Cardiorespiratory Markers Relate to Change-of-Direction Performance During Incremental Endurance Tests and Friendly Matches in Professional Male Handball Players.

PURPOSE: To compare the standard Yo-Yo intermittent recovery (IR) test and an agility Yo-Yo IR test with a higher number of change-of-direction movements to cardiorespiratory match performance. METHODS: The study included 11 professional male handball players (age 24.5 [4.6] y) of a German second-league team. The performance parameters of the players of the seasons 2016-17 to 2018-19 were analyzed. The Yo-Yo IR test was compared to a Yo-Yo IR test with multiple multidirectional changes of direction in response to visual stimuli, which was conducted on a SpeedCourt (Yo-Yo SC IR). Peak oxygen uptake (VO2peak) and maximum heart rate (HRmax) were measured. Between-methods differences of individual athletes were quantified with Bland-Altman plots. RESULTS: HRmax was not statistically different during the Yo-Yo SC IR test compared to the Yo-Yo IR test (181 [10] vs 188 [8] beats·min-1; P = .16). Agreement between the 2 tests was moderate for HRmax and good for heart rates >180 beats·min-1. Mean average VO2peak was 51.7 (3.9) and 50.9 (2.8) mL·min-1·kg-1 for the Yo-Yo SC IR test and the Yo-Yo IR test (P = .693), respectively. CONCLUSIONS: A Yo-Yo test with multidirectional changes of direction in response to visual stimuli yielded good agreement with the frequently used linear running tests and can be used to assess players' VO2peak. The HRmax achieved during this test should be used with caution.

ChatGPT Generated Training Plans for Runners are not Rated Optimal by Coaching Experts, but Increase in Quality with Additional Input Information.

ChatGPT may be used by runners to generate training plans to enhance performance or health aspects. However, the quality of ChatGPT generated training plans based on different input information is unknown. The objective of the study was to evaluate ChatGPT-generated six-week training plans for runners based on different input information granularity. Three training plans were generated by ChatGPT using different input information granularity. 22 quality criteria for training plans were drawn from the literature and used to evaluate training plans by coaching experts on a 1-5 Likert Scale. A Friedmann test assessed significant differences in quality between training plans. For training plans 1, 2 and 3, a median rating of <3 was given 19, 11, and 1 times, a median rating of 3 was given 3, 5, and 8 times and a median rating of >3 was given 0, 6, 13 times, respectively. Training plan 1 received significantly lower ratings compared to training plan 2 for 3 criteria, and 15 times significantly lower ratings compared to training plan 3 (p < 0.05). Training plan 2 received significantly lower ratings (p < 0.05) compared to plan 3 for 9 criteria. ChatGPT generated plans are ranked sub-optimally by coaching experts, although the quality increases when more input information are provided. An understanding of aspects relevant to programming distance running training is important, and we advise avoiding the use of ChatGPT generated training plans without an expert coach's feedback.

Corrigendum: Position statement and updated international guideline for safe and effective whole-body electromyostimulation training-the need for common sense in WB-EMS application.

[This corrects the article DOI: 10.3389/fphys.2023.1174103.].

Position statement and updated international guideline for safe and effective whole-body electromyostimulation training-the need for common sense in WB-EMS application.

