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Monitoring performance-related characteristics of athletes can reveal changes that facilitate training adaptations. Here, we examine the relationships between submaximal running, maximal jump performance (CMJ), concentrations of blood lactate, sleep duration (SD) and latency (SL), and perceived stress (PSS) in junior cross-country skiers during pre-season training. These parameters were monitored in 15 male and 14 females (17 ± 1 years) for the 12-weeks prior to the competition season, and the data was analysed using linear and mixed-effect models. An increase in SD exerted a decrease in both PSS (B = -2.79, p  ≤ 0.01) and blood lactate concentrations during submaximal running (B = -0.623, p  ≤ 0.05). In addition, there was a negative relationship between SL and CMJ (B = -0.09, p  = 0.08). Compared to males, females exhibited higher PSS scores and little or no change in performance-related tests. A significant interaction between time and sex was present in CMJ with males displaying an effect of time on CMJ performance. For all athletes, lower PSS appeared to be associated with longer overnight sleep. Since the females experienced higher levels of stress, monitoring of their PSS might be beneficial. These findings have implications for the preparation of young athletes' competition season.

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., Competing Interests: The authors have declared that no competing interests exist.

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., (© Journal of Sports Science and Medicine.)

Purpose: It is known that modifying the endurance-type training load of athletes may result in altered cardiac autonomic modulation that may be estimated with heart rate variability (HRV). However, the specific effects of intensive resistance-type training remain unclear. The main aim of this study was to find out whether an intensive 2-wk resistance training period affects the nocturnal HRV and strength performance of healthy participants., Methods: Young healthy men (N = 13, age 24 [2] y) performed 2-wk baseline training, 2-wk intensive training, and a 9-d tapering periods, with 2, 5, and 2 hypertrophic whole-body resistance exercise sessions per week, respectively. Maximal isometric and dynamic strength were tested at the end of these training periods. Nocturnal HRV was also analyzed at the end of these training periods., Results: As a main finding, the nocturnal root mean square of differences of successive R-R intervals decreased (P = .004; from 49 [18] to 43 [15] ms; 95% CI, 2.4-10.4; effect size = 0.97) during the 2-wk intensive resistance training period. In addition, maximal isometric strength improved slightly (P = .045; from 3933 [1362] to 4138 [1540] N; 95% CI, 5.4-404; effect size = 0.60). No changes were found in 1-repetition-maximum leg press or leg press repetitions at 80% 1-repetition maximum., Conclusions: The present data suggest that increased training load due to a short-term intensive resistance training period can be detected by nocturnal HRV. However, despite short-term accumulated physiological stress, a tendency of improvement in strength performance was detected.

Kinematic analysis is often performed with a camera system combined with reflective markers placed over bony landmarks. This method is restrictive (and often expensive), and limits the ability to perform analyses outside of the lab. In the present study, we used a markerless deep learning-based method to perform 2D kinematic analysis of deep water running, a task that poses several challenges to image processing methods. A single GoPro camera recorded sagittal plane lower limb motion. A deep neural network was trained using data from 17 individuals, and then used to predict the locations of markers that approximated joint centres. We found that 300-400 labelled images were sufficient to train the network to be able to position joint markers with an accuracy similar to that of a human labeler (mean difference < 3 pixels, around 1 cm). This level of accuracy is sufficient for many 2D applications, such as sports biomechanics, coaching/training, and rehabilitation. The method was sensitive enough to differentiate between closely-spaced running cadences (45-85 strides per minute in increments of 5). We also found high test-retest reliability of mean stride data, with between-session correlation coefficients of 0.90-0.97. Our approach represents a low-cost, adaptable solution for kinematic analysis, and could easily be modified for use in other movements and settings. Using additional cameras, this approach could also be used to perform 3D analyses. The method presented here may have broad applications in different fields, for example by enabling markerless motion analysis to be performed during rehabilitation, training or even competition environments., (Copyright © 2019 Elsevier Ltd. All rights reserved.)

