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Institute
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 (HR\(_{max}\)) or peak oxygen uptake (VO\(_{2peak}\)) 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.
Background
Repeated sprint performance is determined by explosive production of power, as well as rapid recovery between successive sprints, and there is evidence that compression garments and sports taping can improve both of these factors.
Methods
In each of two sub-studies, female athletes performed two sets of 30 30-m sprints (one sprint per minute), one set wearing compression garment with adhesive silicone stripes (CGSS) intended to mimic taping and the other with normal clothing, in randomized order. Sub-study 1 (n = 12) focused on cardio-respiratory, metabolic, hemodynamic and perceptual responses, while neuronal and biomechanical parameters were examined in sub-study 2 (n = 12).
Results
In both sub-studies the CGSS improved repeated sprint performance during the final 10 sprints (best P < 0.01, d = 0.61). None of the cardio-respiratory or metabolic variables monitored were altered by wearing this garment (best P = 0.06, d = 0.71). Also during the final 10 sprints, rating of perceived exertion by the upper leg muscles was reduced (P = 0.01, d = 1.1), step length increased (P = 0.01, d = 0.91) and activation of the m. rectus femoris elevated (P = 0.01, d = 1.24), while the hip flexion angle was lowered throughout the protocol (best P < 0.01, d = 2.28) and step frequency (best P = 0.34, d = 0.2) remained unaltered.
Conclusion
Although the physiological parameters monitored were unchanged, the CGSS appears to improve performance during 30 30-m repeated sprints by reducing perceived exertion and altering running technique.
Background
Repeated sprint performance is determined by explosive production of power, as well as rapid recovery between successive sprints, and there is evidence that compression garments and sports taping can improve both of these factors.
Methods
In each of two sub-studies, female athletes performed two sets of 30 30-m sprints (one sprint per minute), one set wearing compression garment with adhesive silicone stripes (CGSS) intended to mimic taping and the other with normal clothing, in randomized order. Sub-study 1 (n = 12) focused on cardio-respiratory, metabolic, hemodynamic and perceptual responses, while neuronal and biomechanical parameters were examined in sub-study 2 (n = 12).
Results
In both sub-studies the CGSS improved repeated sprint performance during the final 10 sprints (best P < 0.01, d = 0.61). None of the cardio-respiratory or metabolic variables monitored were altered by wearing this garment (best P = 0.06, d = 0.71). Also during the final 10 sprints, rating of perceived exertion by the upper leg muscles was reduced (P = 0.01, d = 1.1), step length increased (P = 0.01, d = 0.91) and activation of the m. rectus femoris elevated (P = 0.01, d = 1.24), while the hip flexion angle was lowered throughout the protocol (best P < 0.01, d = 2.28) and step frequency (best P = 0.34, d = 0.2) remained unaltered.
Conclusion
Although the physiological parameters monitored were unchanged, the CGSS appears to improve performance during 30 30-m repeated sprints by reducing perceived exertion and altering running technique.
Athletes schedule their training and recovery in periods, often utilizing a pre-defined strategy. To avoid underperformance and/or compromised health, the external load during training should take into account the individual’s physiological and perceptual responses. No single variable provides an adequate basis for planning, but continuous monitoring of a combination of several indicators of internal and external load during training, recovery and off-training as well may allow individual responsive adjustments of a training program in an effective manner. From a practical perspective, including that of coaches, monitoring of potential changes in health and performance should ideally be valid, reliable and sensitive, as well as time-efficient, easily applicable, non-fatiguing and as non-invasive as possible. Accordingly, smartphone applications, wearable sensors and point-of-care testing appear to offer a suitable monitoring framework allowing responsive adjustments to exercise prescription. Here, we outline 24-h monitoring of selected parameters by these technologies that (i) allows responsive adjustments of exercise programs, (ii) enhances performance and/or (iii) reduces the risk for overuse, injury and/or illness.
Although it is becoming increasingly popular to monitor parameters related to training, recovery, and health with wearable sensor technology (wearables), scientific evaluation of the reliability, sensitivity, and validity of such data is limited and, where available, has involved a wide variety of approaches. To improve the trustworthiness of data collected by wearables and facilitate comparisons, we have outlined recommendations for standardized evaluation. We discuss the wearable devices themselves, as well as experimental and statistical considerations. Adherence to these recommendations should be beneficial not only for the individual, but also for regulatory organizations and insurance companies.
Background: Physical activity reduces the incidences of noncommunicable diseases, obesity, and mortality, but an inactive lifestyle is becoming increasingly common. Innovative approaches to monitor and promote physical activity are warranted. While individual monitoring of physical activity aids in the design of effective interventions to enhance physical activity, a basic prerequisite is that the monitoring devices exhibit high validity.
