Assessment of Maximum Oxygen Uptake in Elite Youth Soccer Players: A Comparative Analysis of Smartwatch Technology, Yoyo Intermittent Recovery Test 2, and Respiratory Gas Analysis.

The maximum oxygen uptake (VO2max) is a critical factor for endurance performance in soccer. Novel wearable technology may allow frequent assessment of V̇O2max during non-fatiguing warm-up runs of soccer players with minimal interference to soccer practice. The aim of this study was to assess the validity of VO2max provided by a consumer grade smartwatch (Garmin Forerunner 245, Garmin, Olathe, USA, Software:13.00) and the YoYo Intermittent Recovery Run 2 (YYIR2) by comparing it with respiratory gas analysis. 24 trained male youth soccer players performed different tests to assess VO2max: i) a treadmill test employing respiratory gas analysis, ii) YYIR2 and iii) during a non-fatiguing warm-up run of 10 min wearing a smartwatch as recommended by the device-manufacturer on 3 different days within 2 weeks. As the device-manufacturer indicates that validity of smartwatch-derived VO2max may differ with an increase in runs, 16 players performed a second run with the smartwatch to test this claim. The main evidence revealed that the smartwatch showed an ICC of 0.37 [95% CI: -0.25; 0.71] a mean absolute percentage error (MAPE) of 5.58% after one run, as well as an ICC of 0.54 [95% CI: -0.3; 8.4] and a MAPE of 1.06% after the second run with the smartwatch. The YYIR2 showed an ICC of 0.17 [95% CI: -5.7; 0.6]; and MAPE of 4.2%. When using the smartwatch for VO2max assessment in a non-fatiguing run as a warm-up, as suggested by the device manufacturer before soccer practice, the MAPE diminishes after two runs. Therefore, for more accurate VO2max assessment with the smartwatch, we recommend to perform at least two runs to reduce the MAPE and enhance the validity of the findings.

Reliability of power output, maximal rate of capillary blood lactate accumulation, and phosphagen contribution time following 15-s sprint cycling in amateur cyclists.

Based on Mader's mathematical model, the rate of capillary blood lactate concentration (νLamax) following intense exercise is thought to reflect the maximal glycolytic rate. We aimed to investigate the reliability of important variables of Mader's model (i.e. power output, lactate accumulation, predominant phosphagen contribution time frames (tP Cr)) and resulting νLamax values derived during and after a 15-s cycling sprint. Fifty cyclists performed a 15-s all-out sprint test on a Cyclus2 ergometer three times. The first sprint test was considered a familiarization trial. Capillary blood was sampled before and every minute (for 8 min) after the sprint to determine νLamax. Test-retest analysis between T2 and T3 revealed excellent reliability for power output (Pmean and Ppeak; ICC = 0.99, 0.99), ∆La and νLamax with tPCr of 3.5 s (ICC = 0.91, 0.91). νLamax calculated with tPCr = tP peak (ICC = 0.87) and tP Cr = tPpeak-3.5% (ICC = 0.79) revealed good reliability. tPpeak and tPpeak-3.5% revealed only poor and moderate reliability (ICC = 0.41, 0.52). Power output and ∆La are reliable parameters in the context of this test. Depending on tPCr, reliability of νLamax varies considerably with tP Cr of 3.5 s showing excellent reliability. We recommend standardization of this type of testing especially tP Cr.

The exercise-app Axia for axial spondyloarthritis enhances the home-based exercise frequency in axial spondyloarthritis patients - A cross-sectional survey.

