Adaptive training load optimization for track and field athletes: A reinforcement learning approach

The aim of the study is to develop the standards of HRV indexes at rest and during an orthostatic challenge, taking into account different ranges of variability of cardiac intervals (MxDMn) of track and field athletes. The other purpose is to identify the features of changes in the standards in the training process in cases of malfunctions of cardioregulatory systems, sinus node functioning and recovery process, overtraining, and decrease in athletic performance. The authors used the results of individual dynamic express-tests of heart rate variability (HRV) in track and field athletes belonging to different specific training orientations to achieve the goals of the study. Research Methods and Organization. We carried out 1740 dynamic HRV measurements at rest and during an orthostatic challenge. The studies involved 56 track and field athletes (sprinters, middle distance runners and stayers) aged 18 to 29 years, belonging to the 1st adult category, Candidates Master of Sports and Masters of Sports, in different periods of the training process. We carried out HRV measurements in the laboratory of functional research methods of the Institute of physical culture and sports at Udmurt State University, as well as at training camps in the middle mountains (Kyrgyzstan, Kislovodsk) and on the plain (Elabuga). We examined the test subjects at rest in the morning after the previous training day, using the VARICARD 2.51 device and the ISCIM6 and VARICARD MP programs (Ryazan). We recorded cardio intervals of athletes for 5 minutes in lying position and for 6 minutes in standing position. We applied HRV measurements to one or four athletes simultaneously using the ISCIM6 and VARICARD MP programs. Research results. We assigned special emphasis to the assessment of changes in the variational range of cardiointervals (MxDMn) reflecting the state of cardiac regulation and the sinus node functioning during dynamic HRV studies in the training process of each runner. We identified seven MxDMn variation ranges from <150ms to >650ms. We revealed that each MxDMn variation range corresponds to a certain prevailing type of regulation. We demonstrated that frequent shifts of the MxDMn ranges from one level to another in the training process of runners indicate instability of cardiac regulation. We elaborated standards for the variational range of cardiointervals (MxDMn), taking into account the predominance of the HF and LF power in the HRV power spectrum for runners with different specific training orientations. We found that respiratory (HF) or vasomotor waves (LF) could prevail within the same MxDMn variation ranges, which points to a different autonomic balance. We revealed that at rest, the variational range of cardiointervals (MxDMn) depends more on the state of cardiac regulation and the sinus node functioning and less on the specifics of running. We often detected paradoxical reactions to an orthostatic challenge at low or extremely high MxDMn values in the overtrained runners. We determined that runners of any specific training orientation could increase their fitness, adaptive and reserve capabilities only in the context of the optimal regulation state, stable favorable ranges of MxDMn values, and the absence of paradoxical reactions to an orthostatic challenge. The paper contains tables with standard HRV indicators for different MxDMn variation ranges and consideration of the predominance of HF and LF waves at rest and during an orthostatic challenge, as well as examples of the results of HRV analysis at rest and during an orthostatic challenge in runners with different MxDMn variation ranges in the training process. Conclusion. The research demonstrated that the use of the HRV analysis method at rest and during an orthostatic challenge, taking into account the standards of MxDMn values in the training process of track and field athletes, is aimed at obtaining the necessary information about the stability of autonomic balance, autonomic reactivity and body reserves that ensure optimal adaptation and recovery processes.

The aim of this short review was to summarize data pertaining to the rating of perceived exertion (RPE) methods (RPE value and session-RPE) during combat sport-specific activities (i.e., competition and training) based on many factors, including contest type (i.e., official vs. simulated vs. training), combat rounds, age of participants and muscle groups, and their correlation with physiological variables (i.e., blood lactate concentration [La] and heart rate [HR]). The current review shows higher RPE in a match of mixed martial arts (MMAs) than Brazilian jiu-jitsu and kickboxing matches and during the competitive period compared with the precompetitive period. This could be explained by the longer duration of bouts, the higher percentage contribution of aerobic metabolism in MMA than other combat sports and contest type differences (simulated vs. official matches). Thus, this review found significant correlations between RPE or session-RPE, [La] and HR. Particularly, there was a stronger correlation between RPE and [La] during official striking (r = 0.81) than grappling combat sports matches (r = 0.53). In addition, a variation of correlation (moderate to large) between session-RPE and HR-based methods has been reported (i.e., Edwards' training load [r ranged between 0.58 and 0.95] and Banister training impulse [r ranged between 0.52 and 0.86]). Specifically, stronger correlation was apparent in combat sport competition that required a much higher percentage contribution of aerobic metabolism (e.g., karate) and in adult athletes than anaerobic-based combat sports (e.g., taekwondo) and young athletes, respectively. Indeed, the current review highlights that the correlations between session-RPE and HR-based methods were higher during official competition than training sessions. Session-RPE was affected by participants' competitive level, the intensity of session (high vs. low), the training modalities (tactical-technical vs. technical-development vs. simulated competition), and the training volume in combat sports athletes. Rating of perceived exertion is a valid tool for quantifying internal training and combat loads during short- and long-term training and simulated and official competitions in novice and elite combat sport athletes. Furthermore, both RPE methods may be a more reliable measure of intensity or effort when both anaerobic and aerobic systems are appreciably activated. Coaches, sports scientists, and athletes can use session-RPE method to quantify short-term training and combat loads in adult athletes during precompetitive period much more than long-term training and in young athletes during the competitive period. They can also use RPE to monitor combat and short- and long-term training loads to better plan and assist training programs and competitions.

