean difference (MD), typical error of measurement (TE) and intraclass correlation coefficient (ICC) derived from test–retest(s) designs. Pearson’s correlation coefficient (r) describing the relationship between SMFT HRex and a criterion measure of endurance performance was used as the statistic for convergent validity. Qualitative assessment was conducted using risk of bias assessment tool for non-randomised studies. Mixed-effects, multilevel hierarchical models combined with robust variance estimate tests were performed to obtain pooled measurement property estimates, effect heterogeneity, and meta-regression of modifying effects.
Results
The electronic search yielded 21 reliability (29 samples) and 20 convergent validity (29 samples) studies that met the inclusion criteria. Reliability meta-analysis indicated good absolute (MD = 0.5 [95% CI 0.1 to 0.9] and TE = 1.6 [95% CI 1.4 to 1.9] % points), and high relative (ICC = 0.88 [95% CI 0.84 to 0.91]) reliability. Convergent validity meta-analysis indicated an inverse, large relationship (r = − 0.58 [95% CI − 0.62 to − 0.54]) between SMFT HRex and endurance tests performance. Meta-regression analyses suggested no meaningful influence of SMFT protocol or athlete characteristics on reliability or convergent validity estimates.
Conclusions
Submaximal fitness test HRex is a reliable and valid proxy indicator of endurance performance in team sport athletes. Athlete and SMFT protocol characteristics do not appear to have a meaningful effect on these measurement properties. Practitioners may implement SMFT HRex for monitoring athlete’s physiological state by using our applied implications to guide the interpretation of data in practice. Future research should examine the utility of SMFT HRex to track within-athlete changes in aerobic capacity, as well as any further possible effects of SMFT protocols design elements or HRex analytical methods on measurement properties.
Registration Protocol registration can be found in Open Science Framework and available through https://doi.org/10.17605/OSF.IO/9C2JV.
... Whenever HRex at a standardized submaximal intensity is used as a marker of aerobic fitness, factors such as training status, environmental conditions or time of day can all influence the HR -exercise intensity relationship [54]. Provided that these circumstances are tightly controlled, HRex has been found to be a highly reliable measure [55] and the lowest day-to-day variations have been reported for intensities > 85 % of HRmax [56]. It has been proposed that a change in submaximal HRex of more than 3 beats . ...
This systematic review provides a synthesis of research investigating submaximal protocols to monitor changes in cardiocirculatory fitness in running-based sports. Following PRISMA guidelines, 2,452 records were identified and 14 studies, representing 515 athletes, satisfied the eligibility criteria. While most studies found large associations between changes in heart rate at standardized, submaximal running speeds and changes in aerobic fitness (r=0.51–0.88), three studies failed to establish a relationship (r=0.19–0.35). The intensity of the submaximal protocols seems to be relevant, with changes in running speeds at 90% of maximal heart rate showing larger relationships with changes in aerobic fitness (r=0.52–0.79) compared to 70% of maximal heart rate (r=0.24–0.52). Conversely, changes in post-exercise heart rate variability were very largely associated with changes in aerobic fitness when the testing protocols were less intense (70% of maximal heart rate) (r=0.76–0.88), but not when the test required participants to achieve 90% of their maximal heart rate (r=−0.02–0.06). Studies on post-exercise heart rate recovery revealed inconclusive results (r=−0.01– −0.55), while rate of heart rate increase may be a promising athlete monitoring metric (r=0.08– −0.84) but requires further research. In summary, when executed, analyzed, and interpreted appropriately, submaximal protocols can provide valuable information regarding changes in athlete cardiocirculatory fitness.
... HRR is also strongly associated with cognitive impairment in aging (Intzandt et al., 2020;Mehta, 2012). Defined as the change in the heart rate from the peak of exercise to the heart rate after 1-min and 2-min cessation (Lamberts et al., 2004), HRR reflects the dynamic mechanisms of autonomic heart rate regulation and can be easily measured through a submaximal exercise fitness assessment (Oppewal et al., 2014), which is generally recommended due to challenges with the gold standard CRF assessment the maximal oxygen uptake (VO 2max ) in the aging population. ...
Background
Neuroplasticity and cardiovascular health behavior are critically important factors for optimal brain health.
Objective
To assess the association between the efficacy of the mechanisms of neuroplasticity and metrics of cardiovascular heath in sedentary aging adults.
Methods
We included thirty sedentary individuals (age = 60.6 ± 3.8 y; 63 % female). All underwent assessments of neuroplasticity, measured by the change in amplitude of motor evoked potentials elicited by single-pulse Transcranial Magnetic Stimulation (TMS) at baseline and following intermittent Theta-Burst (iTBS) at regular intervals. Cardiovascular health measures were derived from the Incremental Shuttle Walking Test and included Heart Rate Recovery (HRR) at 1-min/2-min after test cessation. We also collected plasma levels of brain-derived neurotrophic factor (BDNF), vascular endothelial growth factor (VEGF), and c-reactive protein.
Results
We revealed moderate but significant relationships between TMS-iTBS neuroplasticity, and the predictors of cardiovascular health (|r| = 0.38 to 0.53, p < .05). HRR1 was the best predictor of neuroplasticity (β = 0.019, p = .002). The best fit model (Likelihood ratio = 5.83, p = .016) of the association between neuroplasticity and HRR1 (β = 0.043, p = .002) was selected when controlling for demographics and health status. VEGF and BDNF plasma levels augmented the association between neuroplasticity and HRR1.
Conclusions
Our findings build on existing data demonstrating that TMS may provide insight into neuroplasticity and the role cardiovascular health have on its mechanisms. These implications serve as theoretical framework for future longitudinal and interventional studies aiming to improve cardiovascular and brain health. HRR1 is a potential prognostic measure of cardiovascular health and a surrogate marker of brain health in aging adults.
... This technique is yet to be used in modern clinical diagnosis since it has proven to provide crucial information about heart and lung diseases. As a special case, the analysis of the heart rate (HR) has been proven to predict diseases such as sepsis [11], hypotension [12], or arrhythmias [13], and variations in this parameter have been widely used as biomarkers of hypoxemia at birth [14] to depth anesthesia [15] or epilepsy [16] states, baro-oscillatory phenomenon frequency in diabetic patients [17], sport performance [18], etc. Moreover, there are also a huge number of shortterm extrinsic factors related to HR variations, independent of the health baseline of the patient [19]. ...
In this paper, a noninvasive portable prototype is presented for biomedical audio signal processing. The proposed prototype is suitable for monitoring the health of patients. The proposed hardware setup consists of a cost-effective microphone, multipurpose microcontroller and computing node that could be a mobile phone or general-purpose computer. Using parallel and high-performance techniques, this setup allows one to register and wirelessly multicast the recorded biomedical signals to computing nodes in real time. The developed prototype was used as a case study to estimate the heart rate (HR) from the captured biomedical audio signal. In this regard, the developed algorithm for estimating HR comprises three stages: preprocessing, separation, and HR estimation. In the first stage, the signal captured by the microphone is adapted for processing. Subsequently, a separation stage was proposed to alleviate the acoustic interference between the lungs and heart. The separation is performed by combining a non-negative matrix factorization algorithm, clustering approach, and soft-filter strategy. Finally, HR estimation was obtained using a novel and efficient method based on the autocorrelation function. The developed prototype could be used not only for the estimation of the HR, but also for the retrieval of other biomedical information related to the recording of cardiac or respiratory audio signals. The proposed method was evaluated using well-known datasets and compared with state-of-the-art algorithms for source-separation. The results showed that it is possible to obtain an accurate separation and reliable real-time estimation in terms of source separation metrics and relative error in the tested scenarios by combining multi-core architectures with parallel and high-performance techniques. Finally, the proposed prototype was validated in a real-world scenario.
... Although part of our included studies [25,46], taken together with previous research in endurance athletes [76,77], have highlighted an improved absolute reliability (i.e., reduced TE) at higher SMFT intensities, one of the key findings of the current meta-analysis was that SMFT exercise intensity (expressed as HRex) had no effect upon absolute and relative reliability estimates ( Fig. 2 and 3, SMFT seems a reasonable approach, the rationale for using a particular method and/or time span in other SMFT protocols was not provided in the included studies. Whilst we observed trivial differences between methods (Fig. 2-4, panel E), mean HR over a particular time-frame before the SMFT cessation maybe deemed preferable [4,9] since it minimises a potential measurement noise such as HR spikes owing to signal error. ...
Background
Submaximal Fitness Tests (SMFT) are a pragmatic approach for evaluating athlete’s physiological state, due to their time-efficient nature, low physiological burden and relative ease of administration in team-sports settings. Whilst a variety of outcome measures can be collected during SMFT, exercise heart rate (HRex) is the most popular. Understanding the measurement properties of HRex can support the interpretation of data and assist in decision-making regarding athlete’s current physiological state and training effects.Objectives
The aims of our systematic review and meta-analysis were to: 1) establish meta-analytic estimates of SMFT HRex reliability and convergent validity; and 2) examine the moderating influence of athlete and protocol characteristics on the magnitude of these measurement properties.Methods
We conducted a systematic literature search with MEDLINE, Scopus and Web of Science databases for studies published up until January 2022 since records began. Studies were considered for inclusion when the reliability and/or convergent validity of SMFT HRex was investigated. Reliability statistics included the group mean difference (MD), typical error of measurement (TE) and intraclass correlation coefficient (ICC) derived from test-retest(s) designs. Pearson’s correlation coefficient (r) describing the relationship between SMFT HRex and a criterion measure of endurance performance was used as the statistic for convergent validity. Mixed-effects, multilevel hierarchical models, combined with robust variance estimate tests were performed to obtain pooled measurement property estimates, effect heterogeneity, and meta-regression of modifying effects. ResultsThe electronic search yielded 21 reliability (29 samples) and 20 convergent validity (29 samples) studies that met the inclusion criteria. Reliability meta-analysis indicated good absolute (MD = 0.5 [95% CI: 0.1 to 0.9] and TE = 1.6 [1.4 to 1.9] % points), and high relative (ICC = 0.88 [0.84 to 0.91]) reliability. Convergent validity meta-analysis indicated an inverse, large relationship (r = –0.58 [–0.62 to –0.54]) between SMFT HRex and endurance tests performance. Meta-regression analyses suggested no meaningful influence of SMFT protocol or athlete characteristics on reliability or convergent validity estimates.Conclusions
Submaximal Fitness Test HRex is a reliable and valid proxy indicator of endurance performance in team-sport athletes. Athlete and SMFT protocol characteristics do not appear to have a meaningful effect on these measurement properties. Practitioners may implement SMFT HRex for monitoring athlete’s physiological state by using our applied implications to guide the interpretation of data in practice. Future research should examine the utility of SMFT HRex to track within-athlete changes in aerobic capacity, as well as any further possible effects of SMFT protocols design elements or HRex analytical methods on measurement properties.