BACKGROUND: Patients with axial spondyloarthritis (axSpA) benefit from regular home-based exercise (HbE). In spite of recommendations, a relevant proportion of German axSpA patients does not adhere to recommended HbE practices. To enhance HbE care, we developed the novel digital therapeutic (DTx) "Axia" compliant with the European medical device regulation (MDR). Axia offers a modern app-based HbE solution with patient educative content and further integrated features. OBJECTIVE: We aimed to assess Axia's efficacy, attractiveness, and functionality through a survey among axSpA-patients involved in the first user tests. METHODS: A mixed-method online questionnaire with 38 items was administered to 37 axSpA volunteers after using Axia. Numeric rating scales (NRS) and likelihood scales were primarily used. RESULTS: HbE frequency significantly increased from a median of 1 day/week to 6 days/week (p < 0.001) by using Axia. Existing HbE practitioners also increased their frequency (median of 4 days/week before, 6 days/week with Axia, p < 0.05). Axia received a median rating of 5 out of 5 stars. On NRS scales, Axia scored a median of 9 for intuitiveness and design, and a median of 8 for entertainment. 64.9% reported improved range of motion, 43.2% reported reduced pain, and 93.6% enhanced disease-specific knowledge. All users recommended Axia to other patients. CONCLUSION: Axia increases axSpA patients HbE frequency, possibly due to its good intuitiveness and design, leading to reduction in pain and subjective improvement of range of motion. This warrants further investigation in large randomized controlled interventional trials to establish its efficacy conclusively and patients adherence to HbE.

Acute physiological, biomechanical, and perceptual responses of runners wearing downward-curved carbon fiber insoles.

In a randomized controlled cross-over study ten male runners (26.7 ± 4.9 years; recent 5-km time: 18:37 ± 1:07 min:s) performed an incremental treadmill test (ITT) and a 3-km time trial (3-km TT) on a treadmill while wearing either carbon fiber insoles with downwards curvature or insoles made of butyl rubber (control condition) in light road racing shoes (Saucony Fastwitch 9). Oxygen uptake, respiratory exchange ratio, heart rate, blood lactate concentration, stride frequency, stride length and time to exhaustion were assessed during ITT. After ITT, all runners rated their perceived exertion, perceived shoe comfort and perceived shoe performance. Running time, heart rate, blood lactate levels, stride frequency and stride length were recorded during, and shoe comfort and shoe performance after, the 3-km TT. All parameters obtained during or after the ITT did not differ between the two conditions [range: p = 0.188 to 0.948 (alpha value: 0.05); Cohen's d = 0.021 to 0.479] despite the rating of shoe comfort showing better scores for the control insoles (p = 0.001; d = -1.646). All parameters during and after the 3-km TT showed no differences (p = 0.200 to 1.000; d = 0.000 to 0.501) between both conditions except for shoe comfort showing better scores for control insoles (p = 0.017; d = -0.919). Running with carbon fiber insoles with downwards curvature did not change running performance or any submaximal or maximal physiological or biomechanical parameter and perceived exertion compared to control condition. Shoe comfort is impaired while running with carbon fiber insoles. Wearing carbon fiber insoles with downwards curvature during treadmill running is not beneficial when compared to running with control insoles.

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.

The proportional distribution of training by elite endurance athletes at different intensities during different phases of the season.

The present review examines retrospective analyses of training intensity distribution (TID), i.e., the proportion of training at moderate (Zone 1, Z1), heavy (Z2) and severe (Z3) intensity by elite-to-world-class endurance athletes during different phases of the season. In addition, we discuss potential implications of our findings for research in this field, as well as for training by these athletes. Altogether, we included 175 TIDs, of which 120 quantified exercise intensity on the basis of heart rate and measured time-in-zone or employed variations of the session goal approach, with demarcation of zones of exercise intensity based on physiological parameters. Notably, 49% of the TIDs were single-case studies, predominantly concerning cross-country skiing and/or the biathlon. Eighty-nine TIDs were pyramidal (Z1 > Z2 > Z3), 65 polarized (Z1 > Z3 > Z2) and 8 "threshold" (Z2 > Z1 = Z3). However, these relative numbers varied between sports and the particular phases of the season. In 91% (n = 160) of the TIDs >60% of the endurance exercise was of low intensity. Regardless of the approach to quantification or phase of the season, cyclists and swimmers were found to perform a lower proportion of exercise in Z1 (<72%) and higher proportion in Z2 (>16%) than athletes involved in the triathlon, speed skating, rowing, running, cross-country skiing or biathlon (>80% in Z1 and <12% in Z2 in all these cases). For most of the athletes their proportion of heavy-to-severe exercise was higher during the period of competition than during the preparatory phase, although with considerable variability between sports. In conclusion, the existing literature in this area does not allow general conclusions to be drawn. The methods utilized for quantification vary widely and, moreover, contextual information concerning the mode of exercise, environmental conditions, and biomechanical aspects of the exercise is often lacking. Therefore, we recommend a more comprehensive approach in connection with future investigations on the TIDs of athletes involved in different endurance sports.