Objective: Our goal was to assess the validity of monitoring heart rate (HR) and energy expenditure (EE) while sitting or performing light-to-vigorous physical activity with 4 popular wrist-worn wearables (Apple Watch Series 4, Polar Vantage V, Garmin Fenix 5, and Fitbit Versa).
Methods: While wearing the 4 different wearables, 25 individuals performed 5 minutes each of sitting, walking, and running at different velocities (ie, 1.1 m/s, 1.9 m/s, 2.7 m/s, 3.6 m/s, and 4.1 m/s), as well as intermittent sprints. HR and EE were compared to common criterion measures: Polar-H7 chest belt for HR and indirect calorimetry for EE.
Results: While monitoring HR at different exercise intensities, the standardized typical errors of the estimates were 0.09-0.62, 0.13-0.88, 0.62-1.24, and 0.47-1.94 for the Apple Watch Series 4, Polar Vantage V, Garmin Fenix 5, and Fitbit Versa, respectively. Depending on exercise intensity, the corresponding coefficients of variation were 0.9%-4.3%, 2.2%-6.7%, 2.9%-9.2%, and 4.1%-19.1%, respectively, for the 4 wearables. While monitoring EE at different exercise intensities, the standardized typical errors of the estimates were 0.34-1.84, 0.32-1.33, 0.46-4.86, and 0.41-1.65 for the Apple Watch Series 4, Polar Vantage V, Garmin Fenix 5, and Fitbit Versa, respectively. Depending on exercise intensity, the corresponding coefficients of variation were 13.5%-27.1%, 16.3%-28.0%, 15.9%-34.5%, and 8.0%-32.3%, respectively.
Conclusions: The Apple Watch Series 4 provides the highest validity (ie, smallest error rates) when measuring HR while sitting or performing light-to-vigorous physical activity, followed by the Polar Vantage V, Garmin Fenix 5, and Fitbit Versa, in that order. The Apple Watch Series 4 and Polar Vantage V are suitable for valid HR measurements at the intensities tested, but HR data provided by the Garmin Fenix 5 and Fitbit Versa should be interpreted with caution due to higher error rates at certain intensities. None of the 4 wrist-worn wearables should be employed to monitor EE at the intensities and durations tested."
Athletes adapt their training daily to optimize performance, as well as avoid fatigue, overtraining and other undesirable effects on their health. To optimize training load, each athlete must take his/her own personal objective and subjective characteristics into consideration and an increasing number of wearable technologies (wearables) provide convenient monitoring of various parameters. Accordingly, it is important to help athletes decide which parameters are of primary interest and which wearables can monitor these parameters most effectively. Here, we discuss the wearable technologies available for non-invasive monitoring of various parameters concerning an athlete's training and health. On the basis of these considerations, we suggest directions for future development. Furthermore, we propose that a combination of several wearables is most effective for accessing all relevant parameters, disturbing the athlete as little as possible, and optimizing performance and promoting health.
Background
High-intensity interval training (HIIT) is frequently employed to improve the endurance of various types of athletes. To determine whether youth soccer players may benefit from the intermittent load and time efficiency of HIIT, we performed a meta-analysis of the relevant scientific literature.
Objectives
Our primary objective was to compare changes in various physiological parameters related to the performance of youth soccer players in response to running-based HIIT to the effects of other common training protocols (i.e., small-sided games, technical training and soccer-specific training, or high-volume endurance training). A secondary objective was to compare specifically running-based HIIT to a soccer-specific form of HIIT known as small-sided games (SSG) in this same respect, since this latter type of training is being discussed extensively by coaches.
Method
A systematic search of the PubMed, SPORTDiscus, and Web of Science databases was performed in August of 2017 and updated during the review process in December of 2018. The criteria for inclusion of articles for analysis were as follows: (1) comparison of HIIT to SSG or some other training protocol employing a pre-post design, (2) involvement of healthy young athletes (≤ 18 years old), and (3) assessment of variables related to endurance or soccer performance. Hedges’ g effect size (dppc2) and associated 95% confidence intervals for the comparison of the responses to HIIT and other interventions were calculated.
Results
Nine studies, involving 232 young soccer players (mean age 16.2 ± 1.6 years), were examined. Endurance training in the form of HIIT or SSG produced similar positive effects on most parameters assessed, including peak oxygen uptake and maximal running performance during incremental running (expressed as Vmax or maximal aerobic speed (MAS)), shuttle runs (expressed as the distance covered or time to exhaustion), and time-trials, as well as submaximal variables such as running economy and running velocity at the lactate threshold. HIIT induced a moderate improvement in soccer-related tests involving technical exercises with the soccer ball and other game-specific parameters (i.e., total distance covered, number of sprints, and number of involvements with the ball). Neuromuscular parameters were largely unaffected by HIIT or SSG.
Conclusion
The present meta-analysis indicates that HIIT and SSG have equally beneficial impacts on variables related to the endurance and soccer-specific performance of youth soccer players, but little influence on neuromuscular performance.