Jairo Hidalgo Migueles

• Department of Physical Education and Sport

  Faculty of Sport Sciences
  University of Granada , Spain
  Ctra Alfacar s/n. 18071. Granada, Spain

Jairo Hidalgo Migueles

is a Ramón y Cajal Research Fellow at the University of Granada. He studied Sport Sciences at the University of Granada (2009-2013), where he subsequently completed his PhD in Biomedicina (2015-2020), earning an International Mention and the Extraordinary PhD Award. Following a 3-year postdoctoral stay in Sweden (Linköping University and Karolinska Institutet), Jairo returned to the University of Granada under a Beatriz Galindo fellowship until securing his current Ramón y Cajal position. Among his most notable achievements and contributions, he leads the development of open-source methodologies and software widely used internationally for accelerometry analysis and wearable sensor data processing, serving as a core developer of the GGIR R package along with other open-source tools. With over 100 published articles and more than 10,000 citations, his work stands out for combining biostatistical rigor, movement analysis, and technology transfer to public health, all conducted under the principles of open science.

His main areas of interest are:

• Measurement of physical activity, sedentary behavior, and sleep using wearable sensors.
• Algorithm development, signal processing, and open-source R packages.
• Identification and validation of digital movement biomarkers.
• Open science, scientific reproducibility, and methodological harmonization in physical activity epidemiology.

Top-5 publications

1. Migueles JH, Rowlands AV, Huber F, Sabia S, van Hees VT. GGIR: a research community–driven open-source R package for processing wearable accelerometer data. Journal for the Measurement of Physical Behaviours. 2019;2(3):188-196. doi: https://doi.org/10.1123/jmpb.2018-0063

Contribution: This work presents and integrates the methodological framework of the open-source R package GGIR for processing, calibrating, and extracting raw acceleration metrics to evaluate physical activity, sedentary behavior, sleep, and the activity-rest cycle.

2. Migueles JH, Cadenas-Sanchez C, Ekelund U, Delisle Nyström C, Mora-Gonzalez J, Löf M, Labayen I, Ruiz JR, Ortega FB. Accelerometer data collection and processing criteria to assess physical activity and other outcomes: a systematic review and practical considerations. Sports Medicine. 2017;47(9):1821-1845. doi: https://doi.org/10.1007/s40279-017-0716-0

Contribution: An internationally benchmarked systematic review synthesizing accelerometer data collection and processing criteria for measuring physical activity and sleep. This study provides standardized guidelines and recommendations to maximize comparability across research in sports and exercise sciences.

3. Migueles JH, et al. Development of an accelerometer age- and sex-specific approach based on population-standardized values for physical activity surveillance: A proof of concept. Scandinavian Journal of Medicine & Science in Sports. 2024;34(10):e14751. doi: https://doi.org/10.1016/j.jshs.2024.100995

Contribution: This work presents a proof of concept for physical activity epidemiological surveillance using an age- and sex-standardized approach. The proposal allows accelerometry estimates to be interpreted based on population reference values, facilitating methodologically rigorous comparisons free from the bias associated with traditional fixed cut-points.

4. Migueles JH, Aadland E, Andersen LB, Brønd JC, Chastin SF, Hansen BH, Konstabel K, Kvalheim OM, McGregor DE, Rowlands AV, Sabia S, van Hees VT, Walmsley R, Ortega FB; External review group. GRANADA consensus on analytical approaches to assess associations with accelerometer-determined physical behaviours (physical activity, sedentary behaviour and sleep) in epidemiological studies. British Journal of Sports Medicine. 2022 Apr;56(7):376-384. doi: https://doi.org/10.1136/bjsports-2020-103604 

Contribution: An international consensus work (Granada Consensus) bringing together global experts to review and standardize analytical approaches for continuous accelerometry data (isotemporal substitution models, compositional data analysis, multivariate models, machine learning, etc.). It provides a practical guide and a methodological decision tree to steer analysis selection based on the epidemiological research question.

5. Migueles JH, Cadenas-Sanchez C, Lubans DR, Henriksson P, Torres-Lopez LV, Rodriguez-Ayllon M, Plaza-Florido A, Gil-Cosano JJ, Henriksson H, Escolano-Margarit MV, Gómez-Vida J, Maldonado J, Löf M, Ruiz JR, Labayen I, Ortega FB. Effects of an Exercise Program on Cardiometabolic and Mental Health in Children With Overweight or Obesity: A Secondary Analysis of a Randomized Clinical Trial. JAMA Network Open. 2023 Jul 3;6(7):e2324839. https://doi.org/10.1001%2Fjamanetworkopen.2023.24839

Contribution: In this study, we demonstrated that an exercise intervention can reduce total adiposity measured by reference methods in up to 80% of children with overweight or obesity, as well as positively impact visceral adiposity, LDL cholesterol, and cardiorespiratory fitness.