The Validity and Reliability of the My Jump Lab Artificial Intelligence Application
DOI:
https://doi.org/10.51224/SRXIV.431Keywords:
Countermovement Jump, Force Decks, My Jump, Impulse-momentumAbstract
Jump height (JH) achieved in a countermovement jump (CMJ) has been suggested to allow for the monitoring of neuromuscular fatigue (NMF) and assessment of lower body power. Although force platforms (FP) are considered the gold standard for measuring CMJ height, they are expensive compared to mobile apps such as My Jump Lab (MJL). Therefore, this study aimed to assess the concurrent validity and agreement of the MJL app compared to a FP (ForceDecks [FD]) system and to determine its test-rest reliability. A convenience sample of 26 (n = 11 females and n = 15 males) recreationally active university sport students and staff (mean ± SD; age: 23.08 ± 6.33 years; mass: 72.85 ± 9.93 kg; stature: 176.63 ± 10.18 cm) participated in the study. Participants attended the laboratory for testing on two separate occasions, separated by one week. After a standardised warm-up, they completed three CMJs on each occasion, with CMJ height simultaneously assessed by the FD and MJL app. The MJL Artificial Intelligence mode showed a mean bias of 4.32 cm [95% CI: 3.4, 5.26] overestimation with 95% limits of agreement ranging from -3.33 cm [95% CI: -4.96, -0.85] to 11.98 cm [95% CI: 10.13, 13.41]. Both methods demonstrated minimal mean bias (FD = 0.61 cm [95% CI: -0.31, 1.37] and MJL = 0.25 cm [95% CI = -0.48, 0.98]) between sessions, and both showed a similar width to their limits of agreement, ranging ~7 cm about the mean bias. In summary, the MLJ overestimated CMJ height in this sample compared to the FD system, but both methods were reliable. Given the significant differences in cost for these two methods, teams on a budget may interested in trialling the MJL app.
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References
Allaire, J, Dervieux, C. quarto: R interface to “Quarto” markdown publishing system. 2024.
Allaire, J, Dervieux, C, McPherson, J, et al. rmarkdown: Dynamic documents for R [Manual]. 2024.
Amrhein, V, Trafimow, D, Greenland, S. Inferential statistics as descriptive statistics: There is no replication crisis if we don’t expect replication. The American Statistician 73: 262-270, 2019.
Balsalobre-Fernández, C. Real time estimation of vertical jump height with a markerless motion capture smartphone app: A proof-of-concept case study. Proceedings of the Institution of Mechanical Engineers, Part P: Journal of Sports Engineering and Technology: 17543371241227817, 2024.
Balsalobre-Fernández, C, Glaister, M, Lockey, RA. The validity and reliability of an iPhone app for measuring vertical jump performance. Journal of sports sciences 33: 1574-1579, 2015.
Bates, D, Macherl, M, Bolker, B, et al. Fitting linear mixed-effects models using lme4. Journal of Statistical Software 67: 1-48, 2015.
Bishop, C, Jarvis, P, Turner, A, et al. Validity and reliability of strategy metrics to assess countermovement jump performance using the newly developed smartphone application. Journal of Human Kinetics 83: 185-195, 2022.
Bishop, C, Turner, A, Jordan, M, et al. A framework to guide practitioners for selecting metrics during the countermovement and drop jump tests. Strength & Conditioning Journal 44: 95-103, 2022.
Claudino, JG, Cronin, J, Mezêncio, B, et al. The countermovement jump to monitor neuromuscular status: A meta-analysis. Journal of Science and Medicine in Sport 20: 397-402, 2017.
Collings, TJ, Lima, YL, Dutaillis, B, et al. Concurrent validity and test–retest reliability of VALD ForceDecks' strength, balance, and movement assessment tests. Journal of Science and Medicine in Sport, 2024.
Firke, S. janitor: Simple tools for examining and cleaning dirty data. 2023.
Gathercole, R, Sporer, B, Stellingwerff, T, et al. Alternative countermovement-jump analysis to quantify acute neuromuscular fatigue. International journal of sports physiology and performance 10: 84-92, 2015.
