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Validity and Reliability of a Smartphone Accelerometer for Measuring Lift Velocity in Bench-Press Exercises

Author

Listed:
  • Javier Peláez Barrajón

    (Department of Health and Human Performance, Sport Biomechanics Laboratory, Facultad de Ciencias Actividad Física y Deporte—INEF, Universidad Politécnica de Madrid, 28040 Madrid, Spain)

  • Alejandro F. San Juan

    (Department of Health and Human Performance, Sport Biomechanics Laboratory, Facultad de Ciencias Actividad Física y Deporte—INEF, Universidad Politécnica de Madrid, 28040 Madrid, Spain)

Abstract

The aim of this study was to determine the validity and reliability that a smartphone accelerometer (ACC) used by a mobile basic program (MBP) can provide to measure the mean velocity of a bench-press (BP) lift. Ten volunteers participated in the study (age 23.1 ± 2.5 years; mean ± SD). They had more than one year of resistance training experience in BP exercise. All performed three attempts with different loads: 70%, 90%, and 100% of the estimated value of the one-repetition maximum (1RM). In each repetition, the mean velocity was measured by a validated linear transducer and the ACC. The smartphone accelerometer used by the mobile basic program showed no significant differences between the mean velocities at 70% 1RM lifts (ACC = 0.52 ± 0.11 m/s; transducer = 0.54 ± 0.09 m/s, p > 0.05). However, significant differences were found in the mean velocities for 90% 1RM (ACC = 0.46 ± 0.09 m/s; transducer = 0.31 ± 0.03 m/s, p < 0.001), and 100% 1RM (ACC = 0.33 ± 0.21 m/s; transducer = 0.16 ± 0.04 m/s, p < 0.05). The accelerometer is sensitive enough to measure different lift velocities, but the algorithm must be correctly calibrated.

Suggested Citation

  • Javier Peláez Barrajón & Alejandro F. San Juan, 2020. "Validity and Reliability of a Smartphone Accelerometer for Measuring Lift Velocity in Bench-Press Exercises," Sustainability, MDPI, vol. 12(6), pages 1-9, March.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:6:p:2312-:d:333041
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    Cited by:

    1. Zoi Christoforou & Christos Gioldasis & Yeltsin Valero & Grigoris Vasileiou-Voudouris, 2022. "Smart Traffic Data for the Analysis of Sustainable Travel Modes," Sustainability, MDPI, vol. 14(18), pages 1-21, September.

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