Strengths, weaknesses, opportunities, and threats associated with the application of artificial intelligence in connection with sport research, coaching, and optimization of athletic performance: a brief SWOT analysis.

Here, we performed a non-systematic analysis of the strength, weaknesses, opportunities, and threats (SWOT) associated with the application of artificial intelligence to sports research, coaching and optimization of athletic performance. The strength of AI with regards to applied sports research, coaching and athletic performance involve the automation of time-consuming tasks, processing and analysis of large amounts of data, and recognition of complex patterns and relationships. However, it is also essential to be aware of the weaknesses associated with the integration of AI into this field. For instance, it is imperative that the data employed to train the AI system be both diverse and complete, in addition to as unbiased as possible with respect to factors such as the gender, level of performance, and experience of an athlete. Other challenges include e.g., limited adaptability to novel situations and the cost and other resources required. Opportunities include the possibility to monitor athletes both long-term and in real-time, the potential discovery of novel indicators of performance, and prediction of risk for future injury. Leveraging these opportunities can transform athletic development and the practice of sports science in general. Threats include over-dependence on technology, less involvement of human expertise, risks with respect to data privacy, breaching of the integrity and manipulation of data, and resistance to adopting such new technology. Understanding and addressing these SWOT factors is essential for maximizing the benefits of AI while mitigating its risks, thereby paving the way for its successful integration into sport science research, coaching, and optimization of athletic performance.

Genetics and athletic performance: a systematic SWOT analysis of non-systematic reviews.

Exercise genetics/genomics is a growing research discipline comprising several Strengths and Opportunities but also deals with Weaknesses and Threats. This "systematic SWOT overview of non-systematic reviews" (sSWOT) aimed to identify the Strengths, Weaknesses, Opportunities, and Threats linked to exercise genetics/genomics. A systematic search was conducted in the Medline and Embase databases for non-systematic reviews to provide a comprehensive overview of the current literature/research area. The extracted data was thematically analyzed, coded, and categorized into SWOT clusters. In the 45 included reviews five Strengths, nine Weaknesses, six Opportunities, and three Threats were identified. The cluster of Strengths included "advances in technology", "empirical evidence", "growing research discipline", the "establishment of consortia", and the "acceptance/accessibility of genetic testing". The Weaknesses were linked to a "low research quality", the "complexity of exercise-related traits", "low generalizability", "high costs", "genotype scores", "reporting bias", "invasive methods", "research progress", and "causality". The Opportunities comprised of "precision exercise", "omics", "multicenter studies", as well as "genetic testing" as "commercial"-, "screening"-, and "anti-doping" detection tool. The Threats were related to "ethical issues", "direct-to-consumer genetic testing companies", and "gene doping". This overview of the present state of the art research in sport genetics/genomics indicates a field with great potential, while also drawing attention to the necessity for additional advancement in methodological and ethical guidance to mitigate the recognized Weaknesses and Threats. The recognized Strengths and Opportunities substantiate the capability of genetics/genomics to make significant contributions to the performance and wellbeing of athletes.

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.

Factors associated with high-level endurance performance: An expert consensus derived via the Delphi technique.