... However, despite the advances in swimrun training, it would be beneficial to provide athletes with modern training strategies. This would include constructing programmes based on internal markers of cardiovascular fitness, such as V_O 2 max (would require lab testing), 29 heart rate zone tests 30 during running and swimming, and swimming tests 31 (timed swim sets, distance per stroke tests, lactate testing if available). Using these values could inform coaches to create more effective training strategies, keeping in mind the swimrun race being trained for: terrain type, running:swimming ratio, total distance and partner selection. ...
Swimrun was established in Sweden in 2006. In competition athletes alternate between running and swimming multiple times. It has grown from only being hosted in Sweden to now being a global sport. The swimrun race exposes athletes to environments that require a unique set of skills. For example, participants have to negotiate ocean currents and waves. The environmental conditions change between the runs and the swims. Athletes may be exposed to hot temperatures when running in wetsuits (25 oC and hotter) and cold water (colder than 16 oC) when swimming. This sudden change in environmental conditions imposes a poorly defined physiological stress on the participants. Research on the demands of swimrun is scarce. More research is needed to improve athlete safety during events. Also, research is needed to provide insight into enhance training methods and performance.
... 269such, their reliability and usefulness to field based sports may be limited. For example, past 270 findings have suggested that when exercising at a higher intensity, HR measures are more 271 reliable and sensitive to change(Lamberts et al. 2004;Lamberts and Lambert 2009). ...
Purpose: The aim of the present study was to examine the reliability and usefulness of a proposed 4-min individualised submaximal shuttle run test (SSRIndiv) in elite rugby league players.
Materials and methods: Twenty-two elite rugby league players competing in the National Rugby League competition (23.2 ± 3.4 years, 186.8 ± 5.4 cm, 100.2 ± 8.5 kg) performed the SSRIndiv twice, seven days apart (test–retest design). The SSRIndiv was prescribed as 75% of the average speed during a 1500-m time trial. Exercise heart rate was calculated as the average heart rate (HR) over the final 30 s (HRex). Seated HR recovery (HRR) was recorded at 1- (HRR60) and 2-min (HRR120) post-exercise. Data were analysed with magnitude-based inferences.
Results: Test–retest typical errors were moderate for HRex (1.2 percentage points; 90% confidence limits: 1.0–1.7), HRR60 (3.4; 2.7–4.6) and HRR120 (2.9; 2.3–3.9). Intraclass correlation coefficients were extremely high for HRex (0.91; 0.78–0.94) and very high for both HRR60 (0.80; 0.61–0.90) and HRR120 (0.84; 0.69–0.92). Thresholds for an individual change that would be likely small and greater than the typical error were ±1.8 (percentage points), ±4.6 and ±4.1 for HRex, HRR60 and HRR120, respectively.
Conclusions: The SSRIndiv demonstrates acceptable reliability in the assessment of HRex and HRR, thus demonstrating its potential usefulness for monitoring fitness and fatigue in elite rugby league players.
... Monitoring of submaximal HR provides athletes and practitioners with a low cost and non-invasive tool to assess changes in training status and may provide an indication of overtraining (Achten & Jeukendrup, 2003;Lambert et al., 1998). Under controlled conditions, HR has shown daily variability of 5-8 beats min −1 at submaximal running speeds in physically active adults (Lamberts, Lemmink, Durandt, & Lambert, 2004). The variability across all speeds in the present study is slightly lower (mean difference: 4 ± 4 beats min −1 , 95% CI: 3.7-5.2 ...
This study aimed to quantify the intra-individual reliability of a number of physiological variables in a group of national and international young distance runners. Sixteen (8 male, 8 female) participants (16.7 ± 1.4 years) performed a submaximal incremental running assessment followed by a maximal running test, on two occasions separated by no more than seven days. Maximal oxygen uptake (V̇O2max), speed at V̇O2max (km h(-1)), running economy and speed and heart rate (HR) at fixed blood lactate concentrations were determined. V̇O2max and running economy were scaled for differences in body mass using a power exponent derived from a larger cohort of young runners (n = 42). Running economy was expressed as oxygen cost and energy cost at the speed associated with lactate turnpoint (LTP) and the two speeds prior to LTP. Results of analysis of variance revealed an absence of systematic bias between trials. Reliability indices showed a high level of reproducibility across all parameters (typical error [TE] ≤2%; intra-class correlation coefficient >0.8; effect size <0.6). Expressing running economy as energy cost appears to provide superior reliability than using oxygen cost (TE ∼1.5% vs. ∼2%). Blood lactate and HR were liable to daily fluctuations of 0.14-0.22 mmol L(-1) and 4-5 beats min(-1) respectively. The minimum detectable change values (95% confidence) for each parameter are also reported. Exercise physiologists can be confident that measurement of important physiological determinants of distance running performance are highly reproducible in elite junior runners.
... 21,22 Overall, previous studies 7,21 have suggested that biological and technological error account for 2% to 10% of the variation in maximal, RCT, and VT variables. Lower test-retest error (1-3%) was shown for submaximal HR. 23 When obtained, TEMs in this study were expressed as a percentage (ie, coefficient of variation) and values <5% were found for all variables except for RPE (10%). Values <5% 24 have been previ- ously accepted as the criterion to declare that a variable is reliable. ...
Purpose:
The aim of this study was to determine the reliability and validity of several submaximal variables that can be easily obtained by monitoring cyclists' performance.
Methods:
Eighteen professional cyclists participated in this study. In a first part (n=15) the test-retest reliability of HR and RPE during a progressive maximal test was measured. Derived submaximal variables based on HR, RPE and power output (PO) responses were analyzed. In a second part (n=7) the pattern of the submaximal variables according to cyclists' training status was analyzed. Cyclists were assessed 3 times during the season: at the beginning of the season, before the Vuelta a España and the day after this Grand Tour.
Results:
Part 1: no significant differences in maximal and submaximal variables between test-retest were found. Excellent ICCs (0.81-0.98) were obtained in all variables. Part 2: the HR and RPE showed a rightward shift from early to peak season. In addition, RPE showed a left shift after the Vuelta a España. Submaximal variables based on RPE had the best relationship with both performance and changes in performance.
Conclusion:
The present study showed the reliability of different maximal and submaximal variables used to assess cyclists' performance. Submaximal variables based on RPE seem to be the best to monitor changes in training status over a season.
... La frecuencia cardíaca (FC), se encuentra entre las variables fisiológicas más analizadas comúnmente, debido a la disponibilidad y practicidad de los monitores de ritmo cardíaco para su valoración en deportes de equipo y a la precisión, la validez y fiabilidad en la obtención de los datos (Achten J, Jeukendrup A, 2003, Alexandre et al., 2012). Por medio de la misma se puede obtener una estimación de la intensidad relativa de ejercicio y se puede cuantificar la carga de trabajo de modo indirecto durante la actividad competitiva (Coutts et al., 2003;Duthie et al., 2003Jeukendrup, 2003;Lamberts et al., 2004). Existe una gran cantidad de estudios publicados que han analizado el comportamiento de la frecuencia cardíaca durante la competición en diferentes deportes de equipo tales como waterpolo (Smith, 1998;Botonis et al., 2015), criquet (Noakes yDurand, 2000), futbol (Reilly, 1994en Helgerud et al., 2001Helgerud et al., 2001;Eniseler 2005;Stolen et al., 2005;Alejandre et al., 2012;Castagna et al., 2009), rugby (Coutts et al., 2003;Cunniffe et al., 2009;Sparks, M., Coetzee, B., 2013), hockey sobre hierba (Lythe et al., 2011), baloncesto (Abdelfrim et al., 2010, Mongomery et al., 2010), y balonmano, (Krüger et al., 2014;Póvoas et al., 2012;Karcher y Buchheit, 2014Vittasalo et al., 1987;Dyba, 1982;Fardy et al., 1976).Millán et al., (2001)citando a varios autores, indica valores de FCpico de 183 ± 2.4 latidos/minuto (Parnat et al., 1975), 185 ± 9 latidos/minuto (Hakkinen, 1993), 192 ± 5.7 latidos/minuto (Vittasalo et al., 1987) y 155 latidos/minuto (Walker et al, 1973)Coutts et al., 2009;Aughey et al., 2011b;Boyd et al., 2011;Stein et al., 2014), rugby union (Suárez-Arrones et al., 2012;Highman et al., 2012), rugby league (Gabbett et al., 2012otros tipos de acelerómetros (Maddison et al., 2010). ...
Existe escasa evidencia reportada, en tiempo real, durante los entrenamientos y la competición, referente a las demandas fisiológicas y mecánicas (aceleraciones), que acontecen en el juego del voleibol de élite. Esta carencia es todavía aun mayor desde que se modificaron las reglas en el año 1999. La principal modificación es la introducción del líbero y la sustitución del central cuando llega a la zona defensiva por el líbero. De esta manera mientras un central está en la red (en ataque), el otro central, que fue sustituido por el líbero al llegar a la zona defensiva, se encontrará descansando. Generándose de esta manera una sustancial mejora en la capacidad de recepción y de defensa de los equipos. Esta modificación reglamentaria indujo un cambio en los aspectos tácticos y físicos del juego que devino a acciones más explosivas y de menor duración, al mismo tiempo, además, generaron una mayor especialización en los jugadores, por lo que generó un impacto en su perfil fisiológico y neuromuscular (Sheppard et al., 2009).
Gran parte de los estudios de análisis de tiempo-movimiento durante el entrenamiento y la competición se centran en la cantidad de saltos y la frecuencia con la que estos ocurren (Sheppard et al., 2009), comparados por puesto y nivel de calificación (Sheppard et al, 2007; Sheppard et al., 2009; Hasegawa et al., 2002). Por otro lado muchos estudios analizan en forma aislada la biomecánica del salto, sobre todo la técnica, la cinemática y la cinética durante la caída (Tillman et al., 2004; Bisseling y Hof, 2006; Suda et al., 2007; Cronin et al., 2008; Wagner et al., 2009; Marquez et al., 2009; Hughes et al., 2010; Hsienhand y Huang, 2012), así como su relación con mecanismos de producción de lesión (Niell et al., 2007; Bisseling et al., 2008; Janssen et al., 2013; Taylor et al., 2011; Bates et al., 2013; Kulig et al., 2015). Sin embargo, no hemos encontrado estudios que reporten la altura de los saltos durante el entrenamiento y la competición y la carga mecánica que representan los mismos en relación a los procesos de fatiga y lesión por sobreuso.