Gençoğlu, C, Ulupınar, S, Özbay, S, et al. Validity and reliability of “My Jump app” to assess vertical jump performance: a meta-analytic review. Scientific reports 13: 20137, 2023.
Heredia-Jimenez, J, Orantes-Gonzalez, E. Comparison of three different measurement systems to assess the vertical jump height. Revista Brasileira de Medicina do Esporte 26: 143-146, 2020.
Hester, J, Bryan, J. glue: Interpreted string literals [Manual]. 2024.
Hughes, S, Chapman, DW, Haff, GG, et al. The use of a functional test battery as a non-invasive method of fatigue assessment. PloS one 14: e0212870, 2019.
Landau, WM. tarchetypes: Archetypes for targets [Manual]. 2021.
Landau, WM. The targets R package: A dynamic Make-like function-oriented pipeline toolkit for reproducibility and high-performance computing. Journal of Open Source Software 6: 2959, 2021.
Lombard, W, Reid, S, Pearson, K, et al. Reliability of metrics associated with a counter-movement jump performed on a force plate. Measurement in Physical Education and Exercise Science 21: 235-243, 2017.
Loy, A, Steele, S, Korobova, J. lmeresampler: Bootstrap methods for nested linear mixed-effects models [Manual]. 2024.
McMaster, DT, Gill, N, Cronin, J, et al. A brief review of strength and ballistic assessment methodologies in sport. Sports Medicine 44: 603-623, 2014.
Merrigan, JJ, Strang, A, Eckerle, J, et al. Countermovement jump force-time curve analyses: reliability and comparability across force plate systems. The Journal of Strength & Conditioning Research 38: 30-37, 2024.
Mesquida, C, Murphy, J, Lakens, D, et al. Replication concerns in sports and exercise science: a narrative review of selected methodological issues in the field. Royal Society Open Science 9: 220946, 2022.
Nuzzo, JL, McBride, JM, Cormie, P, et al. Relationship between countermovement jump performance and multijoint isometric and dynamic tests of strength. The Journal of Strength & Conditioning Research 22: 699-707, 2008.
Parker, RA, Scott, C, Inácio, V, et al. Using multiple agreement methods for continuous repeated measures data: a tutorial for practitioners. BMC Medical Research Methodology 20: 1-14, 2020.
Pedersen, TL. patchwork: The composer of plots [Manual]. 2024.
Rodriguez-Sanchez, F, Jackson, CP, Hutchins, SD, et al. Grateful: Facilitate Citation of R Packages. 2023.
Şentürk, D, Yüksel, O, Akyildiz, Z. The concurrent validity and reliability of the My Jump Lab smartphone app for the real-time measurement of vertical jump performance. Proceedings of the Institution of Mechanical Engineers, Part P: Journal of Sports Engineering and Technology: 17543371241246439, 2024.
Team, RC. R: A language and environment for statistical computing [Manual]. R Foundation for Statistical Computing. 2024.
Ushey, K, Wickham, H. renv: Project environments [Manual]. 2024.
Wickham, H, Averick, M, Bryan, J, et al. Welcome to the tidyverse: Journal of Open Source Software, v. 4. doi 10: 1686, 2019.
Xie, Y. A comprehensive tool for reproducible research in R, in: Implementing reproducible computational research. V Stodden, F Leisch, RD Peng, eds.: Chapman and Hall/CRC., 2014.
Xie, Y. Dynamic documents with R and knitr Chapman and Hall/CRC, 2015.
Xie, Y. knitr: A general-purpose package for dynamic report generation in R [Manual]. 2024.
Xie, Y, Allaire, JJ, Grolemund, G. R markdown: The definitive guide. Chapman and Hall/CRC., 2018.
Xie, Y, Dervieux, C, Riederer, E. R markdown cookbook. Chapman and Hall/CRC., 2020.
Xu, J, Turner, A, Comfort, P, et al. A systematic review of the different calculation methods for measuring jump height during the countermovement and drop jump tests. Sports Medicine 53: 1055-1072, 2023.
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Copyright (c) 2024 Lee Bridgeman, Bailey Cameron, James Steele (Author)
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