***TASK*** the task is to summarize an input biomedical literature in six sentences 
    ***INPUT*** the input is a biomedical literature 
    ***OUTPUT*** the output is the summary of an input biomedical literature in six sentences 
    ***DOCUMENTATION*** 
    ***EXAMPLES*** 
    Input: The effects of high-intensity , short- duration , re-warm-ups on team-sport-related performance were investigated . In a r and omised , cross-over study , participants performed 2 × 26-min periods of an intermittent activity protocol ( IAP ) on a non-motorized treadmill , interspersed by 15-min of passive recovery ( CON ) ; 3-min small-sided game ( SSG ) ; or a 5RM leg-press . Measures included counter-movement jump , repeated-sprint , the Loughborough soccer passing test ( LSPT ) , blood lactate concentration , heart-rate , and perceptual measures . Data were analyzed using effect size ( 90 % confidence intervals ) , and percentage change ; determining magnitudes of effects . A 5RM re-warm-up improved flight-time to contraction-time ratio when compared to SSG ( 9.8 % , ES ; 0.5±0.3 ) and CON ( ES : 9.4 % , 0.7±0.5 ) re-warm-ups , remaining higher following the second IAP ( 8.8 % , ES ; 0.5±0.3 and 10.2 % , ES ; 0.6±0.6 , respectively ) . Relative-maximum rate-of-force development was greater in the 5RM condition following the second IAP compared to SSG ( 29.3 % , ES ; 0.7±0.5 ) and CON ( 16.2 % , ES ; 0.6±0.6 ) . Repeated-sprint ability during the second IAP improved in the 5RM re-warm-up ; peak velocity , mean velocity , and acceleration were 4 , 3 , and 18 % greater , respectively . Within groups , the SSG re-warm-up improved LSPT performance post-intervention ; 6.4 % ( ES : 0.6±0.8 ) and following the second IAP 6.2 % ( ES : 0.6±0.6 ) , compared to pre-intervention . A 5RM leg-press re-warm-up improved physical performance , while a SSG re-warm-up enhanced skill execution following st and ardized intermittent exercise Sweeney , KM , Wright , GA , Brice , AG , and Doberstein , ST . The effect of β-alanine supplementation on power performance during repeated sprint activity . J Strength Cond Res 24(1 ) : 79 - 87 , 2010-The dipeptide carnosine has been shown to contribute to the buffer capacity of hydrogen ions ( H+ ) during intense exercise . Increasing skeletal muscle carnosine levels through β-alanine ( BA ) supplementation has been shown to maintain acid-base balance , delay fatigue , and improve exercise performance . We design ed this study to examine the effect of 5 weeks of BA supplementation on repeat high-intensity sprint performance . Nineteen , physically active , college men were divided into 2 groups ( control [ C ] , n = 10 or BA , n = 9 ) . We performed double-blind placebo-controlled study where subjects ingested 4 g per day during the first week and 6 g per day over the next 4 weeks of a placebo ( rice flour ) or a BA supplement . Subjects completed 2 sets of 5 5-second sprints with 45-second recovery separated by 2 minutes of active recovery . All tests were conducted on a non-motorized treadmill against a resistance of 15 % of the participant 's body weight . We recorded horizontal power ( HP ) of the running sprint . Post-exercise capillary blood sample s were analyzed for lactate to determine the metabolic dem and s. There were no significant between-group differences ( p > 0.05 ) in HPpeak or HPmean for the repeat sprint protocol . No significant between-group differences were found for performance decrement ( % fatigue ) for HPpeak or HPmean . In addition , no significant interactions were observed . Post-exercise blood lactate values were similar pre and post supplementation in both groups . The results of this study clearly indicate that 5 weeks of BA supplementation provides no benefit for repeat sprint performance We investigated the acute and chronic responses to multiple sets of repeated-sprint exercise ( RSE ) , focusing on changes in acceleration , intermittent running capacity and physiological responses . Ten healthy young adults ( 7 males , 3 females ) performed an incremental test , a Yo-Yo intermittent recovery test level1 ( Yo-Yo IR1 ) , and one session of RSE . RSE comprised three sets of 5 × 4-s maximal sprints on a non-motorised treadmill , with 20 s of passive recovery between repetitions and 4.5 min of passive recovery between sets . After ten repeated-sprint training sessions , participants repeated all tests . During RSE , performance was determined by measuring acceleration , mean and peak power/velocity . Recovery heart rate ( HR ) , HR variability , and finger-tip capillary lactate concentration ( [ Lac− ] ) were measured . Performance progressively decreased across the three sets of RSE , with the indices of repeated-sprint ability being impaired to a different extent before and after training . Training induced a significant increase ( p < 