Respecto a las respuestas fisiológicas, los escasos estudios que abordan esta problemática fueron realizados con las reglas antiguas, cuando los partidos tenían una duración superior, con una carga de saltos aún mayor. Hasta la fecha, hemos encontrado un estudio que analizó la evolución de la frecuencia cardíaca durante el entrenamiento y la competición, para permitir estimar la carga del entrenamiento y obtener valores que sirvan como parámetros de control de las sesiones de entrenamiento (Berna Jimenez, 2014). Sin embargo, en este estudio, no utilizaron dispositivos que permitiesen cuantificar, a la vez, la solicitación del aparato cardiovascular y las solicitaciones mecánicas.
Existe suficiente evidencia sobre modelos subjetivos de cuantificación de la carga en deportes de equipo tales como el baloncesto (Foster et al., 2001; Anderson et al., 2003; Manzi et al., 2010, Moreira et al., 2012), fútbol (Impellizzeri et al., 2004; Little y Williams, 2007; Alexiou y Coutts, 2008; Coutts et al., 2009; Casamichana et al., 2013; Scott et al., 2013; Fanchini et al., 2015), rugby (Gabbett y Domrow, 2007; Elloumi et al., 2012; (Moreira et al., 2015) y voleibol (Berna Jimenez, 2014; Rodríguez-Marroyo et al., 2014; Freitas et al., 2014). Las herramientas de medida más utilizadas para controlar la carga del entrenamiento se basan en el registro de la frecuencia cardíaca (FC) y la percepción subjetiva del esfuerzo (RPE) . Por medio de la frecuencia cardiaca, por ejemplo, se puede establecer el denominado impulso del entrenamiento (TRIMP) (Banister, 1991), o bien cuantificar la carga en función del tiempo empleado en cada zona de intensidad (Berna Jimez, 2014).
Medios actuales más sofisticados utilizando GPS y/o acelerómetros permiten cuantificar la carga del entrenamiento a partir de las velocidades y/o aceleraciones y las distancias recorridas en franjas de velocidad o de aceleración. El GPS no es un instrumento adecuado para el control de las variables mecánicas durante el voleibol porque se juega en estadio cubierto (indoor) impidiendo la correcta señal del GPS. Sin embargo, los acelerómetros permiten cuantificar, las aceleraciones y desaceleraciones producidas durante el entrenamiento y la competición en cualquier terreno de juego.
El dispositivo comercial ZephyrTM BioharnessTM, permite monitorizar en tiempo real la carga fisiológica y mecánica del entrenamiento y la competición. Este dispositivo es relativamente nuevo y no existen trabajos publicados en la literatura científica respeto a la utilización del mismo como método de control del voleibol. Teniendo en cuenta esta carencia y el interés del estudio, parece interesante explorar la utilización del ZephyrTM como una herramienta de valoración de la carga de entrenamiento de los jugadores de voleibol.
Debido a la escasa fuente de información existente sobre las manifestaciones fisiológicas y mecánicas en el entrenamiento y la competición del voleibol, y la importancia que puede tener contar con mecanismos de control de la carga durante los entrenamientos, el objeto del presente trabajo, ha sido estudiar y comparar, las respuestas fisiológicas y mecánicas de los jugadores de voleibol masculino de elite, durante el entrenamiento y la competición, durante cuatro semanas previas a la celebración del campeonato del mundo de la categoría sub-23.
... In cases of parasympathetic type overtraining syndrome, both heart rate and plasma lactate levels may be lower at all workloads [179] . One of the most commonly published submaximal performance tests used to monitor training responses is the Heart Rate Interval Monitoring System (HIMS)[182]. The HIMS test is a submaximal shuttle running test 13 minutes in duration (consisting of 4 x 2 minute stages with progressively increasing speeds). ...
With improving professionalism of sports around the world, the volume and frequency of training required for competitive performances at the elite level has increased concurrently. With this amplification in training load comes an increased need to closely monitor the associated fatigue responses, since maximising the adaptive response to training is also reliant on avoiding the negative consequences of excessive fatigue. The rationale for the experimental chapters in this thesis was established after considering survey responses regarding current best practice for monitoring fatigue in high performance sporting environments (Chapter 3). On the basis of the results, vertical jump assessments were selected for further investigation regarding their utility in determining neuromuscular fatigue responses. Outcomes from the subsequent series of studies aimed to provide practitioners working in high performance sport with guidelines for using vertical jumps to monitor athletic fatigue.
The results from Chapter 4 indicate using the mean value of at least six jumps enhances the ability to detect small but practically important changes in performance from week to week. This study also highlighted large differences (4-6%) in morning and afternoon performance, indicating that the time of day performance is assessed needs to be accounted for when monitoring changes in jump performance. Chapter 5 explored the theory that the time of day effect observed in Chapter 4 can be explained by internal temperature differences. This theory was supported by demonstrating that an extended warm-up period can negate differences in jump performance in the morning and the afternoon. Researchers who are unable to standardise the time of day that assessment occurs are able, therefore, to control for performance differences by manipulating the warm-up protocols.
The third study examined changes in vertical jump performance over a three month training period and produced several novel outcomes. A major finding was that unloaded jumps were more sensitive to neuromuscular fatigue during intensive training than loaded jumps (Chapter 6). Furthermore, this set of results showed that all subjects changed their jump technique via a reduction in the amplitude of the countermovement when they were highly fatigued. Using the same data, an analysis was performed to quantify individual differences in within-subject variation (Chapter 7) during normal and intensive training. These results provided the first indication that within-subject variability in vertical jump performance is substantially different between individuals and between different training phases, an important consideration for interpreting the practical importance of performance changes.
In Chapter 8 the relationship between vertical jump performance and electrically elicited force of the knee extensors was examined to better understand the mechanism(s) of changes in jump performance associated with neuromuscular fatigue during intensive overload training. The results showed that the fatigue assessed by vertical jump performance was likely not only peripheral in origin as previously suggested by other authors. Further research is required to further understand the mechanisms of reduced performance during overload training, although the preliminary evidence presented implicates central mechanisms. To conclude the thesis, the findings presented in the experimental chapters are summarised, with a series of practical recommendations for using vertical jumps to monitor athletic fatigue presented.
... Individual changes in HR, depending on footwear, were estimated by defining a realistic threshold for actual changes of 1.5 times the CV, defined as the standard deviation relative to the mean (Hopkins, 2000). Lamberts and Lambert (2009) and Lamberts, Lemmnik, Durandt, and Lambert (2004) reported the lowest HR CV to be 1.4% at an intensity eliciting 85–90% HRmax. Thus, an individual relative difference of > ±2.1% was assessed as an actual change, whereas relative differences within ±2.1% were assigned to diurnal variations and therefore were treated as negligible. ...
Abstract Running shoe construction influences the forces experienced by the human body while running. The aim of this study was to ascertain whether the new sole architecture of the On running shoe reduces ground reaction forces compared with running barefoot or with a conventional running shoe and whether it changes the physiological parameters of running in shoes. Thirty-seven trained male participants were studied while running at submaximal speeds wearing their conventional running shoe, wearing the On running shoe and while barefoot. Additional biomechanical and physiological values were investigated to determine whether the On running shoe induced any changes in these parameters compared with conventional running shoes. The On exhibited similar ground reaction forces as conventional shoes, and these were different from the forces experienced while running barefoot, showing that the On was more similar to typical shoed running. No difference was observed in running economy between the On and a conventional shoe model. However, a slightly lower heart rate (HR) (≈1.3%) and blood lactate concentration (≈5.5%) were observed during submaximal running with the On running shoe compared with a conventional running shoe, as well as a greater lateral deviation of the centre of pressure mid-stance. The ramifications of the reduced HR and blood lactate concentration for competitive performance are unknown.
... A study by Brisswalter and Legros (1994) found that the day-to-day variation in heart rate under controlled, submaximal exercise conditions was 6 beats· min -1 . A more recent study by Lamberts et al (2003) also found the dayto-day heart rate variation to be about 5 to 8 beats· min -1 under controlled conditions during a submaximal test. Although the intraclass correlation coefficient (minimum heart rate during sleep) was 0.92 (95% C.I. of 0.79 – 0.98) suggesting that the measurement has " good reliability " (Vincent 1995), from a clinical perspective it is debatable whether this is sufficiently precise to detect relatively small changes in heart rate during sleep that may occur with a change in training status. ...
Resting heart rate has sometimes been used as a marker of training status. It is reasonable to assume that the relationship between heart rate and training status should be more evident during sleep when extraneous factors that may influence heart rate are reduced. Therefore the aim of the study was to assess the repeatability of monitoring heart rate during sleep when training status remained unchanged, to determine if this measurement had sufficient precision to be used as a marker of training status. The heart rate of ten female subjects was monitored for 24 hours on three occasions over three weeks whilst training status remained unchanged. Average, minimum and maximum heart rate during sleep was calculated. The average heart rate of the group during sleep was similar on each of the three tests (65 ± 9, 63 ± 6 and 67 ± 7 beats·min(-1) respectively). The range in minimum heart rate variation during sleep for all subjects over the three testing sessions was from 0 to 10 beats·min(-1) (mean = 5 ± 3 beats·min(-1)) and for maximum heart rate variation was 2 to 31 beats·min(-1) (mean = 13 ± 9 beats·min(-1)). In summary it was found that on an individual basis the minimum heart rate during sleep varied by about 8 beats·min(-1). This amount of intrinsic day-to-day variation needs to be considered when changes in heart rate that may occur with changes in training status are interpreted.
... On the contrary, significant differences were observed in resting HR values (Table 3). In the literature, it is reported that resting HR values may exhibit wide range of variation due to the various factors (Lamberts et al., 2004; Lemmink et al., 2004 ). On the other hand, similarity among peak HR values at Pre-RF, End-RF and After-RF (Table 3) demonstrated that cardiovascular stress caused by supramaximal exercise was not affected by Ramadan fasting. ...