Whole-Body Electromyostimulation (WB-EMS) is a training technology that enables simultaneous stimulation of all the main muscle groups with a specific impulse intensity for each electrode. The corresponding time-efficiency and joint-friendliness of WB-EMS may be particularly attractive for people unable or unmotivated to conduct (intense) conventional training protocols. However, due to the enormous metabolic and musculoskeletal impact of WB-EMS, particular attention must be paid to the application of this technology. In the past, several scientific and newspaper articles reported severe adverse effects of WB-EMS. To increase the safety of commercial non-medical WB-EMS application, recommendations "for safe and effective whole-body electromyostimulation" were launched in 2016. However, new developments and trends require an update of these recommendations to incorporate more international expertise with demonstrated experience in the application of WB-EMS. The new version of these consensus-based recommendations has been structured into 1) "general aspects of WB-EMS", 2) "preparation for training", recommendations for the 3) "WB-EMS application" itself and 4) "safety aspects during and after training". Key topics particularly addressed are 1) consistent and close supervision of WB-EMS application, 2) mandatory qualification of WB-EMS trainers, 3) anamnesis and corresponding consideration of contraindications prior to WB-EMS, 4) the participant's proper preparation for the session, 5) careful preparation of the WB-EMS novice, 6) appropriate regeneration periods between WB-EMS sessions and 7) continuous interaction between trainer and participant at a close physical distance. In summary, we are convinced that the present guideline will contribute to greater safety and effectiveness in the area of non-medical commercial WB-EMS application.

Muscle strength gains per week are higher in the lower-body than the upper-body in resistance training experienced healthy young women-A systematic review with meta-analysis.

BACKGROUND: Women are underrepresented in resistance exercise-related studies. To date only one meta-analysis provides concrete training recommendations for muscle strength gains through resistance training in eumenorrhoeic women. OBJECTIVE: This review aims to identify research gaps to advance future study in this area to expand the knowledge concerning resistance exercise-induced strength gains in women and to provide guidelines on the number of repetitions per set and the training frequency per week to enhance maximal muscle strength. METHODS: The electronic databases PubMed and Web of Science were searched using a comprehensive list of relevant terms. After checking for exclusion criteria, 31 studies could be included in the final analysis using data from 621 subjects. From these data sets, the ideal number of repetitions per set and also the training frequency per week were analyzed. RESULTS: In the lower body, the largest gains were achieved with 1 to 6 repetitions (17.4% 1RM increase). For lower-body exercises, the highest gains were achieved with 13 to 20 repetitions (8.7% 1RM increase). The lower body should be trained two times a week (8.5% 1RM increase). The upper body should be trained two (5.2% 1RM increase) to three times (4.5% 1RM increase) a week. CONCLUSION: Women can increase their 1RM by 7.2% per week in the upper body and by 5.2% per week in the lower-body exercises. The upper body can be trained more than two times per week whereas the lower body should be trained two times. Women with intermediate experiences in RT and advanced performance level show more rapid increases in strength in the lower-body compared to the upper-body while no differences were found between upper and lower limb adaptations in RT-beginner subjects.

The magnitude and time-course of physiological responses to 9 weeks of incremental ramp testing.

PURPOSE: The aims of this study were to assess (1) the day-to-day variability in, and (2) the magnitude and time-course of adaptation of physiological parameters (i.e., maximal oxygen uptake [VO2 max], heart rate [HR], blood lactate concentration, respiratory exchange ratio [RER], ratings of perceived exertion [RPE], and time-to-exhaustion [TTE]) in response to an intervention involving three incremental ramp tests per week for 9 weeks. METHODS: Twelve participants (25 ± 4 yrs, VO2 max, 47.8 ± 5.2 mL∙min-1 ∙kg-1 (means ± SD)) completed the entire experimental procedure. The tests comprised a 5-min constant workload to obtain submaximal parameters followed by an incremental protocol until exhaustion. RESULTS: The mean day-to-day variability for the maximal value of VO2 was 2.8%, 1.1% for HR, 18.1% for blood lactate concentration, 2.1% for RER, 1.1% for RPE, and 5.0% for TTE. The values for the corresponding submaximal variables were 3.8% for VO2 , 2.1% for HR, 15.6% for blood lactate concentration, 2.6% for RER and 6.0% for RPE. VO2 max (+4.7% ± 3.5%), TTE (+17.9% ± 8.6%), and submaximal HR (-3.2 ± 3.5%) improved significantly. Except for RPE (p < 0.01), there were no alterations in the coefficient of variation for any parameter. On the group level, the first changes greater than the day-to-day variability in VO2 max, TTE, and submaximal HR were observed after 21, 12, and 9 training sessions, respectively. CONCLUSION: Based on our findings, we recommend that training studies include assessment of the reliability of the measurements, for example, the CVs in the specific laboratory to be able to judge if the changes detected are actually physiological.

