ABSTRACTBalsalobre-Fernández, C, Tejero-González, CM, del Campo-Vecino, J, and Bavaresco, N. The concurrent validity and reliability of a low-cost, high-speed camera-based method for measuring the ...flight time of vertical jumps. J Strength Cond Res 28(2)528–533, 2014—Flight time is the most accurate and frequently used variable when assessing the height of vertical jumps. The purpose of this study was to analyze the validity and reliability of an alternative method (i.e., the HSC-Kinovea method) for measuring the flight time and height of vertical jumping using a low-cost high-speed Casio Exilim FH-25 camera (HSC). To this end, 25 subjects performed a total of 125 vertical jumps on an infrared (IR) platform while simultaneously being recorded with a HSC at 240 fps. Subsequently, 2 observers with no experience in video analysis analyzed the 125 videos independently using the open-license Kinovea 0.8.15 software. The flight times obtained were then converted into vertical jump heights, and the intraclass correlation coefficient (ICC), Bland-Altman plot, and Pearson correlation coefficient were calculated for those variables. The results showed a perfect correlation agreement (ICC = 1, p < 0.0001) between both observersʼ measurements of flight time and jump height and a highly reliable agreement (ICC = 0.997, p < 0.0001) between the observersʼ measurements of flight time and jump height using the HSC-Kinovea method and those obtained using the IR system, thus explaining 99.5% (p < 0.0001) of the differences (shared variance) obtained using the IR platform. As a result, besides requiring no previous experience in the use of this technology, the HSC-Kinovea method can be considered to provide similarly valid and reliable measurements of flight time and vertical jump height as more expensive equipment (i.e., IR). As such, coaches from many sports could use the HSC-Kinovea method to measure the flight time and height of their athleteʼs vertical jumps.
The purpose of this investigation was to analyse the concurrent validity and reliability of an iPhone app (called: My Jump) for measuring vertical jump performance. Twenty recreationally active ...healthy men (age: 22.1 ± 3.6 years) completed five maximal countermovement jumps, which were evaluated using a force platform (time in the air method) and a specially designed iPhone app. My jump was developed to calculate the jump height from flight time using the high-speed video recording facility on the iPhone 5 s. Jump heights of the 100 jumps measured, for both devices, were compared using the intraclass correlation coefficient, Pearson product moment correlation coefficient (r), Cronbach's alpha (α), coefficient of variation and Bland-Altman plots. There was almost perfect agreement between the force platform and My Jump for the countermovement jump height (intraclass correlation coefficient = 0.997, P < 0.001; Bland-Altman bias = 1.1 ± 0.5 cm, P < 0.001). In comparison with the force platform, My Jump showed good validity for the CMJ height (r = 0.995, P < 0.001). The results of the present study showed that CMJ height can be easily, accurately and reliably evaluated using a specially developed iPhone 5 s app.
Enacted measures to control the spread of COVID-19 disease such as compulsory confinement may influence health behaviors. The present study investigated changes in physical activity (PA) levels ...during the first days of confinement. Using an online survey, the Spanish population (n = 2042, 54% women, age 35.9 (SD 13.6) years) replied to questions concerning sociodemographic characteristics as well as PA behavior before and during the first week of enacted isolation. Physical activity vital sign (PAVS) short form was used to estimate weekly minutes of PA before and during the isolation period. Statistical analysis used the following tests: Mc Nemar Chi-squared tests, independent and paired samples t-test, and effect size (Cohen’s d). During the first week of confinement, participants reduced their weekly PA levels by 20% (~45.2 weekly minutes (95% CI: 37.4−53.0)). This led to a decrease from 60.6% to 48.9% (difference: 11.7%) (p < 0.0001) in the number of participants meeting the recommended World Health Organization (WHO) PA levels. Subgroups including men, participants aged 43 or over, and those not holding a university degree had the greatest reductions in both weekly minutes of PA and adherence to guidelines. The PA levels of the Spanish population generally declined during the first days of COVID-19 confinement.
The objective of the present study was to compare the effects of a traditional resistance training program (fixed exercises and repetition ranges) to a resistance training program where exercises and ...repetition ranges were randomized on a session-by-session basis on markers of muscular adaptations and intrinsic motivation.
Twenty-one resistance trained men were randomized to perform an 8-week resistance training program using either a fixed exercise selection (CON) or having exercises randomly varied each session via a computerized app. Both groups performed 3 sets of 6 exercises, with training carried out 4 times per week.
Both conditions promoted large, statistically significant increases in the bench press and back-squat 1 repetition maximum without differences between groups. Muscle thickness (MT) measures for the individual quadriceps showed large, statistically significant increases in of the vastus lateralis and rectus femoris for both conditions, with no observed between-group differences. Although no between-group in MT were noted for the vastus intermedius, only the CON displayed significant increases from baseline. Participants in EXP showed a significant, moderate improvement in the intrinsic motivation to training, while participants in the CON group presented non-significant decreases in this variable.