The aim of this study was to investigate the effects of Ramadan fasting on anaerobic power and capacity and the removal rate of lactate after short time high intensity exercise in power athletes. Ten male elite power athletes (2 wrestlers, 7 sprinters and 1 thrower, aged 20-24 yr, mean age 22.30 ± 1.25 yr) participated in this study. The subjects were tested three times [3 days before the beginning of Ramadan (Pre-RF), the last 3 days of Ramadan (End-RF) and the last 3 days of the 4th week after the end of Ramadan (After-RF)]. Anaerobic power and capacity were measured by using the Wingate Anaerobic Test (WAnT) at Pre-RF, End-RF and After-RF. Capillary blood samples for lactate analyses and heart rate recordings were taken at rest, immediately after WAnT and throughout the recovery period. Repeated measures of ANOVA indicated that there were no significant changes in body weight, body mass index, fat free mass, percentage of body fat, daily sleeping time and daily caloric intake associated with Ramadan fasting. No significant changes were found in total body water either, but urinary density measured at End-RF was significantly higher than After-RF. Similarity among peak HR and peak LA values at Pre-RF, End-RF and After-RF demonstrated that cardiovascular and metabolic stress caused by WAnT was not affected by Ramadan fasting. In addition, no influence of Ramadan fasting on anaerobic power and capacity and removal rate of LA from blood following high intensity exercise was observed. The results of this study revealed that if strength-power training is performed regularly and daily food intake, body fluid balance and daily sleeping time are maintained as before Ramadan, Ramadan fasting will not have adverse effects on body composition, anaerobic power and capacity, and LA metabolism during and after high intensity exercise in power athletes.
This chapter discusses the main characteristics and challenges of the elite sports environment, derived impacts on the athlete’s body and mind, as well as implications of the training process. “Elite Sports” is a common but not well-defined phrase. In this chapter, we refer to the elite sports environment as “the top competitions in a sport (e.g., world championships/series, Olympic Games, etc.) and the training process with the purpose to compete/succeed in competition.” Main characteristics are the search for optimal, on point performance through constantly improving fitness for a specific context of top competition. This implies a high investment of energy and time over a long period. Elite sports competes globally and is in the focus of public attention. Therefore, elite sports is not just extreme in terms of extraordinary physical and mental demands imposed by the movement task but also in respect to the special social and more or less superficial environment in which it takes place. The main challenge of elite sports is to handle physical, psychological, and social stress in the right way. Utilizing it as the motor for the human adaptation capacity in the training process and promoter of optimal performance. High loads of biopsychological stress are needed to optimize fitness. The meaning of the concepts of resilience and antifragility is discussed. Foremost, it is important to balance the stress with sufficient recovery, as well as coping with and minimizing stressors, which are counteracting the adaptive process.
Firefighters are exposed to many dangerous and stressful situations when they are deployed to fight structural and wildland fires as well as rescuing victims from vehicular accidents, or other adverse events. When they are deployed, they can be exposed to physical danger as well as extreme heat and/or extreme cold due to fire and environmental conditions, thus making firefighting an extreme environment. This chapter provides an overview of the firefighter profession as an extreme environment including their clothing and equipment, the specific impacts on the human body, and the impact of biological sex and gender together with training and fitness approaches. This situational context information is important in order to understand this profession and the opportunities for engineering and information technology solutions for health, wellness, resilience, and adaption within this population.
Purpose
The purpose of this study was to compare heart rate (HR) and heart rate variability in young endurance athletes during nocturnal sleep and in the morning; and to assess whether changes in these values are associated with changes in submaximal running (SRT) and counter-movement jump (CMJ) performance.
Methods
During a three-week period of similar training, eleven athletes (16 ± 1 years) determined daily HR and heart rate variability (RMSSD) during sleep utilizing a ballistocardiographic device (Emfit QS), as well as in the morning with a HR monitor (Polar V800). Aerobic fitness and power production were assessed employing SRT and CMJ test.
Results
Comparison of the average values for week 1 and week 3 revealed no significant differences with respect to nocturnal RMSSD (6.8%, P = 0.344), morning RMSSD (13.4%, P = 0.151), morning HR (-3.9 bpm, P = 0.063), SRT HR (-0.7 bpm, P = 0.447), SRT blood lactate (4.9%, P = 0.781), CMJ (-4.2%, P = 0.122) or training volume (16%, P = 0.499). There was a strong correlation between morning and nocturnal HRs during week 1 (r = 0.800, P = 0.003) and week 3 (r = 0.815, P = 0.002), as well as between morning and nocturnal RMSSD values (for week 1, r = 0.895, P<0.001 and week 3, r = 0.878, P = 0.001).
Conclusion
This study concluded that HR and RMSSD obtained during nocturnal sleep and in the morning did not differ significantly. In addition, weekly changes in training and performance were small indicating that fitness was similar throughout the 3-week period of observation. Consequently, daily measurement of HR indices during nocturnal sleep provide a potential tool for long-term monitoring of young endurance athletes.
The analysis of the heart rate variability (HRV) consists of changes in the time intervals between consecutive R waves. It provides information on the autonomic nervous system regulation and it is a predictor of adverse cardiovascular events. Several studies analyzed this parameter in youth and adults with Intellectual Disability (ID). Nevertheless, there is a lack of information regarding the HRV before, during, and after exercise in older adults with ID. Therefore, we aimed to describe and compare the cardiac autonomic modulation before, during, and after the six-minute walk test (6MWT) in older adults with and without ID. Twenty-four volunteers with ID and 24 without ID (non-ID) participated in this study. HRV was assessed by R-R intervals at rest, during and after the 6MWT. At rest and recovery periods, the participants remained sited. The symbolic analysis was used to evaluate non-linear HRV components. The recovery HR kinetics was assessed by the mean response time, which is equivalent to time constant (τ)+time delay (TD). Between groups differences in HRV variables were not significant. During the recovery period, HR kinetics time variables showed significant better results in non-ID participants (TD: 6±5s vs. 15±11s; τ: 19±10s vs. 35±17s; and MRT: 25±9s vs. 50±11s, all p <0.050). In conclusion, our results suggest that the HRV in older adults with and without ID is similar during rest, exercise, and recovery. Recovery HR kinetics after the 6MWT was slower in older adults with ID. The reason for these results may be a reduced post-exercise vagal rebound in older adults with ID.
The aims of the current study were to examine the relationships between heart rate variability (HRV), salivary cortisol, sleep duration and training in young athletes. Eight athletes (16 ± 1 years) were monitored for 7 weeks during training and competition seasons. Subjects were training for endurance-based winter sports (cross-country skiing and biathlon). Training was divided into two zones (K1, easy training and K2, hard training). Heart rate and blood lactate during submaximal running tests (SRT), as well as cortisol, sleep duration and nocturnal HRV (RMSSD), were determined every other week. HRV and cortisol levels were correlated throughout the 7-week period (r = -0.552, P = 0.01), with the strongest correlation during week 7 (r = -0.879, P = 0.01). The relative changes in K1 and HRV showed a positive correlation from weeks 1-3 (r = 0.863, P = 0.006) and a negative correlation during weeks 3-5 (r = -0.760, P = 0.029). The relative change in sleep during weeks 1-3 were negatively correlated with cortisol (r = -0.762, P = 0.028) and K2 (r = -0.762, P = 0.028). In conclusion, HRV appears to reflect the recovery of young athletes during high loads of physical and/or physiological stress. Cortisol levels also reflected this recovery, but significant change required a longer period than HRV, suggesting that cortisol may be less sensitive to stress than HRV. Moreover, our results indicated that during the competition season, recovery for young endurance athletes increased in duration and additional sleep may be beneficial.
Chest bands have been the most used device to monitor heart rate during running. However, some runners feel uncomfortable with the use of bands due to the friction and pressure exerted on the chest. Thus, the aim of this study was to determine if the photoplethysmography (PPG) system Polar Precision Prime used in the Polar Vantage M watch could replace chest bands (Polar V800-H10) to monitor heart rate with the same precision. A group of 37 people, middle-distance and long-distance professional runners, participated in this study. The submaximal speed was determined using 50% of the participants' maximum speed in the height of their season. The Polar Vantage M reported high correlation (r. 0.84) and high ICC (ICC. 0.86) when comparing its heart rate monitor with the Polar V800 synchronised with H10 chest strap during recording intervals of more than 2 min. The systematic bias and random error were very small (\ 1 bpm), especially for the 600 s recording interval (0.26 6 5.10 bpm). Nevertheless, the error increased for 10 s (25.13 6 9.20 bpm), 20 s (28.65 6 12.60 bpm) and 30 s (210.71 6 14.99 bpm) time intervals. In conclusion, the PPG Polar Precision Prime included in the Polar Vantage M demonstrates that it could be a valid alternative to chest bands for monitoring heart rate while running, taking into account some usage considerations, good strap adjustment and an initial calibration time during the first 2-3 min.
Die Ausdauer und das Ausdauertraining sind aus Sicht des Energiestoffwechsels und des kardiopulmonalen Systems für den Leistungs- und Gesundheitssport von höchster Bedeutung. Das Kapitel liefert einen Überblick über die Bedeutung und Erscheinungsformen der Ausdauer und über ausgewählte biologische Grundlagen zum Verständnis des Ausdauertrainings. Hierbei wird speziell dem Energiestoffwechsel und der Substratverwertung (Kohlenhydrat- und Fettstoffwechsel) bei verschiedenen Ausdauerbelastungen viel Aufmerksamkeit gewidmet. Ausdauertraining bewirkt auf verschiedenen Funktionsebenen zahlreiche Anpassungsvorgänge. Diese beziehen sich auf das kardiopulmonale System, den Energie- und Fettstoffwechsel sowie auf mitochondriale, zirkulatorische und hämatologische Anpassungen. Auch den genetischen Ursachen unter anderem für die Überlegenheit der afrikanischen Langstreckenläufer wird ein spezielles Teilkapitel gewidmet. Für die Sportpraxis werden die typischen Ausdauertrainingsmethoden und die Möglichkeiten der Belastungsdosierung beschrieben. Dabei wird speziell der Trainingssteuerung mittels Herzfrequenz und den zugrunde liegenden Formeln detaillierte Aufmerksamkeit geschenkt. Konkrete Trainingsbeispiele runden das Kapitel ab.
https://www.rug.nl/research/portal/publications/monitoring-endurance-athletes(485ae435-aacb-47b7-afc1-61c2a3324f0a).html
Endurance athletes seek for the optimal balance in training stress and recovery so they can perform at their best and avoid injuries. The PhD thesis of Ruby Otter at the School of Sport Studies (Hanze University of Applied Sciences) and the Center of Human Movement Sciences (UMCG, University of Groningen) showed that not only physical stress and recovery, but also psychosocial stress and recovery influence performance and injury risk of endurance athletes. During the research project, 115 endurance athletes have been monitored for two years. The athletes kept a daily training log including information about any injuries. Every 1 to 3 weeks the athletes filled out a psychosocial stress and recovery questionnaire and they came into the SportsFieldLab Groningen to perform exercise tests every 6 weeks. Results showed that an increase in stress and a decrease in recovery are associated to decreased performance parameters. An unplanned negative life event disturbed perceived psychosocial stress and recovery over a relatively short period and it impaired performance parameters of runners. In addition, the risk of sustaining an injury increased after increased relative training loads (physical stress). Finally, a new submaximal rowing test has shown to be reliable and practical for predicting maximal performance of rowers. The findings in this thesis support the notion that psychosocial as well as physical stress and recovery play a role in performance changes of endurance athletes. Athletes and coaches could benefit from monitoring physical and psychosocial factors so that training programs can be adapted for each individual.