Objectives: Rescuers work in 24-h shifts and the demanding nature of the occupation requires adequate recovery between work shifts. The purpose of this study has been to find out what kind of changes in autonomic control may be seen during work shift and its recovery period in the case of rescuers. An additional interest has been to see if aerobic fitness is associated with recovery from work shifts., Material and Methods: Fourteen male rescuers (aged 34±9 years old) volunteered to participate in the study. Heart rate variability (HRV) was recorded for 96 h to study stress and recovery, from the beginning of a 24-h work shift to the beginning of the next shift. Aerobic fitness assessment included maximal oxygen uptake (VO2max) estimation with a submaximal bicycle ergometer test. Salivary cortisol samples were collected 0 min, 15 min, and 30 min after awakening on the 3 resting days., Results: Some HRV parameters showed enhanced autonomic control after the work shift. Stress percentage decreased from the working day to the 2nd rest day (p < 0.05). However, maximal oxygen uptake was not associated with enhanced parasympathetic cardiac control (p > 0.05). Cortisol awakening response was attenuated right after the work shift., Conclusions: The HRV findings show that recovery after a long work shift takes several days. Thus, rescuers should pay attention to sufficient recovery before the next work shift, and an integrated model of perceived and physiological measurements could be beneficial to assess cardiovascular strain among rescuers with long work shifts. Int J Occup Med Environ Health 2017;30(3):433-444., (This work is available in Open Access model and licensed under a CC BY-NC 3.0 PL license.)

Vesterinen, V, Nummela, A, Laine, T, Hynynen, E, Mikkola, J, and Häkkinen, K. A submaximal running test with postexercise cardiac autonomic and neuromuscular function in monitoring endurance training adaptation. J Strength Cond Res 31(1): 233-243, 2017-The aim of this study was to investigate whether a submaximal running test (SRT) with postexercise heart rate recovery (HRR), heart rate variability (HRV), and countermovement jump (CMJ) measurements could be used to monitor endurance training adaptation. Thirty-five endurance-trained men and women completed an 18-week endurance training. Maximal endurance performance and maximal oxygen uptake were measured every 8 weeks. In addition, SRTs with postexercise HRR, HRV, and CMJ measurements were carried out every 4 weeks. Submaximal running test consisted of two 6-minute stages at 70 and 80% of maximum heart rate (HRmax) and a 3-minute stage at 90% HRmax, followed by a 2-minute recovery stage for measuring postexercise HRR, HRV, and CMJ test. The highest responders according to the change of maximal endurance performance showed a significant improvement in running speeds during stages 2 and 3 in SRT, whereas no changes were observed in the lowest responders. The strongest correlation was found between the change of maximal endurance performance and running speed during stage 3, whereas no significant relationships were found between the change of maximal endurance performance and the changes of postexercise HRR, HRV, and CMJ. Running speed at 90% HRmax intensity was the most sensitive variable to monitor adaptation to endurance training. The present submaximal test showed potential to monitor endurance training adaptation. Furthermore, it may serve as a practical tool for athletes and coaches to evaluate weekly the effectiveness of training program without interfering in the normal training habits.

Introduction: Measures of HR variability (HRV) have shown potential to be of use in training prescription., Purpose: The aim of this study was to investigate the effectiveness of using HRV in endurance training prescription., Methods: Forty recreational endurance runners were divided into the HRV-guided experimental training group (EXP) and traditional predefined training group (TRAD). After a 4-wk preparation training period, TRAD trained according to a predefined training program including two to three moderate- (MOD) and high-intensity training (HIT) sessions per week during an 8-wk intensive training period. The timing of MOD and HIT sessions in EXP was based on HRV, measured every morning. The MOD/HIT session was programmed if HRV was within an individually determined smallest worthwhile change. Otherwise, low-intensity training was performed. Maximal oxygen consumption (V˙O2max) and 3000-m running performance (RS3000m) were measured before and after both training periods., Results: The number of MOD and HIT sessions was significantly lower (P = 0.021, effect size = 0.98) in EXP (13.2 ± 6.0 sessions) compared with TRAD (17.7 ± 2.5 sessions). No other differences in training were found between the groups. RS3000m improved in EXP (2.1% ± 2.0%, P = 0.004) but not in TRAD (1.1% ± 2.7%, P = 0.118) during the intensive training period. A small between-group difference (effect size = 0.42) was found in the change in RS3000m. V˙O2max improved in both groups (EXP: 3.7% ± 4.6%, P = 0.027; TRAD: 5.0% ± 5.2%, P = 0.002)., Conclusion: The results of the present study suggest the potential of resting HRV to prescribe endurance training by individualizing the timing of vigorous training sessions.