The training load monitoring and adjustment algorithm for athletes, based on heart rate variability (HRV) and body index data, offers a comprehensive approach to optimizing athletic performance and minimizing the risk of injury. By leveraging HRV data, which reflects the autonomic nervous system's response to training stress, and body index measurements such as body mass index (BMI) or body fat percentage, the algorithm provides insights into athletes' physiological readiness and recovery status. The design of an effective training load monitoring and adjustment algorithm is critical for optimizing athletic performance while minimizing the risk of injury and overtraining. This paper proposes a novel approach that integrates heart rate variability (HRV) and body index data to tailor training programs to individual athlete needs. This paper presents an innovative approach to training load monitoring and adjustment for athletes, utilizing heart rate variability (HRV) and body index data. Through continuous monitoring and analysis of HRV metrics such as RMSSD and LF/HF Ratio, in conjunction with body mass index (BMI) and body fat percentage, personalized load management strategies are developed to optimize athletic performance while mitigating the risk of injury and overtraining. The optimization algorithm outlined in this study allows for real-time adjustments to training loads based on individual physiological responses, ensuring that athletes receive tailored training programs that maximize performance gains and promote long-term health and well-being. By leveraging HRV and body index data, coaches and sports scientists can enhance athletic performance outcomes and support the overall development and longevity of athletes' careers.

PURPOSE: This study aimed to determine relationships between changes in heart rate variability, training load (TL) and perceived recovery status indicators (psychometrics) following a 2-week preseason and to interpret these changes on an individual basis among 8 Division-1 collegiate female soccer players. METHODS: Weekly averages for Smartphone-derived resting logarithm of the root mean square of successive RR intervals multiplied by 20 (lnRMSSD), TL (training impulse) and psychometrics were compared with effect sizes (ES) and magnitude based inferences. Relationships between variables were determined with Pearson correlations. Individual increases in lnRMSSD and decreases in lnRMSSD coefficient of variation (CV) were interpreted as a positive coping response and vice versa for a negative coping response. RESULTS: Group analysis showed an unclear small increase in daily TL (week 1 = 176.4 ± 27.6, week 2 = 195.5 ± 57.7; proportion = 74/19/7, ES = 0.45) and a likely small increase in lnRMSSD (week 1 = 74.2 ± 11.1, week 2 = 78.1 ± 10.5; proportion = 81/14/5, ES = 0.35). Fatigue demonstrated a very likely small improvement (week 1 = 5.03 ± 1.09, week 2 = 5.51 ± 1.00; proportion = 95/4/1; ES = 0.45) while the other psychometrics did not meaningfully change. A very large negative correlation was found between the changes in TL and lnRMSSD (r = -0.85) while small to large correlations were found between lnRMSSD and psychometric variables (r values of 0.56, 0.34, 0.54, -0.06 and -0.03 for fatigue, sleep, soreness, stress and mood, respectively). Individual analysis determined that 2 subjects may benefit from decreased TL, 2 subjects may benefit from increased TL and 4 subjects require no intervention based on their psychometric and mean and CV lnRMSSD responses to the TL. CONCLUSION: Weekly mean changes in lnRMSSD are related to changes in TL and perceived levels of fatigue and soreness in female soccer players. Monitoring TL and recovery status indicators during preseason may be useful for managing fatigue and optimizing TL on an individual basis.