هدف از مطالعه حاضر بررسی تغییرات روزانه شاخص های ضربان قلب در یک آزمون زیر بیشینه پله بود. 20 بازیکن فوتبال جوان با میانگین سنی (6/ 17سال) بطور داوطلبانه در پژوهش حاضر شرکت کردند. آزمودنی ها پس از شرکت در یک جلسه آشنایی، در چهار روز متعاقب در آزمایشگاه حاضر شدند. در هر جلسه آزمودنی ها در آزمون پله 3 دقیقه ای با آهنگ 96 ضربه در دقیقه شرکت کرده و بلافاصله 2 دقیقه پس از اتمام آزمون بطور غیر فعال برای اندازه گیری شاخص های بازفعالی پاراسمپاتیکی ضربان قلب استراحت می کردند. در کل زمان آزمون فواصل R-R ضربان قلب توسط سینه بند بلوتوث دار پلار (H7، ساخت کشور فنلاند) ارسال و توسط اپلیکیشن Elite HRV ثبت می شد. مقادیر ضربان قلب تمرین (HRex) در 30، 60 و 180 ثانیه ای آزمون، ضربان قلب بازگشت به حالت اولیه ((HRR 60 و 120 ثانیه ای و همینطور لگاریتم طبیعی ریشه میانگین مجموع مربعات اختلاف بین موج های R ضربان قلب (Ln rMSSD) 60 و 120 ثانیه پس از تمرین به عنوان شاخص تغییر پذیری ضربان قلب (HRV) با استفاده از نرم افزار Kubios محاسبه گردید. از تجزیه و تحلیل آماری پیشرفته علوم ورزشی استفاده شده و خطای معیار (TE)، ضریب تغییر (CV) و همینطور ضریب همبستگی درون کلاسی (ICC) برای هر شاخص بطور جداگانه محاسبه گردید. نتایج نشان داد کمترین TE و CV و همینطور بالاترین ICC مربوط به HRex بود ( به ترتیب 0.42، 1.3 و 0.84). در شاخص های بازفعالی پاراسمپاتیکی ضربان قلب نیز Ln rMSSD نسبت به HRR پایایی بیشتری داشت. به نظر می رسد در پایش ورزشکاران با آزمون پله، HRex و پس از آن Ln rMSSD با ثبات ترین اندازه های ضربان قلب باشند. مقادیر CV ارائه شده هر شاخص در این مقاله کابردهایی برای پایش و حذف نویز طبیعی آن ها ارائه می دهد.
The study had the following objectives: to create a scale of the subjective perception of the muscle soreness for volleyball players, validate this scale for volleyball players and check the reliability of this instrument in this sample. The research was composed by a women`s team under 16 and under 14, a male team under 14 of a same club of Curitiba that competed the 2nd stage of the Grand Prix 2015. The scale of muscle soreness for the volleyball was developed from some contents of the subjective perception exertion scale, muscle soreness scales and of the chronic pain scales. The muscle soreness of the volleyball scale has five faces with the following classification: 0 is without muscle soreness, 1 is light muscle soreness, 2 is medium muscle soreness, 3 is strong muscle soreness and 4 is maximum muscle soreness. The muscle soreness scale of the volleyball was validated with a muscle soreness scale of seven points at several moments of the competition. The reliability was conducted in scale of the study at different times during the championship. The validity of the scale for the women`s team under 16 was very high (R = 0,90 to 0,99) to high (R = 0,84 to 0,89). While the validity of the scale for the team under 14 female and male was very high (R = 0,90) to moderate (R = 0,79). The reliability of the muscle soreness scale of the volleyball was good (r = 0,75 to 0,80) to excellent (r = 0,90). But the Kappa test identified a moderate agreement (k = 0,42 and 0,56) and the Bland and Altman method the predominant agreement was lower medium agreement. In conclusion, the muscle soreness scale of the volleyball deserves others studies to check the validity and reliability of this instrument.
Accurate assessment of training load (TL) and training load responses (TLR) might be useful for an optimized training regulation and prevention of overtraining. No consensus on a gold-standard for measuring TL or intensity in endurance sports has been reported in the available literature so far. The aim of the present article is i) to identify feasible parameters to measure TL and TLR in daily training and ii) to compare these scientific approaches with the needs of elite endurance coaches. Therefore, the first part provides a systematic review of the current literature and the second part concentrates on the results of a questionnaire that assessed the coaches' requirements for monitoring daily endurance training. The systematic review revealed that the combination of both quantitative and qualitative data seems most promising to evaluate TL and TLR. Thus, validated questionnaires or rating of perceived exertion (RPE), combined with physiological parameters, such as heart rate, are often used and seem to provide the most reliable results. From the coaches' perspective, duration and kind of training, RPE, as well as personal remarks in the athletes' training diaries are considered to be essential information. Further, the coaches favor a feasible system that collects large amounts of directly measurable and perceived data and that is able to learn from previous events in order to present the most important information in a short individual overview. When comparing both parts of the present study, it becomes clear that the scientific research cannot yet fully respond to the coaches' requests, however, based on the coaches' propositions, scientific research might be stimulated to tackle this challenge in the near future.
Control of the treadmill speed automatically with respect to the person’s heart rate is mainly useful for the rehabilitation/secondary prevention program of the heart patients. Antecedents of cardiovascular disease or heart disease should begin in the early life, making primary prevention efforts necessary from childhood. Thus, it has increased the emphasis on preventing atherosclerosis by modifying the risk factors. Variation of the heart rate of the person is used for changing the motor speed of the treadmill. Since the exercising of the body causes adverse effect on the heart rate, it is important to control the speed of the treadmill to reduce the stress on the person. The different ranges of the possible heart rates are set in the system. The voltage and speed is set differently according to the heart rate range. A Permanent magnet DC motor is used for controlling the speed of treadmill. MOSFET regulates the voltage given to the motor according to the pulse width modulated output. Pulse width modulated output changes with the variation of the heart rate which regulates the on-off time of the MOSFET. A 230 v AC supply is filtered and rectified for the working of the motor. Pulsated DC produced by the MOSFET enables the smooth control over the voltage. Model based simulation is used for showing the execution of the proposed system.
This work investigated the suitability of a new tool for decision support in training programs of high performance athletes. The aim of this study was to find a reliable and robust measure of the fitness of an athlete for use as a tool for adjusting training schedules. We examined the use of heart rate recovery percentage (HRr%) for this purpose, using a two-phased approach. Phase 1 consisted of testing the suitability of HRr% as a measure of aerobic fitness, using a modified running test specifically designed for highperformance team running sports such as football. Phase 2 was conducted over a 12-week training program with two different training loads. HRr% measured aerobic fitness and a running time-trial measured performance. Consecutive measures of HRr% during phase 1 indicated a Pearson's r of 0.92, suggesting a robust measure of aerobic fitness. During phase 2, HRr% reflected the training load and significantly increased when the training load was reduced between weeks 4 to 5. This work shows that HRr% is a robust indicator of aerobic fitness and provides an on-the-spot index that is useful for training load adjustment of eliteperformance athletes.
OBJETIVE: The purpose of this study was to assess the acute effects of different stretching protocols
on the ability of vertical jump and sprint 20 meters in a selected soccer team from the University San
Sebastian in the city of Puerto Montt. METHODS: Quasi-experimental study. 24 selected soccer
players were assigned into three groups: Dynamic Stretch (DS) (n = 8), Static Stretching (SS) (n = 8)
and no stretch (NS) (n = 8). After each group performed their respective stretching protocol, the
following criteria were evaluated: Vertical jump and sprint 20 meters by jumping platform.
RESULTS: According to ANOVA, a significant improvement in vertical jumping using protocols DS
above protocols in SS and NS; in Flight time (p = 0.046) and takeoff speed (p = 0.045) after the DS for
about SS height (p = 0.049) after the DS on the SS. Kruskal-Wallis test indicated significant
differences between the various protocols sprint after stretching (p= 0,006), the NS increase running
speed expressed in less travel time (2.58 sec) with respect to DS (2 , 99 sec) and SS (3.23 sec).
CONCLUSION: The acute effect of DS is more effective in the vertical jumping ability than the
protocol of SS and NS, but the results obtained after the sprint, indicates that NS is even a better
protocol to use than DS or SS
Physical and psychosocial stress and recovery are important performance determinants. A holistic approach that monitors these performance determinants over a longer period of time is lacking. Therefore this study aims to investigate the effect of a player's physical and psychosocial stress and recovery on field-test performance. In a prospective non-experimental cohort design 10 female Dutch floorball players were monitored over 6 months. To monitor physical and psychosocial stress and recovery, daily training-logs and 3-weekly the Recovery-Stress Questionnaire for Athletes (RESTQ-Sport) were filled out respectively. To determine field-test performance 6 Heart rate Interval Monitoring System (HIMS) and 4 Repeated Modified Agility T-test (RMAT) measurements were performed. Multilevel prediction models were applied to account for within-players and between-players field-test performance changes. The results show that more psychosocial stress and less psychosocial recovery over 3-6 weeks before testing decrease HIMS performance (p≤0.05). More physical stress over 6 weeks before testing improves RMAT performance (p≤0.05). In conclusion, physical and psychosocial stress and recovery affect submaximal interval-based running performance and agility up to 6 weeks before testing. Therefore both physical and psychosocial stress and recovery should be monitored in daily routines to optimize performance.
© Georg Thieme Verlag KG Stuttgart · New York.
