Browsing by Subject "Accelerometer"

Now showing 1 - 2 of 2
  • Thumbnail Image
    Publication
    Restricted
    Running power meters and theoretical models based on laws of physics: effects of environments and running conditions
    (Elsevier, 2020-05-26) Cerezuela Espejo, Víctor; Hernández Belmonte, Alejandro; Courel Ibáñez, Javier; Conesa Ros, Elena; Martínez Cava, Alejandro; García Pallarés, Jesús; Actividad Física y Deporte
    Training prescription and load monitoring in running activities have benefited from power output (PW) data offered by new technologies. Nevertheless, to date, the sensitivity of PW data provided by these tools is still not completely clear. The aim of this study was to analyze the level of agreement between the PW estimated by five commercial technologies and the two main internationally theoretical models based on laws of physics, in different environments and running conditions. Ten endurance-trained male athletes performed three submaximal running protocols on a treadmill (indoor) and an athletic track (outdoor), with changes in speed, body weight, and slope. PW was simultaneously registered by the commercial technologies Stryd (StrydApp and StrydWatch), RunScribe, GarminRP and PolarV, whereas theoretical power output (TPW) was calculated by the two mathematical models (TPW1 and TPW2). Statistics included, among others, the Pearson's correlation coefficient (r) and standard error of measurement (SEM). The PolarV, and above all Stryd, showed the closest agreement with the TPW1 (Stryd: r ≥ 0.947, SEM ≤ 11 W; PolarV: r ≥ 0.931, SEM ≤ 64 W) and TPW2 (Stryd: r ≥ 0.933, SEM ≤ 60 W; PolarV: r ≥ 0.932, SEM ≤ 24 W), both indoors and outdoors. On the other hand, the devices GarminRP (r ≤ 0.765, SEM ≥ 59 W) and RunScribe. (r ≤ 0.508, SEM ≥ 125 W) showed the lowest agreement with the TPW1 and TPW2 models for all conditions and environments analyzed. The closest agreement of the Stryd and PolarV technologies with the TPW1 and TPW2 models suggest these tools as the most sensitive, among those analyzed, for PW measurement when changing environments and running conditions.
  • Thumbnail Image
    Publication
    Open Access
    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.