0.05 ) in all indices of performance , particularly acceleration ( 21.9 , 14.7 and 15.2 % during sets 1 , 2 and 3 , respectively ) . Training significantly increased Yo-Yo IR1 performance by 8 % and decreased Δ[Lac−]/work ratio ( −15.2 , −15.5 , −9.4 % during sets 1 , 2 and 3 , respectively ) and recovery HR during RSE . There were strong correlations between Yo-Yo IR1 performance and indices of RSE performance , especially acceleration post-training ( r = 0.88 , p = 0.004 ) . Repeated-sprint training , comprising only 10 min of exercise overall , effectively improved performance during multiple-set RSE . This exercise model better reflects team-sport activities than single-set RSE . The rapid training-induced improvement in acceleration , quantified here for the first time , has wide applications for professional and recreational sport activities Abstract Reliability refers to the reproducibility of values of a test , assay or other measurement in repeated trials on the same individuals . Better reliability implies better precision of single measurements and better tracking of changes in measurements in research or practical setting s. The main measures of reliability are within-subject r and om variation , systematic change in the mean , and retest correlation . A simple , adaptable form of within-subject variation is the typical ( st and ard ) error of measurement : the st and ard deviation of an individual ’s repeated measurements . For many measurements in sports medicine and science , the typical error is best expressed as a coefficient of variation ( percentage of the mean ) . A biased , more limited form of within-subject variation is the limits of agreement : the 95 % likely range of change of an individual ’s measurements between 2 trials . Systematic changes in the mean of a measure between consecutive trials represent such effects as learning , motivation or fatigue ; these changes need to be eliminated from estimates of within-subject variation . Retest correlation is difficult to interpret , mainly because its value is sensitive to the heterogeneity of the sample of participants . Uses of reliability include decision-making when monitoring individuals , comparison of tests or equipment , estimation of sample size in experiments and estimation of the magnitude of individual differences in the response to a treatment . Reasonable precision for estimates of reliability requires approximately 50 study participants and at least 3 trials . Studies aim ed at assessing variation in reliability between tests or equipment require complex design s and analyses that research ers seldom perform correctly . A wider underst and ing of reliability and adoption of the typical error as the st and ard measure of reliability would improve the assessment of tests and equipment in our disciplines Despite the exp and ing use of Whole Body Vibration training among athletes , it is not known whether adding Whole Body Vibration training to the conventional training of sprint-trained athletes will improve speed-strength performance .  Twenty experienced sprint-trained athletes ( 13 male symbol , 7 female symbol , 17 - 30 years old ) were r and omly assigned to a Whole Body Vibration group ( n=10 : 6 male symbol and 4 female symbol ) or a Control group ( n=10 : 7 male symbol , 3 female symbol ) . During a 5-week experimental period all subjects continued their conventional training program , but the subjects of the Whole Body Vibration group additionally performed three times weekly a Whole Body Vibration training prior to their conventional training program . The Whole Body Vibration program consisted of unloaded static and dynamic leg exercises on a vibration platform ( 35 - 40 Hz , 1.7 - 2.5 mm , Power Plate ) . Pre and post isometric and dynamic ( 100 degrees/s ) knee-extensor and -flexor strength and knee-extension velocity at fixed resistances were measured by means of a motor-driven dynamometer ( Rev 9000 , Technogym ) . Vertical jump performance was measured by means of a contact mat . Force-time characteristics of the start action were assessed using a load cell mounted on each starting block . Sprint running velocity was recorded by means of a laser system . Isometric and dynamic knee-extensor and knee-flexor strength were unaffected ( p>0.05 ) in the Whole Body Vibration group and the Control group . As well , knee-extension velocity remained unchanged ( p>0.05 ) . The duration of the start action , the result ing start velocity , start acceleration , and sprint running velocity did not change ( > 0.05 ) in either group . In conclusion , this specific Whole Body Vibration protocol of 5 weeks had no surplus value upon the conventional training program to improve speed-strength performance in sprint-trained athletes The literature contains some hypotheses regarding the most favorable