The purpose of this study was to assess predictive value of a new Submaximal Rowing Test (SmRT) on 2000 m ergometer rowing time-trial performance in competitive rowers. In addition, the reliability of the SmRT was investigated. Twenty-four competitive male rowers participated in this study. After determining individual HRmax, all rowers performed a SmRT followed by a 2000 m rowing ergometer time-trial. In addition, the SmRT was performed 4 times (2 days in between) in order to determine the reliability. The SmRT consists of two six-minute stages of rowing at 70 and 80% HRmax, followed by a three-minute stage at 90% HRmax. Power was captured during the three stages and 60 seconds of heart rate recovery (HRR60s) was measured directly after the third stage. Results show that predictive value of power during the SmRT on 2000 m rowing time also increases with stages. CVTEE% is 2.4%, 1.9% and 1.3%. Pearson correlations (CI) are -0.73 (-0.88 - -0.45), -0.80 (-0.94 - -0.67) and -0.93 (-0.97 - -0.84). 2000 m rowing time and HRR60s show no relationship. Reliability of power during the SmRT increases with stages. The Coefficient of Variation (CVTEM%) is 9.2%, 5.6% and 0.4%. Intra-class Correlation Coefficients (ICC) and Confidence Intervals (CI) are 0.91 (0.78 - 0.97), 0.92 (0.81 - 0.97) and 0.99 (0.97 - 1.00). The CVTEM% and ICC of HRR60s is 8.1% and 0.93 (0.82 - 0.98). In conclusion, the data of this study show that the SmRT is a reliable test that is able to accurately predict 2000 rowing time on an ergometer. The SmRT showed to be a practical and valuable monitoring tool for rowers and potentially can assist in fine-tuning and optimizing training prescription in rowers.
The reliability of the interval shuttle run test (ISRT) as a submaximal and maximal field test to measure intermittent endurance capacity was examined. During the ISRT, participants alternately run for 30 seconds and walk for 15 seconds. The running speed is increased from 10 km[middle dot]h-1 every 90 seconds until exhaustion. Within a 2-week period, 17 intermittent sport players (i.e., 10 men and 7 women) performed the ISRT twice in a sports hall under well-standardized conditions. Heart rates per speed and total number of runs were assessed as submaximal and maximal performance measures. With the exception of the heart rates at 10.0 km[middle dot]h-1 for men and 10.0, 12.0, and 13.5 km[middle dot]h-1 for women, zero lay within the 95% confidence interval of the mean differences, indicating that no bias existed between the outcome measures at the 2 test sessions (absolute reliability). The results illustrate that it is important to control for heart rate before the start of the ISRT. Relative reliability was high (intraclass correlation coefficient >= 0.86). We conclude that the reliability of the ISRT as a submaximal and maximal field test for intermittent sport players is supported by the results.
Objective:
To develop a new predictive model of maximal heart rate based on two walking tests at different speeds (comfortable and brisk walking) as an alternative to a cardiopulmonary exercise test during cardiac rehabilitation.
Design:
Evaluation of a clinical assessment tool.
Setting:
A Cardiac Rehabilitation Department in France.
Subjects:
A total of 148 patients (133 men), mean age of 59 ±9 years, at the end of an outpatient cardiac rehabilitation programme.
Main measures:
Patients successively performed a 6-minute walk test, a 200 m fast-walk test (200mFWT), and a cardiopulmonary exercise test, with measure of heart rate at the end of each test. An all-possible regression procedure was used to determine the best predictive regression models of maximal heart rate. The best model was compared with the Fox equation in term of predictive error of maximal heart rate using the paired t-test.
Results:
Results of the two walking tests correlated significantly with maximal heart rate determined during the cardiopulmonary exercise test, whereas anthropometric parameters and resting heart rate did not. The simplified predictive model with the most acceptable mean error was: maximal heart rate = 130 - 0.6 × age + 0.3 × HR200mFWT (R(2) = 0.24). This model was superior to the Fox formula (R(2) = 0.138). The relationship between training target heart rate calculated from measured reserve heart rate and that established using this predictive model was statistically significant (r = 0.528, p < 10(-6)).
Conclusions:
A formula combining heart rate measured during a safe simple fast walk test and age is more efficient than an equation only including age to predict maximal heart rate and training target heart rate.
The purpose of this study was to examine the heart rate recovery depending on anaerobic running. A total of 23 professional soccer players who were player of Turkish Super Leagues, were examined. Anaerobic Run test was applied to the soccer players and their heart rates were recorded before running, just after running, in 3rd and 6th minutes of recovery period. Any statistical differences were not found between the heart rates before run and in 6th minute after run (p > 0.05). On the other hand, there was a statistical difference between the heart rates before run, after run and in 3rd minute after run; the heart rates after run and before run; the heart rates in 3rd and 6th minutes of recovery (p < 0.05). A relationship was determined between the heart rates after run, before run (r = 0.457) and in 3rd minute of recovery (r = 0.537) and the heart rates in 3rd and 6th minutes of recovery (r = 0.629). On the other hand, no relation was found between the heart rates before run, in 3rd minute recovery (r = 0.247) and in 6th minute of recovery (r = -0.004) and the heart rates just after run and in 6th minute of recovery (r = 0.280) (p > 0.05). In conclusion, even if the increase of heart rate occurring after anaerobic run doesn't completely return to normal in 3rd minute of recovery, it will supply the athlete with a suitable condition for the second loading with regard to efficient rest. It is thought that a rest over 3 minutes should be given for athletes to make the heart rate after anaerobic run return to normal.
Measures of resting, exercise, and recovery heart rate are receiving increasing interest for monitoring fatigue, fitness and endurance performance responses, which has direct implications for adjusting training load (1) daily during specific training blocks and (2) throughout the competitive season. However, these measures are still not widely implemented to monitor athletes' responses to training load, probably because of apparent contradictory findings in the literature. In this review I contend that most of the contradictory findings are related to methodological inconsistencies and/or misinterpretation of the data rather than to limitations of heart rate measures to accurately inform on training status. I also provide evidence that measures derived from 5-min (almost daily) recordings of resting (indices capturing beat-to-beat changes in heart rate, reflecting cardiac parasympathetic activity) and submaximal exercise (30- to 60-s average) heart rate are likely the most useful monitoring tools. For appropriate interpretation at the individual level, changes in a given measure should be interpreted by taking into account the error of measurement and the smallest important change of the measure, as well as the training context (training phase, load, and intensity distribution). The decision to use a given measure should be based upon the level of information that is required by the athlete, the marker's sensitivity to changes in training status and the practical constrains required for the measurements. However, measures of heart rate cannot inform on all aspects of wellness, fatigue, and performance, so their use in combination with daily training logs, psychometric questionnaires and non-invasive, cost-effective performance tests such as a countermovement jump may offer a complete solution to monitor training status in athletes participating in aerobic-oriented sports.
The Bioharness™ device is designed for monitoring physiological variables in free-living situations but has only been proven to be reliable and valid in a laboratory environment. Therefore, this study aimed to determine the reliability and validity of the Bioharness™ using a field based protocol. Twenty healthy males participated. Heart rate (HR), breathing frequency (BF) and accelerometry (ACC) were assessed by simultaneous measurement of two Bioharness™ devices and a test-retest of a discontinuous incremental walk-jog-run protocol (4 - 11 km·h(-1)) completed in a sports hall. Adopted precision of measurement devices were; HR: Polar T31 (Polar Electro), BF: Spirometer (Cortex Metalyser), ACC: Oxygen expenditure (Cortex Metalyser). For all data, precision of measurement reported good relationships (r = 0.61 to 0.67, p < 0.01) and large Limits of Agreement for HR (>79.2 b·min(-1)) and BF (>54.7 br·min(-1)). ACC presented excellent precision (r = 0.94, p < 0.01). Results for HR (r= ~0.91, p < 0.01: CV <7.6) and ACC (r > 0.97, p < 0.01; CV <14.7) suggested these variables are reliable. BF presented more variable data (r = 0.46-0.61, p < 0.01; CV < 23.7). As velocity of movement increased (>8 km·h(-1)) data became more erroneous. A data cleaning protocol removed gross errors in the data analysis and subsequent reliability and validity statistics improved across all variables. In conclusion, the Bioharness™ HR and ACC variables have demonstrated reliability and validity in a field setting, though data collected at higher velocities should be treated with caution. Measuring human physiological responses in a field based environment allows for more ecologically valid data to be collected and devices such as the Bioharness™ could be used by exercise professionals to begin to further investigate this area.
Abstract The aim of this study was to assess the validity of the heart rate formula 170 - 0.5 age ± 10 used to prescribe endurance training for healthy sedentary or moderately trained individuals. A total of 795 incremental tests of women and men during running and cycling were analysed. The maximum heart rate, heart rate at deflection and age-dependent declines of these heart rates were determined. The maximum heart rate and the heart rate at deflection were greater during running (women: 192 ± 10 and 181 ± 9 bpm; men: 191 ± 10 and 179 ± 10 bpm) than cycling (women: 185 ± 11 and 170 ± 11 bpm; men: 187 ± 10 and 169 ± 11 bpm, P < 0.001) without any sex-based difference. With the upper limit of the existing heart rate formula, 4% during running and 35% during cycling exceeded the heart rate at deflection. We suggest two heart rate formulae for healthy sedentary or moderately endurance trained individuals separated for mode of exercise but not for sex: 165 - 0.5 age ± 5 for running and 160 - 0.5 age ± 5 for cycling.
This study assessed the longer-term (12-month) variability in post-exercise heart rate recovery following a submaximal exercise test. Longitudinal data was analysed for 97 healthy middle-aged adults (74 male, 23 female) from 2 occasions, 12 months apart. Participants were retrospectively selected if they had stable physical activity habits, submaximal treadmill fitness and anthropometric measurements between the 2 assessment visits. A submaximal Bruce treadmill test was performed to at least 85% age-predicted maximum heart rate. Absolute heart rate and Δ heart rate recovery (change from peak exercise heart rate) were recorded for 1 and 2 min post-exercise in an immediate supine position. Heart rate recovery at both time-points was shown to be reliable with intra-class correlation coefficient values≥0.714. Absolute heart rate 1-min post-exercise showed the strongest agreement between repeat tests (r=0.867, P<0.001). Lower coefficient of variation (≤ 10.2%) and narrower limits of agreement were found for actual heart rate values rather than Δ heart rate recovery, and for 1-min rather than 2-min post-exercise recovery time points. Log-transformed values generated better variability with acceptable coefficient of variation for all measures (2.2-10%). Overall, 1 min post-exercise heart rate recovery data had least variability over the 12-month period in apparently healthy middle-aged adults.
