The Validity and Reliability of the My Jump Lab App for the Measurement of Vertical Jump Performance Using Artificial Intelligence

The countermovement jump (CMJ) is a widely used test to assess lower body neuromuscular performance. This study aims to analyze the validity and reliability of an iOS application using artificial intelligence to measure CMJ height, force, velocity, and power in unloaded and loaded conditions. Twelve physically active participants performed 12 CMJs with external loads ranging from 0% to 70% of their body mass while being simultaneously monitored with a pair of force platforms and the My Jump Lab application. The scores for jump height, mean propulsive force, velocity, and power between devices were compared for validity and reliability purposes. The force platform and the application showed a high association (r > 0.91, <i>p</i> < 0.05) for measuring CMJ height, force, velocity, and power. Small and no statistically significant differences (<i>p</i> < 0.05) were observed in most loading conditions. Both instruments showed high reliability (Cronbach's α > 0.93, Coefficient of variation < 6%) for measuring the different trials performed by each participant. The My Jump Lab application was shown to be valid and reliable for measuring CMJ height, force, velocity, and power in both loaded and unloaded jumps, eliminating the problems associated with the cost and portability of force plates for daily practice.

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Publication Details

Journal
Sensors
Published
2024-12-10
DOI
https://doi.org/10.3390/s24247897
Citations
12
Primary Topic
Sports Performance and Training
Type
article
Field-Weighted Citation Impact
5.73
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article

The Validity and Reliability of the My Jump Lab App for the Measurement of Vertical Jump Performance Using Artificial Intelligence

Daniel Varela-Olalla, Carlos Balsalobre‐Fernández
12 citations
Sensors
Sports Performance and Training
5.73
article

The Validity and Reliability of the My Jump Lab App for the Measurement of Vertical Jump Performance Using Artificial Intelligence

Daniel Varela-Olalla, Carlos Balsalobre‐Fernández
article en
12 citations

Abstract

The countermovement jump (CMJ) is a widely used test to assess lower body neuromuscular performance. This study aims to analyze the validity and reliability of an iOS application using artificial intelligence to measure CMJ height, force, velocity, and power in unloaded and loaded conditions. Twelve physically active participants performed 12 CMJs with external loads ranging from 0% to 70% of their body mass while being simultaneously monitored with a pair of force platforms and the My Jump Lab application. The scores for jump height, mean propulsive force, velocity, and power between devices were compared for validity and reliability purposes. The force platform and the application showed a high association (r > 0.91, <i>p</i> < 0.05) for measuring CMJ height, force, velocity, and power. Small and no statistically significant differences (<i>p</i> < 0.05) were observed in most loading conditions. Both instruments showed high reliability (Cronbach's α > 0.93, Coefficient of variation < 6%) for measuring the different trials performed by each participant. The My Jump Lab application was shown to be valid and reliable for measuring CMJ height, force, velocity, and power in both loaded and unloaded jumps, eliminating the problems associated with the cost and portability of force plates for daily practice.

SensorsVol. 24(24)
Universidad Autónoma de Madrid (ES)
Openalex Percentile: Top 3%
Sports Performance and Training
5.73
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The Validity and Reliability of the My Jump Lab App for the Measurement of Vertical Jump Performance Using Artificial Intelligence — Daniel Varela-Olalla, Carlos Balsalobre‐Fernández · Sensors (2024) | TGRS Research Map | TGRS