Unlabelled: Regular monitoring of adaptation to training is important for optimizing training load and recovery, which is the main factor in successful training., Purpose: To investigate the usefulness of a novel submaximal running test (SRT) in field conditions in predicting and tracking changes of endurance performance., Methods: Thirty-five endurance-trained men and women (age 20-55 y) completed the 18-wk endurance-training program. A maximal incremental running test was performed at weeks 0, 9, and 18 for determination of maximal oxygen consumption (VO2max) and running speed (RS) at exhaustion (RSpeak) and lactate thresholds (LTs). In addition, the subjects performed weekly a 3-stage SRT including a postexercise heart-rate-recovery (HRR) measurement. The subjects were retrospectively grouped into 4 clusters according to changes in SRT results., Results: Large correlations (r = .60-.89) were observed between RS during all stages of SRT and all endurance-performance variables (VO2max, RSpeak, RS at LT2, and RS at LT1). HRR correlated only with VO2max (r = .46). Large relationships were also found between changes in RS during 80% and 90% HRmax stages of SRT and a change of RSpeak (r = .57, r = .79). In addition, the cluster analysis revealed the different trends in RS during 80% and 90% stages during the training between the clusters, which showed different improvements in VO2max and RSpeak., Conclusions: The current SRT showed great potential as a practical tool for regular monitoring of individual adaptation to endurance training without time-consuming and expensive laboratory tests.

The assessment of heart rate variability (HRV) thresholds (HRVTs) as an alternative of Ventilatory thresholds (VTs) is a relatively new approach with increasing popularity which has not been conducted in cross-country (XC) skiing yet. The main purpose of the present study was to assess HRVTs in the five main XC skiing-related techniques, double poling (DP), diagonal striding (DS), Nordic walking (NW), V1 skating (V1), and V2 skating (V2).Ten competitive skiers completed these incremental treadmill tests until exhaustion with a minimum of one to two recovery days in between each test. Ventilatory gases, HRV and poling frequencies were measured. The first HRV threshold (HRVT1) was assessed using two time-domain analysis methods, and the second HRV threshold (HRVT2) was assessed using two non-time varying frequency-domain analysis methods. HRVT1 was assessed by plotting the mean successive difference (MSD) and standard deviation (SD) of normalized R-R intervals to workload. HRVT1 was assessed by plotting high frequency power (HFP) and the HFP relative to respiratory sinus arrhythmia (HFPRSA) with workload. HRVTs were named after their methods (HRVT1-SD; HRVT1-MSD; HRVT2-HFP; HRVT2-HFP-RSA). The results showed that the only cases where the proposed HRVTs were good assessors of VTs were the HRVT1-SD of the DS test, the HRVT1-MSD of the DS and V2 tests, and the HRVT2-HFP-RSA of the NW test. The lack of a wider success of the assessment of HRVTs was reasoned to be mostly due to the high entrainment between the breathing and poling frequencies. As secondary finding, a novel Cardiolocomotor coupling mode was observed in the NW test. This new Cardiolocoomtor coupling mode corresponded to the whole bilateral poling cycle instead of corresponding to each poling action as it was reported to the date by the existing literature.

The aim of this study was to investigate whether a novel heart rate (HR)-running speed index could be used in monitoring adaptation to endurance training. Forty-five recreational runners underwent a 2-phased 28-week training regime. The first 14 weeks included basic endurance training, whereas the second 14 weeks were more intensive (increased volume and intensity). A maximal treadmill running test was performed in the beginning of the experiment, in the middle of basic endurance training, and at the end of each training period (PRE, WEEK 7, WEEK 14, and POST). The novel HR-running speed index was calculated from every continuous-type running exercise during the 28-week experiment based on exercise HR-running speed relation accompanied by individual information on resting and maximal HR and speed. The change in the novel index correlated significantly with the changes of peak running speed in the treadmill tests (r = 0.43-0.61, p < 0.01) and speed at respiratory compensation threshold (r = 0.35-0.39, p ≤ 0.05) during the experiment. The change in the index also correlated significantly (r = 0.49, p = 0.001) with relative changes in maximal oxygen uptake (in ml·kg·min). According to these findings, it seems that the novel index based on exercise HR and running speed may serve as a practical tool for daily monitoring of individual's training adaptation without the need to realize a maximal running test in laboratory conditions.