There is little agreement on the factors influencing endurance performance. Endurance performance often is described by surrogate variables such as maximum oxygen consumption, lactate threshold, and running economy. However, other factors also determine success and progression of high-level endurance athletes. Therefore, the aim was to identify the relevant factors for endurance performance assessed by international experts by adhering to a structured communication method (i.e., Delphi technique). Three anonymous evaluation rounds were conducted initiated by a list of candidate factors (n = 120) serving as baseline input variables. The items that achieved ≥70% of agreement in round 1 were re-evaluated in a second round. Items with a level of agreement of ≥70% in round 2 reached consensus and items with a level of agreement of 40-69% in round 2 were re-rated in a third round followed by a consensus meeting. Round 1 comprised of 27 panellists (n = 24 male) and in round 2 and 3 18 (n = 15 male) of the 27 panellists remained. Thus, the final endurance expert panel comprised of 18 international experts (n = 15 male) with 20 years of experience on average. The consensus report identified the following 26 factors: endurance capacity, running economy, maximal oxygen consumption, recovery speed, carbohydrate metabolism, glycolysis capacity, lactate threshold, fat metabolism, number of erythrocytes, iron deficiency, muscle fibre type, mitochondrial biogenesis, hydrogen ion buffering, testosterone, erythropoietin, cortisol, hydration status, vitamin D deficiency, risk of non-functional overreaching and stress fracture, healing function of skeletal tissue, motivation, stress resistance, confidence, sleep quality, and fatigue. This study provides an expert-derived summary including 26 key factors for endurance performance, the "FENDLE" factors (FENDLE = Factors for ENDurance Level). This consensus report may assist to optimize sophisticated diagnostics, personalized training strategies and technology.

Genetics of long-distance runners and road cyclists-A systematic review with meta-analysis.

The aim of this systematic review and meta-analysis was to identify the genetic variants of (inter)national competing long-distance runners and road cyclists compared with controls. The Medline and Embase databases were searched until 15 November 2021. Eligible articles included genetic epidemiological studies published in English. A homogenous group of endurance athletes competing at (inter)national level and sedentary controls were included. Pooled odds ratios based on the genotype frequency with corresponding 95% confidence intervals (95%CI) were calculated using random effects models. Heterogeneity was addressed by Q-statistics, and I2 . Sources of heterogeneity were examined by meta-regression and risk of bias was assessed with the Clark Baudouin scale. This systematic review comprised of 43 studies including a total of 3938 athletes and 10 752 controls in the pooled analysis. Of the 42 identified genetic variants, 13 were investigated in independent studies. Significant associations were found for five polymorphisms. Pooled odds ratio [95%CI] favoring athletes compared with controls was 1.42 [1.12-1.81] for ACE II (I/D), 1.66 [1.26-2.19] for ACTN3 TT (rs1815739), 1.75 [1.34-2.29] for PPARGC1A GG (rs8192678), 2.23 [1.42-3.51] for AMPD1 CC (rs17602729), and 2.85 [1.27-6.39] for HFE GG + CG (rs1799945). Risk of bias was low in 25 (58%) and unclear in 18 (42%) articles. Heterogeneity of the results was low (0%-20%) except for HFE (71%), GNB3 (80%), and NOS3 (76%). (Inter)national competing runners and cyclists have a higher probability to carry specific genetic variants compared with controls. This study confirms that (inter)national competing endurance athletes constitute a unique genetic make-up, which likely contributes to their performance level.

Type and intensity distribution of structured and incidental lifestyle physical activity of students and office workers: a retrospective content analysis.