Retrospective Analysis of Training Intensity Distribution Based on Race Pace Versus Physiological Benchmarks in Highly Trained Sprint Kayakers.

BACKGROUND: Research results on the training intensity distribution (TID) in endurance athletes are equivocal. This non-uniformity appears to be partially founded in the different quantification methods that are implemented. So far, TID research has solely focused on sports involving the lower-body muscles as prime movers (e.g. running). Sprint kayaking imposes high demands on the upper-body endurance capacity of the athlete. As there are structural and physiological differences between upper- and lower-body musculature, TID in kayaking should be different to lower-body dominant sports. Therefore, we aimed to compare the training intensity distribution during an 8-wk macrocycle in a group of highly trained sprint kayakers employing three different methods of training intensity quantification. METHODS: Heart rate (HR) and velocity during on-water training of nine highly trained German sprint kayakers were recorded during the final 8 weeks of a competition period leading to the national championships. The fractional analysis of TID was based on three zones (Z) derived from either HR (TIDBla-HR) or velocity (TIDBla-V) based on blood lactate (Bla) concentrations (Z1 ≤ 2.5 mmol L-1 Bla, Z2 = 2.5-4.0 mmol L-1 Bla, Z3 ≥ 4.0 mmol L-1 Bla) of an incremental test or the 1000-m race pace (TIDRace): Z1 ≤ 85% of race pace, Z2 = 86-95% and Z3 ≥ 95%. RESULTS: TIDBla-V (Z1: 68%, Z2: 14%, Z3: 18%) differed from TIDBla-HR (Z1: 91%, Z2: 6%, Z3: 3%) in each zone (all p < 0.01). TIDRace (Z1: 73%, Z2: 20%, Z3: 7%) differed to Z3 in TIDBla-V (p < 0.01) and all three TIDBla-HR zones (all p < 0.01). Individual analysis revealed ranges of Z1, Z2, Z3 fractions for TIDBla-HR of 85-98%, 2-11% and 0.1-6%. For TIDBla-V, the individual ranges were 41-82% (Z1), 6-30% (Z2) and 8-30% (Z3) and for TIDRace 64-81% (Z1), 14-29% (Z2) and 4-10% (Z3). CONCLUSION: The results show that the method of training intensity quantification substantially affects the fraction of TID in well-trained sprint kayakers. TIDRace determination shows low interindividual variation compared to the physiologically based TIDBla-HR and TIDBla-V. Depending on the aim of the analysis TIDRace, TIDBla-HR and TIDBla-V have advantages as well as drawbacks and may be implemented in conjunction to maximize adaptation.

Monitoring and adapting endurance training on the basis of heart rate variability monitored by wearable technologies: A systematic review with meta-analysis.

OBJECTIVES: To systematically perform a meta-analysis of the scientific literature to determine whether the outcomes of endurance training based on heart rate variability (HRV) are more favorable than those of predefined training. DESIGN: Systematic review and meta-analysis. METHODS: PubMed and Web of Science were searched systematically in March of 2020 using keywords related to endurance, the ANS, and training. To compare the outcomes of HRV-guided and predefined training, Hedges' g effect size and associated 95% confidence intervals were calculated. RESULTS: A total of 8 studies (198 participants) were identified comprising 9 interventions involving a variety of approaches. Compared to predefined training, most HRV-guided interventions included fewer moderate- and/or high-intensity training sessions. Fixed effects meta-analysis revealed a significant medium-sized positive effect of HRV-guided training on submaximal physiological parameters (g = 0.296, 95% CI 0.031 to 0.562, p = 0.028), but its effects on performance (g = 0.079, 95% CI -0.050 to 0.393, p = 0.597) and V̇O2peak (g = 0.171, 95% CI -0.213 to 0.371, p = 0.130) were small and not statistically significant. Moreover, with regards to performance, HRV-guided training was associated with fewer non-responders and more positive responders. CONCLUSIONS: In comparison to predefined training, HRV-guided endurance training had a medium-sized effect on submaximal physiological parameters, but only a small and non-significant influence on performance and V̇O2peak. There were fewer non-responders regarding performance with HRV-based training.

