Browsing by Subject "Testing"

Now showing 1 - 4 of 4
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    Are we ready to measure running power? Repeatability and concurrent validity of five commercial technologies
    (Wiley, 2021-03) Cerezuela Espejo, Víctor; Hernández Belmonte, Alejandro; Courel Ibáñez, Javier; Conesa Ros, Elena; Mora Rodríguez, Ricardo; García Pallarés, Jesús; Actividad Física y Deporte
    Training prescription in running activities have benefited from power output (PW) data obtained by new technologies. Nevertheless, to date, the suitability of PW data provided by these tools is still uncertain. The present study aimed to: (i) analyze the repeatability of five commercially available technologies for running PW estimation, and (ii) examine the concurrent validity through the relationship between each technology PW and oxygen uptake (VO2). On two occasions (test-retest), twelve endurance-trained male athletes performed on a treadmill (indoor) and an athletic track (outdoor) three submaximal running protocols with manipulations in speed, body weight and slope. PW was simultaneously registered by the commercial technologies StrydApp, StrydWatch, RunScribe, GarminRP and PolarV, while VO2 was monitored by a metabolic cart. Test-retest data from the environments (indoor and outdoor) and conditions (speed, body weight and slope) were used for repeatability analysis, which included the standard error of measurement (SEM), coefficient of variation (CV) and intraclass correlation coefficient (ICC). A linear regression analysis and the standard error of estimate (SEE) were used to examine the relationship between PW and VO2. Stryd device was found as the most repeatable technology for all environments and conditions (SEM ≤ 12.5 W, CV ≤ 4.3%, ICC ≥ 0.980), besides the best concurrent validity to the VO2 (r ≥ 0.911, SEE ≤ 7.3%). On the contrary, although the PolarV, GarminRP and RunScribe technologies maintain a certain relationship with VO2, their low repeatability questions their suitability. The Stryd can be considered as the most recommended tool, among the analyzed, for PW measurement.
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    Open Access
    Sprint performance and mechanical outputs computed with an iPhone app: Comparison with existing reference methods
    (Wiley, 2017-05) Romero Franco, Natalia; Jiménez Reyes, Pedro; Castaño Zambudio, Adrián; Capelo Ramírez, Fernando; Rodríguez Juan, Juan José; González Hernández, Jorge; Toscano Bendala, Francisco Javier; Cuadrado Peñafiel, Víctor; Balsalobre Fernández, Carlos; Fisioterapia
    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 (F0), the maximal theoretical velocity (V0), the maximal power (Pmax) 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.
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    The 2-point method: A quick, accurate, and repeatable approach to estimate ultrasoundderived quadriceps femoris cross-sectional area
    (Human Kinetics, 2022-07-18) Hernández Belmonte, Alejandro; García Pallarés, Jesús; Martínez Cava, Alejandro; Actividad Física y Deporte
    Purpose: To analyze the feasibility of the 2-point method for estimating ultrasound-derived quadriceps femoris cross-sectional area (QUADACSA). First, (1) the agreement between QUADACSA measured by panoramic ultrasound and magnetic resonance imaging (MRI) was studied, and thereafter, we examined 2 approaches of the 2-point method in terms of (2) estimation errors and (3) test–retest repeatability. Methods: Both thighs of 16 young men were analyzed. Ultrasound-QUADACSA versus MRI-QUADACSA comparison was conducted at 6 thigh lengths (20%–70% of the thigh length). Thereafter, ultrasound-QUADACSA corresponding to 30% and 60% (2-point30%–60%) or 20% and 70% (2-point20%–70%) were used to estimate QUADACSA of the remaining regions. Estimated QUADACSA resulting from both 2-point approaches was compared with the measured one. Finally, the test–retest repeatability was examined by comparing the errors generated on 2 separate estimations. Statistics included the standard error of measurement (SEM) expressed in absolute (in square centimeters) and relative terms (in percentage) as a coefficient of variation (CV), as well as the intraclass correlation cofficient (ICC) and bias. Results: An excellent agreement (ICC ≥ 0.980) and reduced errors (SEM ≤ 2.43 cm2) resulted from the ultrasound-QUADACSA versus MRI-QUADACSA comparison. Although estimation errors found were reduced (CV ≤ 7.50%), they proved to be lower and less biased for the 2-point30%–60%, especially at the central regions (SEM ≤ 2.01 cm2; bias ≤ 0.89 cm2). Similarly, repeatability analysis revealed lower test–retest errors for the 2-point30%–60% (CV ≤ 1.9%) than for the 2-point20%–70% (CV ≤ 4.6%). Conclusion: The 2-point method, especially that implemented using the 30% and 60% regions, represents an accurate and repeatable strategy to evaluate QUADACSA.
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    Using an inertial device (WIMU PRO) to quantify neuromuscular load in running reliability, convergent validity, and influence of type of surface and device location
    (Lippincott, Williams & Wilkins, 2020-02) Gómez Carmona, Carlos David; Bastida Castillo, Alejandro; González-Custodio, Adrián; Olcina, Guillermo; Pino Ortega, José; Actividad Física y Deporte
    Gómez-Carmona, CD, Bastida-Castillo, A, González-Custodio, A, Olcina, G, and Pino-Ortega, J. Using an inertial device (WIMU PRO) to quantify neuromuscular load in running: reliability, convergent validity, and influence of type of surface and device location. J Strength Cond Res 34(2): 365–373, 2020—Currently, the use of accelerometers in sport is increasing, and thus, the devices are required to be valid and reliable. This study tested (a) the reliability and validity of WIMU PRO accelerometers to measure PlayerLoad (PL) and (b) the influence of speed, inertial device location, and type of surface where the incremental test is performed. Twenty resistance-trained men (age: 27.32 ± 6.65 years; height: 1.74 ± 0.03 m; body mass: 68.96 ± 4.37 kg; and body mass index: 22.76 ± 1.11 kg·m−2) volunteered to participate in the study that lasted 5 weeks. Four progressive incremental tests were performed in treadmill and athletic track conditions. External load variable (PL) and physiological variables (heart rate [HR] and SmO2) were recorded by 4 WIMU PRO inertial devices (scapulae, center of mass, knee, and ankle), a GARMIN HR band, and a MOXY near-infrared spectroscopy device, respectively. High reliability was found on both types of surface, showing the best values at the ankle (treadmill: intraclass correlation coefficient [ICC] = 0.99, coefficient of variation [CV] = 4.65%; track: ICC = 0.96, CV = 6.54%). A nearly perfect convergent validity was shown with HRAVG (r = 0.99) and a moderate one with SmO2 (r = −0.69). Significant differences in the PL variable between surfaces were reported in all locations except the scapulae (p = 0.173), and the higher values were found on the track. In the analysis per location, the ankle location reported the highest values at all speeds and on the 2 surfaces analyzed. Assessment needs to be individualized, due to the great variability of gait biomechanics among subjects. The accelerometer location should be chosen according to the purpose of the measurement, with the ankle location being recommended for neuromuscular load analysis in running.