Overload principle of training states that training load (TL) must be sufficient to threaten the homeostasis of cells, tissues, organs and/or body. However, there is no "golden standard" for TL measurement. The aim of the present study was to investigate if post-exercise heart rate variability (HRV) could be used to evaluate TL of interval running exercises with different intensities and durations. Thirteen endurance-trained men (35 ± 5 years) performed MO(250) [moderate intensity, 2 × 6 × 250 m/rec 30 s/5 min at 85% of the maximal velocity of the graded maximal test (V (max))], MO(500) (2 × 3 × 500 m/rec 1 min/5 min at 85% V (max)) and HI(250) (high intensity, 2 × 6 × 250 m/rec 30 s/5 min at 105% V (max)) interval exercises on a treadmill. HRV was analyzed during rest, exercise and immediate 15 min recovery. Fast recovery of LFP (P < 0.001), HFP (P < 0.01) and TP (P < 0.01) occurred during the first two recovery minutes after each exercise. Strong negative correlations (P < 0.01) were found between post-exercise HRV and perceived exertion as well as excess post-exercise oxygen consumption. Post-exercise HRV differentiated interval exercises of equal work, but varying intensity or distance of running bout. The results of the present study suggest that immediate post-exercise HRV may offer objective information on TL of interval exercises with different bout durations and intensities.

This study examined the relation of self-reported stress to cardiac autonomic modulation in real-life conditions. The participants for the study were healthy male (N = 59) and female (N = 40) employees (age 40 ± 10 years). A single-item question and a 14-item questionnaire on perceived stress were administered to the participants before the experimental night. RR-intervals (RRI) were recorded during night sleep and an orthostatic test after awakening at home. The RRI data were analyzed for heart rate (HR) and heart rate variability (HRV) in time and frequency domains. Nocturnal urinary stress hormone (cortisol, adrenal and noradrenal) secretion was also analyzed. Based on the self-reported stress, the participants were divided into either low or high stress group. The results showed that higher incidence of stress symptoms was significantly associated with lower HRV in the orthostatic test regardless of age and gender. Differences between the stress groups in HRV indices were approximately 20-50 and 30-75% in supine and standing positions, respectively. No difference was found in nocturnal HR, HRV, or stress hormone secretion between the stress groups. Higher incidence of stress symptoms was significantly associated with greater decrease of HRV from night sleep to the orthostatic test, as a response to awakening. In conclusion, the present findings support the view that autonomic modulation measured in the orthostatic test, but not during night sleep, is related to self-reported stress.

The overload principle of training states that training load (TL) must be sufficient to threaten the homeostasis of cells, tissues, organs, and/or body. However, there is no "golden standard" for TL measurement. The aim of this study was to examine if any post-exercise heart rate variability (HRV) indices could be used to evaluate TL in exercises with different intensities and durations. Thirteen endurance-trained males (35 +/- 5 year) performed MODE (moderate intensity, 3 km at 60% of the maximal velocity of the graded maximal test (vVO(2max))), HI (high intensity, 3 km at 85% vVO(2max)), and PRO (prolonged, 14 km at 60% vVO(2max)) exercises on a treadmill. HRV was analyzed with short-time Fourier-transform method during rest, exercise, and 15-min recovery. Rating of perceived exertion (RPE), blood lactate (BLa), and HFP(120) (mean of 0-120 s post-exercise) described TL of these exercises similarly, being different for HI (P < 0.05) and PRO (P < 0.05) when compared with MODE. RPE and BLa also correlated negatively with HFP(120) (r = -0.604, -0.401), LFP(120) (-0.634, -0.601), and TP(120) (-0.691, -0.569). HRV recovery dynamics were similar after each exercise, but the level of HRV was lower after HI than MODE. Increased intensity or duration of exercise decreased immediate HRV recovery, suggesting that post-exercise HRV may enable an objective evaluation of TL in field conditions. The first 2-min recovery seems to give enough information on HRV recovery for evaluating TL.