Cardiorespiratory, Metabolic and Perceived Responses to Electrical Stimulation of Upper-Body Muscles While Performing Arm Cycling.

This study was designed to assess systemic cardio-respiratory, metabolic and perceived responses to incremental arm cycling with concurrent electrical myostimulation (EMS). Eleven participants (24 ± 3 yrs; 182 ± 10 cm; 86 ± 16.8 kg) performed two incremental tests involving arm cycling until volitional exhaustion was reached with and without EMS of upper-body muscles. The peak power output was 10.1% lower during arm cycling with (128 ± 30 W) than without EMS (141 ± 25 W, p = 0.01; d = 0.47). In addition, the heart rate (2-9%), oxygen uptake (7-15%), blood lactate concentration (8-46%) and ratings of perceived exertion (4-14%) while performing submaximal arm cycling with EMS were all higher with than without EMS (all p < 0.05). Upon exhaustion, the heart rate, oxygen uptake, lactate concentration, and ratings of perceived exertion did not differ between the two conditions (all p > 0.05). In conclusion, arm cycling with EMS induced more pronounced cardio-respiratory, metabolic and perceived responses, especially during submaximal arm cycling. This form of exercise with stimulation might be beneficial for a variety of athletes competing in sports involving considerable generation of work by the upper body (e.g., kayaking, cross-country skiing, swimming, rowing and various parasports).

Comparison of Physiological Parameters During On-Water and Ergometer Kayaking and Their Relationship to Performance in Sprint Kayak Competitions.

PURPOSE: (1) To compare various physiological indicators of performance during a 5 × 1500-m incremental kayak test performed on an ergometer and on-water and (2) to analyze the relationships between these indicators and the actual competition performance of elite sprint kayakers, aiming to provide information to coaches for evaluating and planning training on-water. METHODS: A total of 14 male and female German elite sprint kayakers performed an incremental test both on an ergometer and on-water. The tissue saturation index of the musculus (m.) biceps brachii, oxygen consumption, ratings of perceived exertion, and levels of blood lactate were measured and compared with actual racing times. In addition, power output was monitored during ergometer testing only. RESULTS: Oxygen consumption during the fourth (P = .02; d = 0.32) and final (fifth; P < .001; d = 0.32) steps of incremental testing was higher on-water than on the ergometer. The tissue saturation index of the m. biceps brachii was approximately 21% higher at the end of the ergometer test (P = .002; d = 1.14). During the second (P = .01; d = 0.78), third (P = .005; d = 0.93), and fourth stages (P = .005; d = 1.02), the ratings of perceived exertion for ergometer kayaking was higher. During the final step, power output was most closely correlated to 200- (r = .88), 500- (r = .93), and 1000-m (r = .86) racing times (all Ps < .01). CONCLUSIONS: During high-intensity kayaking on an ergometer or on-water, the oxygen consumption and tissue saturation index of the m. biceps brachii differ. Furthermore, at moderate to submaximal intensities, the ratings of perceived exertion were higher for ergometer than for on-water kayaking. Finally, of all parameters assessed, the power output during ergometer kayaking exhibited the strongest correlation with actual racing performance.

The effects of 12 weeks of functional strength training on muscle strength, volume and activity upon exposure to elevated Gz forces in high-performance aircraft personnel.