Varying exercise selection had a positive effect on enhancing motivation to train in resistance-trained men, while eliciting similar improvements in muscular adaptations.
Basketball is a court-based team-sport that requires a broad array of demands (physiological, mechanical, technical, tactical) in training and competition which makes it important for practitioners ...to understand the stress imposed on the basketball player during practice and match-play. Therefore, the main aim of the present systematic review is to investigate the training and match-play demands of basketball in elite, sub-elite, and youth competition. A search of five electronic databases (PubMed, SportDiscus, Web of Science, SCOPUS, and Cochrane) was conducted until December 20th, 2019. Articles were included if the study: (i) was published in English; (ii) contained internal or external load variables from basketball training and/or competition; and (iii) reported physiological or metabolic demands of competition or practice. Additionally, studies were classified according to the type of study participants into elite (20), sub-elite (9), and youth (6). A total of 35 articles were included in the systematic review. Results indicate that higher-level players seem to be more efficient while moving on-court. When compared to sub-elite and youth, elite players cover less distance at lower average velocities and with lower maximal and average heart rate during competition. However, elite-level players have a greater bandwidth to express higher velocity movements. From the present systematic review, it seems that additional investigation on this topic is warranted before a "clear picture" can be drawn concerning the acceleration and deceleration demands of training and competition. It is necessary to accurately and systematically assess competition demands to provide appropriate training strategies that resemble match-play.
The purpose of this study was to analyze the validity, reliability, and accuracy of new wearable and smartphone-based technology for the measurement of barbell velocity in resistance training ...exercises. To do this, 10 highly trained powerlifters (age = 26.1 ± 3.9 years) performed 11 repetitions with loads ranging 50-100% of the 1-Repetition maximum in the bench-press, full-squat, and hip-thrust exercises while barbell velocity was simultaneously measured using a linear transducer (LT), two
wearable devices (one placed on the subjects' wrist -BW-, and the other one directly attached to the barbell -BB-) and the iOS
app. Results showed a high correlation between the LT and BW (
= 0.94-0.98, SEE = 0.04-0.07 m•s
), BB (
= 0.97-0.98, SEE = 0.04-0.05 m•s
), and the
app (
= 0.97-0.98, SEE = 0.03-0.05 m•s
) for the measurement of barbell velocity in the three exercises. Paired samples
-test revealed systematic biases between the LT and BW, BB and the app in the hip-thrust, between the LT and BW in the full-squat and between the LT and BB in the bench-press exercise (
< 0.001). Moreover, the analysis of the linear regression on the Bland-Altman plots showed that the differences between the LT and BW (
= 0.004-0.03), BB (
= 0.007-0.01), and the app (
= 0.001-0.03) were similar across the whole range of velocities analyzed. Finally, the reliability of the BW (ICC = 0.910-0.988), BB (ICC = 0.922-0.990), and the app (ICC = 0.928-0.989) for the measurement of the two repetitions performed with each load were almost the same than that observed with the LT (ICC = 0.937-0.990). Both the
wearable device and the
app were highly valid, reliable, and accurate for the measurement of barbell velocity in the bench-press, full-squat, and hip-thrust exercises. These results could have potential practical applications for strength and conditioning coaches who wish to measure barbell velocity during resistance training.
This study compared the concurrent validity and reliability of previously proposed generalized group equations for estimating the bench press (BP) 1-repetition maximum (1RM) with the individualized ...load-velocity relationship modeled with a 2-point method.
Thirty men (BP 1RM relative to body mass: 1.08 0.18 kg·kg
) performed 2 incremental loading tests in the concentric-only BP exercise and another 2 in the eccentric-concentric BP exercise to assess their actual 1RM and load-velocity relationships. A high velocity (≈1 m·s
) and a low velocity (≈0.5 m·s
) were selected from their load-velocity relationships to estimate the 1RM from generalized group equations and through an individual linear model obtained from the 2 velocities.
The directly measured 1RM was highly correlated with all predicted 1RMs (r = .847-.977). The generalized group equations systematically underestimated the actual 1RM when predicted from the concentric-only BP (P < .001; effect size = 0.15-0.94) but overestimated it when predicted from the eccentric-concentric BP (P < .001; effect size = 0.36-0.98). Conversely, a low systematic bias (range: -2.3 to 0.5 kg) and random errors (range: 3.0-3.8 kg), no heteroscedasticity of errors (r
= .053-.082), and trivial effect size (range: -0.17 to 0.04) were observed when the prediction was based on the 2-point method. Although all examined methods reported the 1RM with high reliability (coefficient of variation ≤ 5.1%; intraclass correlation coefficient ≥ .89), the direct method was the most reliable (coefficient of variation < 2.0%; intraclass correlation coefficient ≥ .98).