Introduction: Chronic work stress and overtraining are known to influence heart rate (HR) and heart rate variability (HRV) at rest and decreased nocturnal HRV is associated with cardiovascular health and disease. The purpose of this study was to examine whether anticipation of an acute highly stressful event influences HR and HRV during the night and morning., Methods: Nocturnal HR and HRV and urinary stress hormones (cortisol, adrenaline, noradrenaline) as well as HR and HRV responses to an orthostatic test on the morning of a parachute jump day or control day were analyzed from 14 novice and 7 experienced parachute jumpers., Results: There were no differences in any HRV indices during the night or the orthostatic test between the jump and control situations. The novices had higher HR than experienced jumpers in the orthostatic test in the morning and also during the jump, but no differences were found between the groups in nocturnal HR and HRV indices or HRV indices during the orthostatic test. There were no differences in nocturnal stress hormone secretions except slightly elevated adrenaline secretion during the jump night compared to the control night (P = 0.014)., Conclusions: The parachute jump did not substantially influence HR, HRV, or stress hormones during the night or the orthostatic test in the morning preceding the jump. The results suggest that the parachute jump as an acute highly stressful event had no anticipatory effect on autonomic modulation of the heart even though both the novices and experienced jumpers had markedly accentuated sympathetic activation during the parachuting.

The aim of this study was to assess fatigue during a simulated cross-country skiing sprint competition based on skating technique. Sixteen male skiers performed a 30-m maximal skiing speed test and four 850-m heats with roller skies on a tartan track, separated by 20 min recovery between heats. Physiological variables (heart rate, blood lactate concentration, oxygen consumption), skiing velocity, and electromyography (EMG) were recorded at the beginning of the heats and at the end of each 200-m lap during the heats. Maximal skiing velocity and EMG were measured in the speed test before the simulation. No differences were observed in skiing velocity, EMG or metabolic variables between the heats. The end (820-850 m) velocities and sum-iEMG of the triceps brachii and vastus lateralis in the four heats were significantly lower than the skiing velocity and sum-iEMG in the speed test. A significant correlation was observed between mean oxygen consumption and the change in skiing velocity over the four heats. Each single heat induced considerable neuromuscular fatigue, but recovery between the heats was long enough to prevent accumulation of fatigue. The results suggest that the skiers with a high aerobic power were less fatigued throughout the simulation.

Purpose: This study was conducted to test the hypothesis of autonomic imbalance in overtrained athletes during sleep and after awakening with analyses of heart rate variability (HRV) and nocturnal urine stress hormones., Methods: We examined 12 athletes diagnosed to be severely overtrained (OA, 6 men and 6 women, mean age (+/-SD) 25 +/- 7 yr) and 12 control athletes (CA, 6 men and 6 women, mean age 24 +/- 5 yr). Overtraining diagnosis was further supported by higher perceived stress in OA than in CA (24.8 +/- 10.8 vs 15.3 +/- 5.5, P < 0.05). HRV was analyzed with time and frequency domain methods from RR intervals (RRI) recorded during sleep and after awakening. Nocturnal urine stress hormones were analyzed by liquid chromatography., Results: No differences were found in HRV or stress hormones during night sleep. After awakening, the standard deviation of RRI (84 +/- 31 vs 116 +/- 41 ms, P < 0.05) and low-frequency power of RRI (2153 +/- 2232 vs 4286 +/- 2904 ms, P < 0.05) were lower in OA than in CA. From sleep to after awakening, the coefficient of variation of RRI decreased more in OA than in CA (from 11.8 +/- 3.3 to 7.7 +/- 2.5%, P < 0.001 vs from 11.9 +/- 1.8 to 10.0 +/- 2.5%, P < 0.01, respectively, interaction P < 0.05)., Conclusion: The present findings suggest that in OA, cardiac autonomic modulation is at the level of control athletes during sleep, but the parasympathetic cardiac modulation is slightly diminished after awakening. Further investigations should concentrate on autonomic responses to different challenges, such as awakening in the present study.