BACKGROUND: Technological advancements in modern military and acrobatic jet planes have resulted in extraordinary psychophysiological loads being exerted upon flying personnel, including inducing neck and back pain. The purpose of this study was to examine the effects of 12 weeks of functional strength training on 1) the volume and strength of the neck and shoulder muscles and 2) muscular activity upon exposure to helmets of different masses and elevated Gz forces in a long-arm centrifuge in high-performance aircraft personnel. METHODS: Eighteen participants underwent 12 weeks of functional strength training (n = 12) or the control protocol (n = 6) without additional strength training. Pre- and post-intervention tests included evaluations of isometric strength of the head extensor muscles, flexion, and lateral flexion and rotation, as well as magnetic resonance imaging (MRI) to measure the volume of the m. sternocleidomastoideus, m. trapezius, and deep neck muscles. Furthermore, during a long-arm centrifuge (+ 1.4 and + 3 Gz) protocol, the muscular activity levels of the m. sternocleidomastoideus, m. trapezius and m. erector spinae muscles were assessed without a flight helmet, with a helmet, and with a helmet and night vision goggles. Each participant's perception of muscular strain was noted immediately after the long-arm centrifuge protocol. RESULTS: The maximal isometric strength in all exercises and muscle volumes increased in the training group but not the control group (P < 0.05). Relative muscle activity (%MVC) with a helmet decreased after the intervention in the training but not the control group (P = 0.01). Relative muscle activity while wearing a helmet and night vision goggles was higher after intervention in the control group than in the training group (P < 0.01). The perceived muscular strain of the neck muscles induced by the long-arm centrifuge did not differ between the groups. CONCLUSION: Twelve weeks of functional strength training improves the maximal isometric strength and volume of neck and shoulder muscles and leads to lower relative muscle activation upon exposure to elevated Gz forces in a long-arm centrifuge.

The Relationship Between the Distribution of Training Intensity and Performance of Kayak and Canoe Sprinters: A Retrospective Observational Analysis of One Season of Competition.

Purpose: To evaluate retrospectively the training intensity distribution (TID) among highly trained canoe sprinters during a single season and to relate TID to changes in performance. Methods: The heart rates during on-water training by 11 German sprint kayakers (7 women, 4 men) and one male canoeist were monitored during preparation periods (PP) 1 and 2, as well as during the period of competition (CP) (total monitoring period: 37 weeks). The zones of training intensity (Z) were defined as Z1 [<80% of peak oxygen consumption (VO2peak)], Z2 (81-87% VO2peak) and Z3 (>87% VO2peak), as determined by 4 × 1,500-m incremental testing on-water. Prior to and after each period, the time required to complete the last 1,500-m stage (all-out) of the incremental test (1,500-m time-trial), velocities associated with 2 and 4 mmol·L-1 blood lactate (v2[BLa], v4[BLa]) and VO2peak were determined. Results: During each period, the mean TID for the entire group was pyramidal (PP1: 84/12/4%, PP2: 80/12/8% and CP: 91/5/4% for Z1, Z2, Z3) and total training time on-water increased from 5.0 ± 0.9 h (PP1) to 6.1 ± 0.9 h (PP2) and 6.5 ± 1.0 h (CP). The individual ranges for Z1, Z2 and Z3 were 61-96, 2-26 and 0-19%. During PP2 VO2peak (25.5 ± 11.4%) markedly increased compared to PP1 and CP and during PP1 v2[bla] (3.6 ± 3.4%) showed greater improvement compared to PP2, but not to CP. All variables related to performance improved as the season progressed, but no other effects were observed. With respect to time-trial performance, the time spent in Z1 (r = 0.66, p = 0.01) and total time in all three zones (r = 0.66, p = 0.01) showed positive correlations, while the time spent in Z2 (r = -0.57, p = 0.04) was negatively correlated. Conclusions: This seasonal analysis of the effects of training revealed extensive inter-individual variability. Overall, TID was pyramidal during the entire period of observation, with a tendency toward improvement in VO2peak, v2[bla], v4[bla] and time-trial performance. During PP2, when the COVID-19 lockdown was in place, the proportion of time spent in Z3 doubled, while that spent in Z1 was lowered; the total time spent training on water increased; these changes may have accentuated the improvement in performance during this period. A further increase in total on-water training time during CP was made possible by reductions in the proportions of time spent in Z2 and Z3, so that more fractions of time was spent in Z1.

