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.
Highlights
Resistance training has been the most-used method to increase athletes’ strength [1]
The smartphone accelerometer used by the mobile basic program was reliable at medium velocities
The smartphone accelerometer used by the mobile basic program was reliable at medium valid and reliable tool for the measurement of concentric mean velocity of BP exercise in the Smith velocities (70% 1RM), but not at low-velocity lifts (90% and 100% 1RM)
Summary
Resistance training has been the most-used method to increase athletes’ strength [1]. The 1RM estimation method based on lifting velocity has been demonstrated as a valid and reliable way to obtain the 1RM value without performing the lift with maximum load [12,13]. Actual smartphones have inertial sensors (i.e., accelerometers, magnetometers, and gyroscopes) that are used to determine the position and displacement of the device [19]. This technology could be used to measure lifting velocity [20]. As far as it is known, there is not any valid smartphone APP that uses this hardware in order to measure velocity and estimate strength
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