Methodological protocol of running on a treadmill using IMU in healthy people. Scoping review

Authors

DOI:

https://doi.org/10.47197/retos.v73.116214

Keywords:

Biomechanics, kinematics, running, treadmill test, wearable

Abstract

Introduction: Running is a popular and accessible activity with well-established health benefits, although it carries a risk of musculoskeletal injuries. Biomechanical analysis helps identify risk factors and guide preventive strategies. Inertial measurement units (IMUs) have enhanced the assessment of running technique.

Objective: This study aimed to review the methodological protocols applied in the kinematic analysis of treadmill running among recreational runners using IMUs in healthy individuals.

Methodology: The review followed PRISMA-ScR guidelines. Searches were conducted in Medline/PubMed, Web of Science, SportDiscus, and SafeJournal. Eligible studies included descriptive, reliability, validity, and intervention designs using IMUs in healthy participants. Methodological quality was assessed with the modified Downs & Black Index, and inter-rater reliability with Cohen’s Kappa coefficient.

Results: From 6,169 records, 30 studies met the eligibility criteria. A total of 31 devices were analyzed, with sampling frequencies ranging from 1600 Hz to 1 Hz. The tibia was the most common sensor location. Across studies, 553 men (66.2%) and 282 women (33.8%) participated. The most frequently assessed parameters were acceleration, angular velocity, and spatiotemporal variables such as cadence and contact time.

Conclusions: Treadmill-based IMUs are valid tools for measuring kinematic parameters and provide valuable insights into running technique and performance. Measurement accuracy depends on sensor placement. Key limitations included the low representation of women, the predominance of recreational runners, and the frequent use of reduced running speeds. Future studies should incorporate balanced sex representation and systematic comparisons of sensor locations to enhance reproducibility and support injury-prevention programs.

Author Biographies

  • Xantal Borràs Boix, Universitat de Vic - Universitat Central de Catalunya
    1. Borràs X, Balius X, Drobnic F. Efecte dels pantalons compressius sobre l’amplitud articular i el rendiment en el salt vertical. Apunt Med l’Esport. 2012;47(173):31–6.
    2. Borràs X, Balius X, Drobnic F, Galilea P. Vertical jump assessment on volleyball: A follow-up of three seasons of a high-level volleyball team. J Strength Cond Res. 2011;25(6):1686–94.
    3. Alba-Jiménez C, Moreno-Doutres D, Peña J. Trends assessing neuromuscular fatigue in team sports: A narrative review. Sports (Basel). 2022;10(3):33.
    4. Aguilera-Castells J, Buscà B, Arboix-Alió J, Miró A, Fort-Vanmeerhaeghe A, Peña J. sEMG activity in superimposed vibration on suspended supine bridge and hamstring curl. Front Physiol. 2021;12:712471.

    5. Buscà B, Moreno-Doutres D, Peña J, Morales J, Solana-Tramunt M, Aguilera-Castells J. Effects of jaw clenching wearing customized mouthguards on agility, power and vertical jump in male high-standard basketball players. J Exerc Sci Fit. 2018;16(1):5–11.

  • Javier Martínez Gramage, Universidad CEU Cardenal Herrera
    1. Perpiña-Martinez, S., Arguisuelas-Martínez, M. D., Perez-Dominguez, B., Nacher-Moltó, I., & Martínez-Gramage, J. (2023). Differences between sexes and speed levels in pelvic 3D kinematic patterns during running using an inertial measurement unit (IMU). International Journal of Environmental Research and Public Health, 20(4), 3631.
    2. Pardo, J., Mir-Jimenez, M., Moreno, V. H., Moltó, I. N., & Martínez-Gramage, J. (2021). The relationship between VO2Max, power management, and increased running speed: towards GAIT pattern recognition through clustering analysis. Sensors, 21(7), 2422.
    3. Moltó, I. N., Pardo, J., Cuenca, J., Segura-Ortí, E., Gabriel, W., & Martínez-Gramage, J. (2020). Wearable sensors detect differences between the sexes in lower limb electromyographic activity and pelvis 3D kinematics during running. Sensors, 20(22), 6478.
    4. Martínez-Gramage, J., Pardo, J., Moltó, I. N., Cuenca, J., Moreno, V. H., & Segura-Ortí, E. (2020). A Random Forest machine learning framework to reduce running injuries in young triathletes. Sensors, 20(21), 6388.
    5. Noguera-Iturbe, Y., Martínez-Gramage, J., Montañez-Aguilera, F. J., Casaña, J., & Lisón, J. F. (2019). Short-Term effects of kinesio taping in the treatment of latent and active upper trapezius trigger points: two prospective, randomized, SHAM-Controlled trials. Scientific Reports, 9(1).

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02-10-2025

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Vol. 73 (2025)

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Cejudo-Alba, R., Borràs Boix, X., & Martínez Gramage, J. (2025). Methodological protocol of running on a treadmill using IMU in healthy people. Scoping review. Retos, 73, 269-287. https://doi.org/10.47197/retos.v73.116214