Heart rate variability and cognitive function: Effects of physical effort

The effect of strenuous exercise on sleep patterns in swimmers is equivocal. Therefore, the purpose of the study was to describe possible changes in sleep parameters among elite swimmers subjected to different training loads (TL). Methods: Eighteen elite swimmers (8 females) were monitored across two high-volume preparatory 1-wk periods (P1, P2) and a lower-volume tapering 1-wk period (P3) before a major competition. Internal (the session rating of perceived exertion [sRPE]) and external TL (training duration and volume) were measured, along with several sleep indices (e.g., bedtime, get-up time, sleep time, wake after sleep onset [WASO]). Serum measurements of urea, creatine kinase (CK), testosterone and cortisol were taken before and after training sessions at the beginning (Mondays) and end (Fridays) of each micro cycle. Athlete TL decreased significantly in a stepwise manner from P1 to P2 and from P2 to P3. Of all sleep parameters, only significant differences in bedtime and get-up time emerged (P3 > P1 and/or P2). Sleep duration (~6.3 h) or quality (WASO: 41-45 min) were also unaffected by TL. CK levels declined from P1 to P3 (d = -0.8), and from P2 to P3 (d = -0.6). Positive exercise-induced changes in CK were also seen in each training period. The other biomarkers did not show the same temporal or acute patterns. Irrespective of the TL, the monitored swimmers experienced insufficient and fragmented sleep across this study. Neither sleep quality nor quantity were affected by different magnitudes of TL. Among the biochemical markers of fatigue, baseline plasma CK activity best reflected the physiological response to TL.

Purpose: This study was done to investigate quality of sleep and heart rate variability by the physical activity in high school students. Methods: A survey that measures physical activity and quality of sleep was distributed to 118 students at Y High School. Heart rate variability was obtained using the LXC3203 heart rate monitor. The data of 105 students were analyzed using descriptive statistics, t-test, x2-test, and ANOVA with Scheffe? test. Results: Boys and students with part-time jobs had significantly higher physical activity. The quality of sleep was significantly high when the students were non-smokers, felt healthy, happy, less stressed, and satisfied with their school lives. Mean heart rate was significantly higher among girls, and standard deviation from normal to normal R-R intervals were high in boys. Physical activity had no significant relationships with quality of sleep and heart rate variability. Conclusions: Physical activity should be encouraged for high school students, especially for girls. An experimental study with different intensity and time of physical activity is recommended to examine the relationships with quality of sleep and heart rate variability in the future.

The current case study aimed to quantify within-subjects correlations between training load and well-being in elite male beach soccer players. Data were obtained over three consecutive days during the preparation camp for the FIFA Beach Soccer World Cup Russia 2021. The session rating of perceived exertion (s-RPE) and external training load metrics using global positioning system (GPS) were recorded. Eleven players reported perceived well-being (sleep quality, fatigue, muscle soreness and stress) using a Likert scale (Hooper Index) before breakfast. Within-subjects correlation coefficients between workload and well-being were calculated. Workload metrics and perceived well-being indices were significantly lower on day three than on days one and two. The Hooper Index presented a very large positive correlation with s-RPE (r = 0.86 [0.67, 0.94], 95% confidence interval, CI), exposure time (r = 0.88 [0.71, 0.95]), total distance (r = 0.83 [0.60, 0.93]), high-speed distance (r = 0.77 [0.50, 0.91]), and number of sprints (r = 0.75 [0.47, 0.90]). Sleep quality presented a moderate to large positive correlation with s-RPE (r = 0.51 [0.11, 0.77]), exposure time (r = 0.50 [0.10, 0.76]), high-speed distance (r = 0.53 [0.15, 0.78]), number of sprints (r = 0.62 [0.28, 0.83]) and total distance (r = 0.41 [0.18, 0.78]). Fatigue presented a large to very large positive correlation with s-RPE (r = 0.85 [0.66, 0.94]), exposure time (r = 0.90 [0.78, 0.96]), total distance (r = 0.86 [0.68, 0.94]), high-speed distance (r = 0.65 [0.31, 0.84]) and number of sprints (r = 0.56 [0.18, 0.79]). Muscle soreness presented a large to very large positive correlation with s-RPE (r = 0.79 [0.56, 0.91]), exposure time (r = 0.83 [0.62, 0.93]), total distance (r = 0.81 [0.59, 0.92]), high-speed distance (r = 0.75 [0.47, 0.89]) and number of sprints (r = 0.59 [0.22, 0.81]). Overall, workload presented a meaningful correlation with perceived well-being indices in elite male beach soccer players during a training camp. These findings suggest that workload metrics and perceived well-being indices can be implemented into the daily routine of an elite beach soccer team, which may assist coaches, sports scientists, and practitioners in better preparing players for beach soccer competitions.