The quick, fatigue-free, and practical 2-point method was able to predict the BP 1RM with high reliability and practically perfect validity, and therefore, the authors recommend its use over generalized group equations.
The purpose of this study was to assess validity and reliability of sprint performance outcomes measured with an iPhone application (named: MySprint) and existing field methods (i.e. timing ...photocells and radar gun). To do this, 12 highly trained male sprinters performed 6 maximal 40-m sprints during a single session which were simultaneously timed using 7 pairs of timing photocells, a radar gun and a newly developed iPhone app based on high-speed video recording. Several split times as well as mechanical outputs computed from the model proposed by Samozino et al. (2015). A simple method for measuring power, force, velocity properties, and mechanical effectiveness in sprint running. Scandinavian Journal of Medicine & Science in Sports. https://doi.org/10.1111/sms.12490 were then measured by each system, and values were compared for validity and reliability purposes. First, there was an almost perfect correlation between the values of time for each split of the 40-m sprint measured with MySprint and the timing photocells (r = 0.989-0.999, standard error of estimate = 0.007-0.015 s, intraclass correlation coefficient (ICC) = 1.0). Second, almost perfect associations were observed for the maximal theoretical horizontal force (F
0
), the maximal theoretical velocity (V
0
), the maximal power (P
max
) and the mechanical effectiveness (DRF - decrease in the ratio of force over acceleration) measured with the app and the radar gun (r = 0.974-0.999, ICC = 0.987-1.00). Finally, when analysing the performance outputs of the six different sprints of each athlete, almost identical levels of reliability were observed as revealed by the coefficient of variation (MySprint: CV = 0.027-0.14%; reference systems: CV = 0.028-0.11%). Results on the present study showed that sprint performance can be evaluated in a valid and reliable way using a novel iPhone app.
ABSTRACTGallardo-Fuentes, F, Gallardo-Fuentes, J, Ramírez-Campillo, R, Balsalobre-Fernández, C, Martínez, C, Caniuqueo, A, Cañas, R, Banzer, W, Loturco, I, Nakamura, FY, and Izquierdo, M. ...Intersession and intrasession reliability and validity of the My Jump app for measuring different jump actions in trained male and female athletes. J Strength Cond Res 30(7)2049–2056, 2016—The purpose of this study was to analyze the concurrent validity and reliability of the iPhone app named My Jump for measuring jump height in 40-cm drop jumps (DJs), countermovement jumps (CMJs), and squat jumps (SJs). To do this, 21 male and female athletes (age, 22.1 ± 3.6 years) completed 5 maximal DJs, CMJs, and SJs on 2 separate days, which were evaluated using a contact platform and the app My Jump, developed to calculate jump height from flight time using the high-speed video recording facility on the iPhone. A total of 630 jumps were compared using the intraclass correlation coefficient (ICC), Bland-Altman plots, Pearsonʼs product moment correlation coefficient (r), Cronbachʼs alpha (α), and coefficient of variation (CV). There was almost perfect agreement between the measurement instruments for all jump height values (ICC = 0.97–0.99), with no differences between the instruments (p > 0.05; mean difference of 0.2 cm). Almost perfect correlation was observed between the measurement instruments for SJs, CMJs, and DJs (r = 0.96–0.99). My Jump showed very good within-subject reliability (α = 0.94–0.99; CV = 3.8–7.6) and interday reliability (r = 0.86–0.95) for SJs, CMJs, and DJs in all subjects. Therefore, the iPhone app named My Jump provides reliable intersession and intrasession data, as well as valid measurements for maximal jump height during fast (i.e., DJs) and slow (i.e., CMJs) stretch-shortening cycle muscle actions, and during concentric-only explosive muscle actions (i.e., SJs), in both male and female athletes in comparison with a professional contact platform.
ABSTRACTPeart, DJ, Balsalobre-Fernández, C, and Shaw, MP. Use of mobile applications to collect data in sport, health, and exercise scienceA narrative review. J Strength Cond Res 33(4)1167–1177, ...2019—Mobile devices are ubiquitous in the population, and most have the capacity to download applications (apps). Some apps have been developed to collect physiological, kinanthropometric, and performance data; however, the validity and reliability of such data is often unknown. An appraisal of such apps is warranted, as mobile apps may offer an alternative method of data collection for practitioners and athletes with money, time, and space constraints. This article identifies and critically reviews the commercially available apps that have been tested in the scientific literature, finding evidence to support the measurement of the resting heart through photoplethysmography, heart rate variability, range of motion, barbell velocity, vertical jump, mechanical variables during running, and distances covered during walking, jogging, and running. The specific apps with evidence, along with reported measurement errors are summarized in the review. Although mobile apps may have the potential to collect data in the field, athletes and practitioners should exercise caution when implementing them into practice as not all apps have support from the literature, and the performance of a number of apps have only been tested on 1 device.
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