BACKGROUND: Physical activity (PA) guidelines acknowledge the health benefits of regular moderate-to-vigorous physical activity (MVPA) regardless of bout duration. However, little knowledge exists concerning the type and intensity distribution of structured and incidental lifestyle PA of students and office workers. The present study aimed to i) assess the duration and distribution of intensity of MVPAs during waking hours ≥50% of heart rate reserve (HRR), ii) to identify the type of PA through diary assessment, iii) to assign these activities into structured and lifestyle incidental PA, and iv) to compare this information between students and office workers. METHODS: Twenty-three healthy participants (11 students, 12 office workers) recorded heart rate (HR) with a wrist-worn HR monitor (Polar M600) and filled out a PA diary throughout seven consecutive days (i.e. ≥ 8 waking h/day). Relative HR zones were calculated, and PA diary information was coded using the Compendium of PA. We matched HR data with the reported PA and identified PA bouts during waking time ≥ 50% HRR concerning duration, HRR zone, type of PA, and assigned each activity to incidental and structured PA. Descriptive measures for time spend in different HRR zones and differences between students and office workers were calculated. RESULTS: In total, we analyzed 276.894 s (76 h 54 min 54 s) of waking time in HRR zones ≥50% and identified 169 different types of PA. The participants spend 31.9 ± 27.1 min/day or 3.9 ± 3.2% of their waking time in zones of ≥50% HRR with no difference between students and office workers (p > 0.01). The proportion of assigned incidental lifestyle PA was 76.9 ± 22.5%. CONCLUSIONS: The present study provides initial insights regarding the type, amount, and distribution of intensity of structured and incidental lifestyle PA ≥ 50% HRR. Findings show a substantial amount of incidental lifestyle PA during waking hours and display the importance of promoting a physically active lifestyle. Future research could employ ambulatory assessments with integrated electronic diaries to detect information on the type and context of MVPA during the day.

Effects of High-Intensity Interval Training in School on the Physical Performance and Health of Children and Adolescents: A Systematic Review with Meta-Analysis.

BACKGROUND: Performance of high-intensity interval training (HIIT) by children and adolescents improves physical and health-related fitness, as well as cardiometabolic risk factors. OBJECTIVES: To assess the impact of HIIT performed at school, i.e. both in connection with physical education (intra-PE) and extracurricular sports activities (extra-PE), on the physical fitness and health of children and adolescents. METHODS: PubMed and SPORTDiscus were searched systematically utilizing the following criteria for inclusion: (1) healthy children and adolescents (5-18 years old) of normal weight; (2) HIIT performed intra- and/or extra-PE for at least 5 days at an intensity ≥ 80% of maximal heart rate (HRmax) or peak oxygen uptake (VO2peak) or as Functional HIIT; (3) comparison with a control (HIIT versus alternative interventions); and (4) pre- and post-analysis of parameters related to physical fitness and health. The outcomes with HIIT and the control interventions were compared utilizing Hedges' g effect size (ES) and associated 95% confidence intervals. RESULTS: Eleven studies involving 707 participants who performed intra-PE and 388 participants extra-PE HIIT were included. In comparison with the control interventions, intra-PE HIIT improved mean ES for neuromuscular and anaerobic performance (ES jump performance: 5.89 ± 5.67 (range 1.88-9.90); ES number of push-ups: 6.22 (range n.a.); ES number of sit-ups: 2.66 ± 2.02 (range 1.24-4.09)), as well as ES fasting glucose levels (- 2.68 (range n.a.)) more effectively, with large effect sizes. Extra-PE HIIT improved mean ES for neuromuscular and anaerobic performance (ES jump performance: 1.81 (range n.a.); ES number of sit-ups: 2.60 (range n.a.)) to an even greater extent, again with large effect sizes. Neither form of HIIT was more beneficial for parameters related to cardiorespiratory fitness than the control interventions. CONCLUSION: Compared to other forms of exercise (e.g. low-to-moderate-intensity running or walking), both intra- and extra-PE HIIT result in greater improvements in neuromuscular and anaerobic performance, as well as in fasting levels of glucose in school children.

Repeated Sprint Protocols With Standardized Versus Self-Selected Recovery Periods in Elite Youth Soccer Players: Can They Pace Themselves? A Replication Study.