To investigate the internal training loads of a professional Spanish female futsal team throughout 26weeks of training including preseason and in-season weeks and verify the impact of training period and/or training load magnitudes on heart-rate variability responses. Furthermore, we aimed to assess, intraindividually, the relationship between training load and the coefficient of variation (CV) of weekly natural log of the root mean square difference of successive normal interbeat (RR) intervals (lnRMSSDCV), obtained from ∼5 measures per week, and recorded in the seated position. A within-subject design involved 12 high-level outfield female futsal players (mean [SD] age: 23.9 [3.4]y). lnRMSSD was significantly lower and lnRMSSDCV was significantly higher during the preseason (weeks 1-6) compared to in-season (weeks 7-26) (P < .001). Individually, players presented moderate to large negative correlations between lnRMSSDCV and lnRMSSD during the 26weeks of observation. Correlations ranged between rplayer4 = -.41 (95% CI, -.69 to -.02) and rplayer12 = -.55 (-.78 to -.18). Players also presented moderate to very large positive correlations between lnRMSSDCV and session rating of perceived exertion. Correlations ranged between rplayer7 = .41 (.04 to .71) and rplayer1 = .71 (.45 to .86). Professional female futsal players in this study presented increased lnRMSSD and reduced lnRMSSDCV during 20weeks into the competitive season compared to 6weeks of preseason. Furthermore, lnRMSSDCV was negatively associated with lnRMSSD on an intraindividual basis. Finally, higher internal training loads were positively correlated with lnRMSSDCV, indicating that heart-rate variability is responsive to weekly training loads.

BackgroundThe relationship between acute:chronic workload ratios (ACWR) and the incidence of injury, as well as the relationship between subjective wellness scores and training load, is unclear in hockey players.ObjectivesThis study investigated these relationships to determine if the ACWR is a useful workload management tool for field hockey players. In addition, the study investigated the association between specific subjective wellness scores (fatigue, sleep quality, general muscle soreness, mood and stress level) and the acute:chronic workload ratio and training load. The study also assessed the association between individual players’ training loads with the self-reported wellness scores.MethodsFourteen male field hockey players from the men’s first team at the University of the Witwatersrand participated in the study over ten weeks during a premier league competition phase. A Google form was completed within thirty minutes of every training session/match. This form consisted of questions that allowed for the calculation of the ACWR.ResultsNo incidence of injury was reported during the ten-week period. ACWR scores ranged between 0.67 and 1.87. The ACWR was associated with general muscle soreness (p = 0.010) and training load was associated with fatigue (p = 0.002), sleep quality (p = 0.05), general muscle soreness (p = 0.004), and mood (p=0.025).ConclusionThere may be some merit in the use of subjective wellness measures as workload management tools in field hockey. Further research is required to determine if there is an optimal ACWR for this sport.

The aim of this research was to study the peculiarities of heart rate variability (HRV) and microcirculation in students, depending on their sport specialization. Methods and Results: Our study included the results of a survey of 96 students from 18 to 21 years of age who were the members of the national teams of their universities in athletics (n=49) and floorball (n=47). For ECG registration and analysis of hemodynamic findings, including those characterizing the HRV, we used the “Medical Soft” sports testing system (“MS FIT Pro”). For monitoring, we used the standard hemodynamic patterns (blood pressure, HR, stroke volume, cardiac output, and others), statistical and spectral indicators of the HRV, as well as an integral criterion of the state of microcirculation. The studied HRV parameters in most students generally were within the age range. At the same time, track and field athletes have large adaptive resources and, consequently, a more optimal level of myocardial fitness, in comparison with floorball players. Conclusion: The orientation of sports training among students affects heart condition.

The Covid-19 outbreak forced many governments to enter a nationwide lockdown. The aim of this study was to evaluate, by means of a survey, changes in sleep parameters and physical activity characteristics of elite track and field athletes in three periods: before the lockdown (T0), during the lockdown (09th March – 03rd May 2020, T1) and the first month after the lockdown (T2). This study was conducted from May 2020 to June 2020 and data were collected using an offline survey with 89 elite track and field athletes (mean age: 24.7 ± 5.4; n = 43 males; n = 46 females). The survey consisted of demographic data and questions on physical activity and sleep behavior at T0, T1 and T2. Athletes reported lower sleep quality scores at T1 compared to T0 and T2 (p < 0.0001) and registered delayed bedtime, wake-up time and longer sleep latency during the lockdown compared to pre-lockdown and post-lockdown whereas no changes in total sleep time were reported. No inter-group differences were detected in sleep characteristics between short- and long-term disciplines and between genders. The weekly training volume decreased from 16.1 ± 5.7 hours at T0 to 10.7 ± 5.7 hours at T1 (p < 0.0001) whereas no significant differences were detected in training volume during the lockdown in relation to the square footage of the house (p = 0.309). Alcohol (p = 0.136) and caffeine intake (p = 0.990) and use of electronic devices (p = 0.317) were similar pre-, during, and post-lockdown. The unprecedented circumstances of the Covid-19 pandemic had negative impacts on the Italian track and field athletes’ sleep and training volumes.