Entraînement Organe sacré pour les Aztèques et les Egyptiens, siège des émotions pour les romantiques, le coeur laisse rarement indifférent (1) et les sportifs ne font pas exception. Le coeur d'athlète focalise le débat sur la relation risque/bénéfice de l'activité physique, de l'entraînement spor-tif et de la compétition, depuis la Grèce Antique (2). Le stéthoscope de Laënnec, en 1816, le galvanomètre à fil d'Einthoven, en 1901, les Holters numériques et autres systèmes d'image-rie par résonnance magnétique, de nos jours, nous ont permis, petit à petit, de percer les secrets de son fonctionnement. Dans le milieu sportif, la date qui fait référence est plutôt 1983. La société Polar commercialise le premier cardiofréquencemètre sans fil qui permet de stocker et de transférer les enregistrements de fréquence cardiaque (3). Avec le Sport Test PE 2000 (Polar ® , Kempele ® , Finlande ®), et toutes les évolutions qui ont suivi, on ne lirait plus seulement l'heure sur sa montre, l'on verrait aussi s'afficher les battements du coeur. Une révolution qui a mar-qué aussi bien les pratiques d'entraînement que le marché sportif. La fréquence cardiaque est-elle le garde-fou des intensités d'exercice ? Entre arguments commerciaux et réalité physiologique, cet article fait le point.
Heart-rate recovery (HRR) has been proposed as a marker of autonomic function and training status in athletes. The authors performed a systematic review of studies that examined HRR after training. Five cross-sectional studies and 8 studies investigating changes over time (longitudinal) met our criteria. Three out of 5 cross-sectional studies observed a faster HRR in trained compared with untrained subjects, while 2 articles showed no change as a result of training. Most longitudinal studies observed a corresponding increase in HRR and power output (training status). Although confounding factors such as age, ambient temperature, and the intensity and duration of the exercise period preceding HRR make it difficult to compare these studies, the available studies indicated that HRR was related to training status. Therefore, the authors conclude that HRR has the potential to become a valuable tool to monitor changes in training status in athletes and less well-trained subjects, but more studies and better standardization are required to match this potential.
Success in sport at the elite level is dependent on, (i) athletes coinciding their peak fitness with important competitions; and (ii) at the same time remaining physically and mentally healthy and free of injury. The athlete has a better chance of achieving these goals if the support staff (coaching, medical and scientific staff) implement a well-constructed programme of gathering objective and subjective data from the athlete. This programme should include screening for the risk of injury and ill health and testing for fitness and sport-specific parameters that are associated with physical performance. Training intensity and the subjective response to each session should also be included in the monitoring programme. For endurance sports, training status can also be monitored via measurement of the physiological response to a constant submaximal workload. For the testing programme to be valid, the following criteria have to be fulfilled: 1) the tests should be reliable and valid; 2) the typical error of measurement of each test should be determined so that the results can be interpreted correctly; 3) the testing programme should be designed to answer specific questions relevant to the unique demands of training and preparation for a particular sport; and 4) results must be communicated clearly to the athlete and coach with particular emphasis on the practical application of the data.
The purpose of this study was to quantify total intraindividual variability in energy cost of running (C), ventilation (VE), respiratory frequency (RF), heart rate (HR), lactate concentration (La) and stride rate (SR) at usual training pace in French elite middle distance runners. Subjects were monitored four times a week during submaximal treadmill tests at 75% VO2max speed (15.8 +/- .02 km.h-1). No significant differences (p > .05) were found between tests in C, VE, RF, HR, SR. Significant day to day differences were found in La (0.5 +/- 0.3, p < .025). However, a wide range of individual coefficients of variation were observed for C (0.2-10.6), VE (0.9-8.8) and RF (0.7-9.3). SR appears to be the most stable parameter (0.2-2.6). No correlation was found between these individual variations. These results suggest that in well-trained runners C, VE, RF, HR and SR are stable measures for assessing the efficacy of procedures aimed at improving the energy cost of running. For the speed used in testing, the respiratory parameters and energy cost of running presented a wide range of individual variation whereas stride rate appeared to be a very stable measure.
The objectives of the study were to determine: (1) daily energy expenditure (EE) of athletic and non-athletic adolescents of both sexes in free-living conditions; (2) day-to-day variations in daily EE during 1 week; (3) energy costs of the main activities; and (4) the effect of usual activity on EE during sleep, seated and miscellaneous activities. Fifty adolescents (four groups of eleven to fifteen boys or girls aged 16-19 years) participated in the study. Body composition was measured by the skinfold-thickness method, and VO2max and external mechanical power (EMP) by a direct method (respiratory gas exchanges) on a cycloergometer. Daily EE and partial EE in free-living conditions were computed from heart-rate (HR) recordings during seven consecutive days using individual prediction equations established from the data obtained during a 24 h period spent in whole-body calorimeters with similar activities. Fat-free mass (FFM), VO2max, EMP, daily EE and EE during sleep were significantly higher in athletic than in non-athletic subjects. After adjustment for FFM, VO2max, EMP, daily EE and EE during exercise were still higher in athletic than in non-athletic adolescents (P < 0.001). However, adjusted sleeping EE was not significantly different between athletic and non-athletic adolescents. Increases in exercise EE were partly compensated for by significant reductions in EE during schoolwork and miscellaneous activities. Thus, the differences in daily EE between athletic and non-athletic subjects resulted mainly from increases in FFM and EE during exercise (duration and energy cost).
Research into the physiology of exercise and kinanthropometry is intended to improve our understanding of how the body responds and adapts to exercise. If such studies are to be meaningful, they have to be well designed and analysed. Advances in personal computing have made available statistical analyses that were previously the preserve of elaborate mainframe systems and have increased opportunities for investigation. However, the ease with which analyses can be performed can mask underlying philosophical and epistemological shortcomings. The aim of this review is to examine the use of four techniques that are especially relevant to physiological studies: (1) bivariate correlation and linear and non-linear regression, (2) multiple regression, (3) repeated-measures analysis of variance and (4) multi-level modelling. The importance of adhering to underlying statistical assumptions is emphasized and ways to accommodate violations of these assumptions are identified.
The purpose of physiological testing (J.D. MacDougall and H.A. Wenger) what do tests measure? (H.J. Green) testing strength and power (D.G. Sale) testing aerobic power (J.S. Thoden) testing anaerobic power and capacity (C. Bouchard, Albert W. Taylor, Jean-Aime Simoneau, and Serge Dulac) Kknanthropometry (WD. Ross and M.J. Marfell-Jones) testing flexibility (C.L. Hubley-Kozey) evaluating the health status of the athlete (R. Backus and D.C. Reid) modelling elite athletic performance (E.W. Banister).
Heart rate monitors are used widely by scientists, coaches and sports participants to monitor heart rate during physical activity. Although there are data that show that heart rate monitors measure heart rate accurately during a range of physical activities, there is less consensus on the interpretation of heart rate data. The day-to-day variation in heart rate under controlled submaximal exercise conditions is approximately 6 beats min(-1), which is generally less than the decrease in the submaximal heart rate that results from endurance training. A bout of exercise that causes moderate dehydration can affect heart rate during submaximal exercise. It has been estimated that, for every 1% loss in body weight due to dehydration, heart rate increases by 7 beats min(-1). During a 10-km race, the heart rate is approximately 20 beats min(-1) higher at racing pace compared to the heart rate at the same running speed under non-competitive conditions. In conclusion, heart rate monitors measure heart rate accurately under diverse conditions, and have the potential to be regarded as 'ergogenic aids'. However, further scientific studies are needed before the heart rate data can be interpreted accurately and used to improve long-distance running performance.
In little over a decade, lightweight radiotelemetric equipment has been designed and developed which measures heart rate accurately under free-living conditions. The rate of refinement of the heart rate monitor technology has far exceeded the rate at which the understanding of heart rate during exercise has improved. This brief paper lists the problems and questions that need to be addressed to improve our understanding and application of heart rate measured during exercise to optimize exercise prescription for health and sports performance.
To obtain optimal training effects and avoid overtraining, it is necessary to monitor the intensity of training. In cycling, speed is not an accurate indicator of exercise intensity, and therefore alternatives have to be found to monitor exercise intensity during training and competition. Power output may be the most direct indicator, but heart rate is easier to monitor and measure. There are, however, limitations that have to be taken into account when using a heart rate monitor. For example, the position on the bicycle may change heart rate at a given exercise intensity. More important, however, is the increase in heart rate over time, a phenomenon described as 'cardiac drift'. Cardiac drift can change the heart rate-power output relationship drastically, especially in hot environments or at altitude. It is important to determine whether one is interested in monitoring exercise intensity per se or measuring whole-body stress. Power output may be a better indicator of the former and heart rate may, under many conditions, be a better indicator of the latter. Heart rate can be used to evaluate a cyclist after training or competition, or to determine the exercise intensity during training. Heart rate monitoring is very useful in the detection of early overtraining, especially in combination with lactate curves and questionnaires. During overtraining, maximal heart rates as well as submaximal heart rates may be decreased, while resting and, in particular, sleeping - heart rates may be increased.
Interest in rises in oxygen consumption (VO2) with increasing exercise intensity largely originate from the work of Hill and colleagues in the 1920s. Their studies led to a belief that cardiac output and VO2 'plateau' at increasing work rates and that muscle hypoxia leads to fatigue. Hence, it was assumed that the primary benefit of exercise training is to increase muscle oxidative capacity and that the greatest benefit of training would occur at work rates around the 'anaerobic threshold'. In this paper, we question whether working muscles become hypoxic at high work rates. Rather than being a threshold response to hypoxia, we propose that plasma lactate accumulation and curvilinear rises in ventilation at high work rates are both independent consequences of the acceleration of carbohydrate metabolism with increasing exercise intensity. Evidence is also presented to suggest that athletic performances are not exclusively related to muscle oxidative capacity. Once an athlete has adapted to prolonged, 'aerobic' training, intervals of 'anaerobic', high-intensity exercise further improve performance without additional increases in muscle mitochondrial density or alterations in metabolism. Until the mechanisms underlying the latter improvements in performance are understood, it is difficult to advise athletes on how best to prepare for competition.
Numerous approaches have been used to improve the science and art of exercise prescription, and particular challenges exist in the prescription of exercise intensity. Traditionally, work in the area has been the province of exercise physiologists interested in the improvement of training programmes for athletes, as opposed to the more widespread recent interest in health-related fitness and physical activity for all. The generalized approach to the provision of guidelines for exercise prescription has meant that individuals have, at best, prediction equations which provide a wide band of heart rate between which they can work to derive health benefits. This paper explores some of the commonly employed submaximal markers of exercise intensity and proposes a number of approaches for improvements beyond generalized equations.