PURPOSE: Replicating the studies of Gibson et al and Brownstein et al to assess performance, and physiological, and perceived variables during a repeated sprint protocol (RSP) with standardized versus self-selected recovery in youth soccer players. METHODS: Nineteen male soccer players (age 13.1 [1.3] y) completed 2 separate RSPs. RSP1: 10 × 30-m sprints with 30-second recovery and RSP2: 10 × 30-m sprints interspersed with self-selected recovery periods. Mean time of both 10 × 30-m RSPs and self-selected recovery periods of RSP2 were assessed. Heart rate, blood lactate concentration, and rates of perceived exertion were measured following RSPs. RESULTS: RSP2 revealed longer recovery periods (RSP1: 30.0 [0.0] s; RSP2: 39.0 [7.7] s; P < .001; effect size d = 1.648) with shorter repeated sprint time (mean 30-m sprint time: RSP1: 4.965 [0.256] s; RSP2: 4.865 [0.227] s; P = .014; d = 0.414). Blood lactate concentration (P = .002-.005; d = 0.730-0.958), heart rate (P < .001; d = 1.353), and rates of perceived exertion (RSP1: 14.9 [1.9]; RSP2: 12.9 [2.1]; P = .016; d = 1.046) were higher following RSP1. CONCLUSION: In contrast to the original studies, the present replication study demonstrated that self-selected recovery periods during a RSP leads to better repeated sprint performance compared with standardized recovery periods in youth soccer players. The better repeated sprint performance with individual recovery durations in RSP2 was achieved with less physiological and perceived effort.

Assessment of Peak Oxygen Uptake with a Smartwatch and its Usefulness for Training of Runners.

Peak oxygen uptake (˙VO2peak) is an important factor contributing to running performance. Wearable technology may allow the assessment of ˙VO2peak more frequently and on a larger scale. We aim to i) validate the ˙VO2peak assessed by a smartwatch (Garmin Forerunner 245), and ii) discuss how this parameter may assist to evaluate and guide training procedures. A total of 23 runners (12 female, 11 male; ˙VO2peak: 48.6±6.8 ml∙min-1∙kg-1) visited the laboratory twice to determine their ˙VO2peak during a treadmill ramp test. Between laboratory visits, participants wore a smartwatch and performed three outdoor runs to obtain ˙VO2peak values provided by the smartwatch. The ˙VO2peak obtained by the criterion measure ranged from 38 to 61 ml∙min-1∙kg-1. The mean absolute percentage error (MAPE) between the smartwatch and the criterion ˙VO2peak was 5.7%. The criterion measure revealed a coefficient of variation of 4.0% over the VO2peak range from 38-61 ml∙min-1∙kg-1. MAPE between the smartwatch and criterion measure was 7.1, 4.1 and -6.2% when analyzing ˙VO2peak ranging from 39-45 ml∙min-1∙kg-1, 45-55 ml∙min-1∙kg-1 or 55-61 ml∙min-1∙kg-1, respectively.

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.

Proof-of-concept and concurrent validity of a prototype headset to assess peak oxygen uptake without a face mask.

OBJECTIVE: Portable gas exchange instruments allow the assessment of peak oxygen uptake (V̇O2peak) but are often bulky, expensive and require wearing a face mask thereby limiting their routine application. A newly developed miniaturized headset (VitaScale, Nuremberg, Germany) may overcome these barriers and allow measuring V̇O2peak without applying a face mask. Here we aimed (i) to disclose the technical setup of a headset incorporating a gas and volume sensor to measure volume flow and expired oxygen concentration and (ii) to assess the concurrent criterion-validity of the headset to measure V̇O2peak in 44 individuals exercising on a stationary cycle ergometer in consideration of the test-retest reliability of the criterion measure. RESULTS: The coefficient of variation (CV%) while measuring V̇O2peak during incremental cycling with the headset was 6.8%. The CV% for reliability of the criterion measure was 4.0% for V̇O2peak. Based on the present data, the headset might offer a new technology for V̇O2peak measurement due to its low-cost and mask-free design.