Background: Little is known of injury patterns in track and field (athletics). Injury prevalence has been proposed as the most appropriate measure of the injury rate in sports where athletes are at risk for overuse problems. Purpose: To ascertain 1-year retrospective and current prevalence of injury in elite track and field athletes to help plan injury prevention programs for this sport. Study Design: Descriptive epidemiology study. Methods: Two hundred seventy-eight youth (16 years old) and adult athletes from an eligible study population of 321 athletes were included. Results: The 1-year retrospective injury prevalence was 42.8% (95% confidence interval [CI], 36.9%-49.0%); the point prevalence was 35.4% (95% CI, 29.7%-41.4%). The diagnosis group displaying the highest injury prevalence was inflammation and pain in the gradual onset category (1-year prevalence, 20.9%; 95% CI, 16.2%-26.2%; and point prevalence, 23.2%; 95% CI, 18.4%-28.7%). A strong tendency for higher 1-year prevalence of 16.5% (95% CI, 12.2%-21.4%) than point prevalence of 8.5% (95% CI, 5.5%-12.5%) was recorded for sudden onset injuries in the diagnosis group sprain, strain, and rupture. The body region showing the highest injury prevalence was the knee and lower leg with 15.0% (95% CI, 11.0%-19.8%) 1-year prevalence and 13.7% (95% CI, 9.8%-18.3%) point prevalence, followed by the Achilles tendon, ankle, and foot/toe with 11.7% (95% CI, 8.2%-16.1%) 1-year prevalence and 11.4% (95% CI, 7.9%-15.8%) point prevalence. Conclusion: The injury prevalence is high among Swedish elite track and field athletes. Most of the injuries affect the lower extremities and are associated with a gradual onset. Although it is associated with a potential recall bias, the 1-year retrospective prevalence measure captured more sudden onset injuries than the point prevalence measure. Future prospective studies in track and field are needed to identify groups of athletes at increased risk.

Little information is available regarding the TL and training practices of competitive athletes who are solid-organ recipients. This study characterized TL and practices of competitive organ-recipients at the British and World Transplant Games, 2017. Questionnaire data was gathered from 220 participants regarding sporting events and type, frequency, duration and intensity of training sessions undertaken. TL for each training session (session duration × session rating of perceived exertion [RPE]) and total TL were determined. Overall participants trained 5 ± 3 times per week at an RPE of 5 ± 2 AU for between 60 and 75 min per session (TL ∼1,500-1,875 AU). Most participants (n = 176; 79.7%) reported training three or more times each week. Approximately half (49%) the participants reported undertaking resistance training each week (3 ± 2 sessions per week, RPE of 6 ± 2 AU, 45-60 min per session; TL ∼810-1,080 AU, respectively). Of those participants undertaking resistance training 75% undertook two or more sessions each week. Participants generally undertook most events within a predominant sport with one or two events in a secondary sport. Typical weekly TL for the whole group was 2,762 ± 3,583 AU with considerable variation within and across sports (cycling 4,383 ± 4,005 AU; field athletics 3,671 ± 6,181 AU; court-based sports 2,645 ± 3,308 AU; high physical demand sports [e.g., skiing, triathlon] 2,595 + 2,247 AU; track athletics 2,547 ± 2,664 AU; swimming 2,091 ± 1,070 AU; low physical demand sports [e.g., darts, petanque, walking] 1,182 + 801 AU). Sports-specific TL for predominant and secondary sports was ∼1,500 AU. Resistance training and gym-based aerobic training were the most frequent non-specific training components undertaken. Most competitors (79%) were active in sport prior to transplant. The wide range of TL and components undertaken by athletes with solid-organ transplants likely reflects the multiple and diverse event participation of competitive organ-recipients as well as the diverse physical fitness profiles and incentives to participate. Optimization of TL both for multiple competitive sports and maintenance of health should be considered for these athletes.

Longitudinal variations in maximal oxygen intake with age and activity.