The Impact of the German Strategy for Containment of Coronavirus SARS-CoV-2 on Training Characteristics, Physical Activity and Sleep of Highly Trained Kayakers and Canoeists: A Retrospective Observational Study.

Aim: To characterize the impact of the German strategy for containment of Coronavirus SARS-CoV-2 (social distancing and lockdown) on the training, other habitual physical activity, and sleep in highly trained kayakers and canoeists. Method: During the 4 weeks immediately prior to and following the beginning of the German government's strategy for containment of Coronavirus SARS-CoV-2 on March 23, 2020, 14 highly trained athletes (VO2peak: 3,162 ± 774 ml/min; 500-m best time: 117.9 ± 7.9 s) wore a multi-sensor smartwatch to allow continuous assessment of heart rate, physical activity, and sleep duration. Result: In comparison to before lockdown, the overall weekly training time and the average length of each session of training during the lockdown decreased by 27.6% (P = 0.02; d = 0.91) and 15.4% (P = 0.36; d = 0.36), respectively. At the same time, the number of sessions involving specific (i.e., canoeing and kayaking) and non-specific (i.e., running, cycling) training, respectively, did not change (P = 0.36-0.37; d = 0.34-0.35). The number of sessions involving strength (+17.4%; P = 0.03; d = 0.89) or other types of training (+16.7%; P = 0.06; d = 0.75) increased during the lockdown with 2.8-17.5% more training time involving a heart rate <60%, 82-88, 89-93, or 94-100% of individual peak heart rate (HRpeak) (P = 0.03-0.86; d = 0.07-1.38), and 4.3-18.7% less time with a heart rate of 60-72 or 73-83% HRpeak (P = < 0.001-0.0.26; d = 0.44-2.24). The daily duration of sleep was ~30 min (6.7%) longer during the lockdown (P < 0.001; d = 1.53) and the overall time spent lying down was 17% greater (P < 0.001; d = 2.26); whereas sitting time (-9.4%; P = 0.003; d = 1.23), the duration of light (15 min; -7.3%; P = 0.04; d = 0.83), and moderate (-18.6%; P = 0.01; d = 1.00) physical activity other than training (-9.4%; P = 0.22; d = 0.00) were all lower during lockdown. Conclusion: The present data revealed that following the German lockdown for containment of the Coronavirus SARS-CoV-2, highly trained kayakers and canoeists spent less overall time training each week (-27.6%) with, on average, shorter training sessions (-15.1%) and less light-to-moderate physical activity outside of training. Moreover, they performed more strength training sessions per week, and all engaged in more training at intensities >82 and <60% of HRpeak and spent longer periods lying down and sleeping during the lockdown.

Intra-Individual and Seasonal Variation of Selected Biomarkers for Internal Load Monitoring in U-19 Soccer Players.

The aim of this study was to investigate inter-day and -week as well as intra- and inter-individual variation of selected biomarkers in high-performance youth soccer players to assist practitioners interpreting player's internal load to counteract underperformance and unwanted health risks. Eleven male youth soccer players were tested multiple times during two 3-week periods at midpoint (3-wkmid) and at the end (3-wkend) of the first half of a German under-19 1. Bundesliga season. The levels of creatine kinase (CK), urea, and C-reactive protein (CRP) were measured during 3-wkmid and 3-wkend each Monday, Wednesday, and Friday. In 3-wkmid the CK median was 14% higher (241 vs. 212 U/L) compared to 3-wkend (P = 0.26, ES = 0.16). Overall, the medians of CK, urea (P = 0.59, ES = 0.08), and CRP (P = 0.56, ES = 0.10) during 3-wkmid did not differ to the values of 3-wkend. Daily coefficient of variations (CVs) ranged from 22 to 71% (CK), 17 to 37% (urea), and 9 to 164% (CRP). Individual medians ranged from 101 to 350 U/L (CK), 23 to 50 mg/dL (urea), and 0.6 to 1.1 mg/L (CRP). High intra-individual variability was demonstrated by large intra-individual CVs (medians: CK 50%, urea 18%, and CRP 45%). Our data show (i) large inter-day and inter-week variability of all biomarkers, depending on the external load and (ii) considerable inter- and intra-individual parameter variations. Creatine kinase concentrations could sensitively reflect soccer-specific loads during the season.