ground reaction force ( GRF ) for sprint running and how it might be achieved . This study tested the relevance of these hypotheses to the acceleration phase of a sprint , using  GRF impulse as the GRF variable of interest . Thirty-six athletes performed maximal-effort sprints from which video and GRF data were collected at the 16-m mark . Associations between GRF impulse  ( expressed relative to body mass ) and various kinematic measures were explored with simple and multiple linear regressions and paired t-tests . The regression results showed that relative propulsive impulse accounted for 57 % of variance in sprint velocity . Relative braking impulse accounted for only 7 % of variance in sprint velocity . In addition , the faster athletes tended to produce only moderate magnitudes of relative vertical impulse . Paired t-tests revealed that lower magnitudes of relative braking impulse were associated with a smaller touchdown distance ( p < 0.01 ) and a more active touchdown ( p < 0.001 ) . Also , greater magnitudes of relative propulsive impulse were associated with a high mean hip extension velocity of the stance limb ( p < 0.05 ) . In conclusion , it is likely that high magnitudes of propulsion are required to achieve high acceleration . Although there was a weak trend for faster athletes to produce lower magnitudes of braking , the possibility of braking having some advantages could not be ruled out . Further research is required to see if braking , propulsive , and vertical impulses can be modified with specific training . This will also provide insight into how a change in one GRF component might affect the others The aim of the study was to assess the reliability of sprint performance in both field and laboratory conditions . Twenty-one male ( mean ± s : 19 ± 1 years , 1.79 ± 0.07 m , 77.6 ± 7.1 kg ) and seventeen female team sport players ( mean ± s : 21 ± 4 years , 1.68 ± 0 . 07 m , 62.7 ± 4.7 kg ) performed a maximal 20-metre sprint running test on eight separate occasions . Four trials were conducted on a non-motorised treadmill in the laboratory ; the other four were conducted outdoors on a hard-court training surface with time recorded by single-beam photocells . Trials were conducted in r and om order with no familiarisation prior to testing . There was a significant difference between times recorded during outdoor field trials ( OFT ) and indoor laboratory trials ( ILT ) using a non-motorised treadmill ( 3.47 ± 0.53 vs. 6.06 ±1.17s ; p < 0.001 ) . The coefficient of variation ( CV ) for time was 2.55 - 4.22 % for OFT and 5.1 - 7.2 % for ILT . During ILT peak force ( 420.9 ± 87.7N ) , mean force ( 147.2 ± 24.7N ) , peak power ( 1376.8 ± 451.9W ) and mean power ( 514.8 ± 164.4W ) , and were measured . The CV for all ILT variables was highest during trial 1 - 2 comparison . The CV ( 95 % confidence interval ) for the trial 3 - 4 comparison yielded : 9.4 % ( 7.7 - 12 . 1 % ) , 7.9 % ( 6.4 - 10.2 % ) , 10.1 % ( 8.2 - 13.1 % ) and 6.2 % ( 5.1 - 8.0 % ) for PF , MF , PP and MP and respectively . The results indicate that reliable data can be derived for single maximal sprint measures , using fixed distance protocol s. However , significant differences in time/speed over 20-m exist between field and laboratory conditions . This is primarily due to the frictional resistance in the non- motorised treadmill . Measures of force and power during ILT require at least 3 familiarisations to reduce variability in test scores . Key pointsReliable data can be derived from single maximal sprint measures in both indoor and outdoor environments using fixed distance protocol s . There may be significant time differences to complete fixed distance trials between the two environments . Measures of mean force , peak force and peak power during indoor trials may require multiple trials to reduce variability in test scores & NA ; Lakomy , J. , and D.T. Haydon . The effects of enforced , rapid deceleration on performance in a multiple sprint test . J. 
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However , low intraday reliability was reported for the theoretical maximum horizontal force ( ICC 0.64 ) within adolescent athletes , and low validity was reported for velocity during the initial 5 m of a sprint acceleration ( bias up to 0.41 m/s ) measured with a laser device .
There have been no reports to date of criterion validity of kinetic measures of sprint acceleration performance on NMT and TT , and only limited results regarding acceptable concurrent validity of radar-derived kinetic data .
Conclusions Radar , laser , NMT and TT technologies can be used to reliably measure sprint acceleration performance and to provide insight into the determinants of sprinting speed .
Radar and laser technology may not be suitable for measuring the first few steps of a sprint acceleration