Heart rate is a useful indicator of physiological adaptation and intensity of effort. Therefore, heart rate monitoring is an important component of cardiovascular fitness assessment and training programmes. The electrocardiogram (ECG) and Holter monitoring devices are accurate, but they are not appropriate for use in field settings due to cost, size and complexity of operation. Lightweight telemetric heart rate monitors equipped with conventional electrodes have been available since 1983 and have been shown to be accurate and valid tools for heart rate monitoring and registering in the field. Polar Electro Oy has been at the forefront of ambulatory heart rate monitor technology for 15 years. This paper reviews the development of Polar heart rate monitors and their measurement accuracy compared to Holter ECG devices at rest and during exercise, both in adults and in children.
This investigation determined the effect of different rates of dehydration, induced by ingesting different volumes of fluid during prolonged exercise, on hyperthermia, heart rate (HR), and stroke volume (SV). On four different occasions, eight endurance-trained cyclists [age 23 +/- 3 (SD) yr, body wt 71.9 +/- 11.6 kg, maximal O2 consumption 4.72 +/- 0.33 l/min] cycled at a power output equal to 62-67% maximal O2 consumption for 2 h in a warm environment (33 degrees C dry bulb, 50% relative humidity, wind speed 2.5 m/s). During exercise, they randomly received no fluid (NF) or ingested a small (SF), moderate (MF), or large (LF) volume of fluid that replaced 20 +/- 1, 48 +/- 1, and 81 +/- 2%, respectively, of the fluid lost in sweat during exercise. The protocol resulted in graded magnitudes of dehydration as body weight declined 4.2 +/- 0.1, 3.4 +/- 0.1, 2.3 +/- 0.1, and 1.1 +/- 0.1%, respectively, during NF, SF, MF, and LF. After 2 h of exercise, esophageal temperature (Tes), HR, and SV were significantly different among the four trials (P < 0.05), with the exception of NF and SF. The magnitude of dehydration accrued after 2 h of exercise in the four trials was linearly related with the increase in Tes (r = 0.98, P < 0.02), the increase in HR (r = 0.99, P < 0.01), and the decline in SV (r = 0.99, P < 0.01). LF attenuated hyperthermia, apparently because of higher skin blood flow, inasmuch as forearm blood flow was 20-22% higher than during SF and NF at 105 min (P < 0.05). There were no differences in sweat rate among the four trials. In each subject, the increase in Tes from 20 to 120 min of exercise was highly correlated to the increase in serum osmolality (r = 0.81-0.98, P < 0.02-0.19) and the increase in serum sodium concentration (r = 0.87-0.99, P < 0.01-0.13) from 5 to 120 min of exercise. In summary, the magnitude of increase in core temperature and HR and the decline in SV are graded in proportion to the amount of dehydration accrued during exercise.
Overtraining is an imbalance between training and recovery. Short term overtraining or 'over-reaching' is reversible within days to weeks. Fatigue accompanied by a number of physical and psychological symptoms in the athlete is an indication of 'staleness' or 'overtraining syndrome'. Staleness is a dysfunction of the neuroendocrine system, localised at hypothalamic level. Staleness may occur when physical and emotional stress exceeds the individual coping capacity. However, the precise mechanism has yet to be established. Clinically the syndrome can be divided into the sympathetic and parasympathetic types, based upon the predominance of sympathetic or parasympathetic activity, respectively. The syndrome and its clinical manifestation can be explained as a stress response. At present, no sensitive and specific tests are available to prevent or diagnose overtraining. The diagnosis is based on the medical history and the clinical presentation. Complete recovery may take weeks to months.
1. Skinfold thicknesses at four sites – biceps, triceps, subscapular and supra-iliac – and total body density (by underwater weighing) were measured on 209 males and 272 females aged from 16 to 72 years. The fat content varied from 5 to 50% of body-weight in the men and from 10 to 61% in the women.
2. When the results were plotted it was found necessary to use the logarithm of skinfold measurements in order to achieve a linear relationship with body density.
3. Linear regression equations were calculated for the estimation of body density, and hence body fat, using single skinfolds and all possible sums of two or more skinfolds. Separate equations for the different age-groupings are given. A table is derived where percentage body fat can be read off corresponding to differing values for the total of the four standard skinfolds. This table is subdivided for sex and for age.
4. The possible reasons for the altered position of the regression lines with sex and age, and the validation of the use of body density measurements, are discussed.
Circadian rhythms in heart rate were examined at rest, immediately pre-exercise, during submaximal and maximal exercise on a cycle ergometer, and during recovery post-exercise (N = 10). Observations were made under controlled conditions at 0300, 0900, 1500, and 2100 hours. A significant circadian rhythm was found for resting heart rate lying supine and sitting pre-exercise (P less than 0.05), peak values being measured at 1500 hours. The acrophase in the oral temperature rhythm at 1739 hours was not significantly out of phase with that of resting heart rate (P greater than 0.05). The rhythm in heart rate persisted during submaximal exercise (150 W) and at the maximal rate (P less than 0.05); the amplitude of the rhythm was attenuated at maximum. Ratings of perceived exertion at submaximal and maximal exercise intensities, and time of day (P greater than 0.05). The increment of 0.2 degrees C in oral temperature during exercise did not exhibit circadian variation (P greater than 0.05). A significant rhythm was found for recovery heart rates in minutes 2, 3, 4, and 5 post-exercise (P less than 0.05). Observations of systolic and diastolic pressures pre- and post-exercise were inconclusive. Therefore, the circadian rhythm in heart rate responses to exercise should be considered when a heart rate variable is used as a criterion in fitness testing or as an index of physiological strain.
As the exercise intensity is often expressed as percentage of either maximal workload (%Wmax), percentage of maximal heart rate (%HRmax), or as percentage of maximal oxygen uptake, the relationship between %Wmax, %VO2max, and %HRmax was determined in 53 male cyclists. All subjects performed an incremental maximal cycle ergometer test. In all athletes examined, a linear relation between power output, oxygen uptake and heart rate was observed. The relationships between %Wmax and %VO2max as well as between %Wmax and %HRmax were linear (r = 0.98 and r = 0.97; p < 0.001). It is concluded that studies which are different in expression of exercise intensity (%Wmax or %VO2max) can be compared and that the relation between %Wmax and %HRmax needs to be determined individually when an appropriate individualized training intensity based on heart rate is required.
This study determined the effects of a 20-wk endurance training program (The HERITAGE Family Study) on resting heart rate (HRrest). HRrest was obtained on a sample of 26 men and 21 women during sleep; during resting metabolic rate and resting blood pressure measurement periods in the early morning following a 12-h fast and 24-h post-exercise; and at rest prior to a maximal bout of exercise. Following training, the subjects exhibited a 16.0 +/- 9.4% (mean +/- SD) increase in VO2max (P < 0.05), but the HRrest for each of the resting conditions was decreased by only 1.9 to 3.4 bpm (P < 0.05), or an average across the three conditions of 2.7 bpm. In a larger sample of 253 HERITAGE subjects, HRrest obtained only at the time of the resting blood pressure measurement decreased by only 2.6 bpm, while VO2max increased 17.7 +/- 10.0%. It is concluded that there is a significant, but small, decrease in resting heart rate as a result of 20 wk of moderate- to high-intensity endurance training; which suggests a minimal alteration in either, or both, intrinsic heart rate and autonomic control of HRrest.
Nine elite canoeists were investigated concerning changes in performance, heart rate variability (HRV), and blood-chemical parameters over a 6-d training camp. The training regimen consisted of cross-country skiing and strength training, in total 13.0+/-1.6 h, corresponding to a 50% increase in training load.
Time to exhaustion (RunT) decreased from 19.1+/-1.0 to 18.0+/-1.2 min (P < 0.05). VO2max and max lactate (La(max)) both decreased significantly (P < 0.05) over the training period (4.99+/-0.97 to 4.74+/-0.98 L x min(-1) and from 10.08+/-1.25 to 8.98+/-1.03 mmol x L(-1) respectively). Heart rates (HR) decreased significantly at all workloads. Plasma volume increased by 7+/-7% (P < 0.05). Resting cortisol, decreased from 677+/-244 to 492+/-222 nmol x L(-1) (P < 0.05), whereas resting levels of adrenaline and noradrenaline remained unchanged. The change between tests in RunT correlated significantly with the change in HRmax (r = 0.79; P = 0.01). There were no group changes in high or low frequency HRV, neither at rest nor following a tilt.
The reduced maximal performance indicates a state of fatigue/overreaching and peripheral factors are suggested to limit performance even though HRmax and La(max) both were reduced. The reduced submaximal heart rates are probably a result of increased plasma volume. HRV in this group didn't seem to be affected by short-term overtraining.
Detraining can be defined as the partial or complete loss of training-induced adaptations, in response to an insufficient training stimulus. Detraining is characterized, among other changes, by marked alterations in the cardiorespiratory system and the metabolic patterns during exercise. In highly trained athletes, insufficient training induces a rapid decline in VO2max, but it remains above control values. Exercise heart rate increases insufficiently to counterbalance the decreased stroke volume resulting from a rapid blood volume loss, and maximal cardiac output is thus reduced. Cardiac dimensions are also reduced, as well as ventilatory efficiency. Consequently, endurance performance is also markedly impaired. These changes are more moderate in recently trained subjects in the short-term, but recently acquired VO2max gains are completely lost after training stoppage periods longer than 4 wk. From a metabolic viewpoint, even short-term inactivity implies an increased reliance on carbohydrate metabolism during exercise, as shown by a higher exercise respiratory exchange ratio. This may result from a reduced insulin sensitivity and GLUT-4 transporter protein content, coupled with a lowered muscle lipoprotein lipase activity. These metabolic changes may take place within 10 d of training cessation. Resting muscle glycogen concentration returns to baseline within a few weeks without training, and trained athletes' lactate threshold is also lowered, but still remains above untrained values.
Oxygen uptake, heart rate, pulmonary ventilation, and blood lactic acid were studied in five subjects performing maximal work on a bicycle ergometer. After a 10-min warming up period work loads were varied so that exhaustion terminated exercise after about 2—8 min. Peak oxygen uptake and heart rate were practically identical (sd 3.1% and 3 beats/minute, respectively) in the experiments. The heavier the work was and the shorter the work time the higher became the pulmonary ventilation. There was a more rapid increase in the functions studied when the heaviest work loads were performed. It is concluded that aerobic capacity can be measured in a work test of from a few up to about 8 min duration, severity of work determining the actual work time necessary. Duration of work in studies of circulation and respiration during submaximal work should exceed 5 min.
Submitted on June 23, 1961