Predefined vs data-guided training prescription based on autonomic nervous system variation: A systematic review.

Monitoring variations in the functioning of the autonomic nervous system may help personalize training of runners and provide more pronounced physiological adaptations and performance improvements. We systematically reviewed the scientific literature comparing physiological adaptations and/or improvements in performance following training based on responses of the autonomic nervous system (ie, changes in heart rate variability) and predefined training. PubMed, SPORTDiscus, and Web of Science were searched systematically in July 2019. Keywords related to endurance, running, autonomic nervous system, and training. Studies were included if they (a) involved interventions consisting predominantly of running training; (b) lasted at least 3 weeks; (c) reported pre- and post-intervention assessment of running performance and/or physiological parameters; (d) included an experimental group performing training adjusted continuously on the basis of alterations in HRV and a control group; and (e) involved healthy runners. Five studies involving six interventions and 166 participants fulfilled our inclusion criteria. Four HRV-based interventions reduced the amount of moderate- and/or high-intensity training significantly. In five interventions, improvements in performance parameters (3000 m, 5000 m, Loadmax, Tlim) were more pronounced following HRV-based training. Peak oxygen uptake ( V ˙ O 2 peak ) and submaximal running parameters (eg, LT1, LT2) improved following both HRV-based and predefined training, with no clear difference in the extent of improvement in V ˙ O 2 peak . Submaximal running parameters tended to improve more following HRV-based training. Research findings to date have been limited and inconsistent. Both HRV-based and predefined training improve running performance and certain submaximal physiological adaptations, with effects of the former training tending to be greater.

Smartwatch-Derived Data and Machine Learning Algorithms Estimate Classes of Ratings of Perceived Exertion in Runners: A Pilot Study.

The rating of perceived exertion (RPE) is a subjective load marker and may assist in individualizing training prescription, particularly by adjusting running intensity. Unfortunately, RPE has shortcomings (e.g., underreporting) and cannot be monitored continuously and automatically throughout a training sessions. In this pilot study, we aimed to predict two classes of RPE ( ≤ 15 "Somewhat hard to hard" on Borg's 6-20 scale vs. RPE > 15 in runners by analyzing data recorded by a commercially-available smartwatch with machine learning algorithms. Twelve trained and untrained runners performed long-continuous runs at a constant self-selected pace to volitional exhaustion. Untrained runners reported their RPE each kilometer, whereas trained runners reported every five kilometers. The kinetics of heart rate, step cadence, and running velocity were recorded continuously ( 1 Hz ) with a commercially-available smartwatch (Polar V800). We trained different machine learning algorithms to estimate the two classes of RPE based on the time series sensor data derived from the smartwatch. Predictions were analyzed in different settings: accuracy overall and per runner type; i.e., accuracy for trained and untrained runners independently. We achieved top accuracies of 84 . 8 for the whole dataset, 81 . 82 for the trained runners, and 86 . 08 for the untrained runners. We predict two classes of RPE with high accuracy using machine learning and smartwatch data. This approach might aid in individualizing training prescriptions.

Validation of the Polar OH1 and M600 optical heart rate sensors during front crawl swim training.

PURPOSE: The Polar OH1 is an optical heart rate (HR) sensor which can be used on different parts of the body. The purpose of the study was to evaluate the validity of the OH1 as well as a wrist worn heart rate device (Polar M600) during swimming. METHODS: Twenty-six well-trained competitive swimmers performed a regular training session including different swimming intensities. During the training the swimmers wore a H10 HR sensor with Polar Pro strap (H10) underneath the swim suit, a Polar OH1 optical HR sensor (OH1) underneath the swimming cap at the temple, and a sports watch with optical HR sensor, Polar M600 smart watch (M600) on the wrist. RESULTS: No difference in HRmax, HRmean and HRmin between H10 and OH1 were evident. The HRmax and HRmean obtained by the M600 was significantly lower than the obtained by H10 and OH1 (p < 0.05). The ICC showed mostly excellent agreements between H10 and OH1 and poor to good agreements between H10 and M600. Bland-Altmann plot for M600 vs. H10 indicates upper and lower limits of agreement of -53.0 to 33.9 beats per minute. For OH1 vs. H10 the upper and lower limits of agreement were -26.9 to 24.7 beats per minute. CONCLUSION: The Polar OH1 optical HR sensor is a valid tool to monitor HR of different intensities during swimming whereas the Polar M600 smart watch as a wrist worn device is less accurate.

Mitochondrial oxygen affinity increases after sprint interval training and is related to the improvement in peak oxygen uptake.

AIMS: The body responds to exercise training by profound adaptations throughout the cardiorespiratory and muscular systems, which may result in improvements in maximal oxygen consumption (VO2 peak) and mitochondrial capacity. By convenience, mitochondrial respiration is often measured at supra-physiological oxygen levels, an approach that ignores any potential regulatory role of mitochondrial affinity for oxygen (p50mito ) at physiological oxygen levels. METHODS: In this study, we examined the p50mito of mitochondria isolated from the Vastus lateralis and Triceps brachii in 12 healthy volunteers before and after a training intervention with seven sessions of sprint interval training using both leg cycling and arm cranking. The changes in p50mito were compared to changes in whole-body VO2 peak. RESULTS: We here show that p50mito is similar in isolated mitochondria from the Vastus (40 ± 3.8 Pa) compared to Triceps (39 ± 3.3) but decreases (mitochondrial oxygen affinity increases) after seven sessions of sprint interval training (to 26 ± 2.2 Pa in Vastus and 22 ± 2.7 Pa in Triceps, both P < .01). The change in VO2 peak modelled from changes in p50mito was correlated to actual measured changes in VO2 peak (R2  = .41, P = .002). CONCLUSION: Together with mitochondrial respiratory capacity, p50mito is a critical factor when measuring mitochondrial function, it can decrease with sprint interval training and should be considered in the integrative analysis of the oxygen cascade from lung to mitochondria.

Within-sport specialisation and entry age as predictors of success among age group swimmers.

Early specialisation versus early diversification in long-term athlete development remains controversial. Although several parameters of sport specialisation have already been explored, this study investigates within-sport specialisation in the careers of young swimmers. In this cohort study, the number of strokes, events and distance categories during childhood and adolescence, as well as entry age were analysed to find potential correlations with success at age 18. Also, national team members were compared to non-members within this cohort. The number of events, strokes or distance categories at a younger age showed a moderate correlation to the best FINA point score at the age of 18, i.e. the greater the diversification, the greater the performance at age 18. The number of events, strokes or distance categories however, showed a stronger correlation when comparing national team members with the non-members. Most of the observed athletes were more likely to have high FINA points at 18 if they had been listed in the top 100 at 11 years of age. Entry age had a strong negative correlation with the FINA point score at 18, i.e. the younger the athlete when entering the top 100, the higher the FINA point score at 18. When national team members were compared to non-national team members, early age of entry into the top 100 showed a greater impact on the national team members. However, being listed in more than one stroke as a child correlates well with success at age 18.