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Equivalency of four research-grade movement sensors to assess movement behaviors and its implications for population surveillance

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posted on 2022-08-09, 10:55 authored by Jairo H Migueles, Pablo Molina-Garcia, Lucia V Torres-Lopez, Cristina Cadenas-Sanchez, Alex V Rowlands, Ulrich W Ebner-Priemer, Elena D Koch, Andreas Reif, Francisco B Ortega

The benefits of physical activity (PA) and sleep for health, accurate and objective population-based surveillance is important. Monitor-based surveillance has potential, but the main challenge is the need for replicable outcomes from different monitors. This study investigated the agreement of movement behavior outcomes assessed with four research-grade activity monitors (i.e., Movisens Move4, ActiGraph GT3X+, GENEActiv, and Axivity AX3) in adults. Twenty-three participants wore four monitors on the non-dominant wrist simultaneously for seven days. Open-source software (GGIR) was used to estimate the daily time in sedentary, light, moderate-to-vigorous PA (MVPA), and sleep (movement behaviors). The prevalence of participants meeting the PA and sleep recommendations were calculated from each monitor’s data. Outcomes were deemed equivalent between monitors if the absolute standardized difference and its 95% confidence intervals (CI95%) fell within ± 0.2 standard deviations (SD) of the mean of the differences. The participants were mostly men (n = 14, 61%) and aged 36 (SD = 14) years. Pairwise confusion matrices showed that 83–87% of the daily time was equally classified into the movement categories by the different pairs of monitors. The between-monitor difference in MVPA ranged from 1 (CI95%: − 6, 7) to 8 (CI95%: 1, 15) min/day. Most of the PA and sleep metrics could be considered equivalent. The prevalence of participants meeting the PA and the sleep guidelines was 100% consistent across monitors (22 and 5 participants out of the 23, respectively). Our findings indicate that the various research-grade activity monitors investigated show high inter-instrument reliability with respect to sedentary, PA and sleep-related estimates when their raw data are processed in an identical manner. These findings may have important implications for advancement towards monitor-based PA and sleep surveillance systems.


This study was conducted under the umbrella of the CoCA project supported by the European Union’s 2020 research and innovation program (grant agreement #667302). JHM is supported by the Swedish Research Council for Health, Working Life and Welfare (2021-00036). CC-S is supported by a Grant from the Spanish Ministry of Science and Innovation (FJC2018-037925-I). LVT-L is supported by a grant from the Spanish Ministry of Science, Innovation and Universities (FPU17/04802). AVR is supported by the NIHR Leicester Biomedical Research Centre, and the Collaboration for leadership in Applied Health Research and Care (CLAHRC) East Midlands. Additional funding was obtained from the University of Granada, Plan Propio de Investigación 2016, Excellence actions: Units of Excellence; Scientific Excellence Unit on Exercise and Health (UCEENS). Junta de Andalucía, Consejería de Conocimiento, Investigación y Universidades and European Regional Development Funds (ref. SOMM17/6107/UGR). In addition, funding was provided by the SAMID III network, RETICS, funded by the PN I + D+I 2017‐2021 (Spain), ISCIII‐ Sub‐Directorate General for Research Assessment and Promotion, the European Regional Development Fund (ERDF) (Ref. RD16/0022), and the EXERNET Research Network on Exercise and Health (DEP2005‐00046/ACTI; 09/UPB/19; 45/UPB/20; 27/UPB/21).



Migueles, J.H., Molina-Garcia, P., Torres-Lopez, L.V. et al. Equivalency of four research-grade movement sensors to assess movement behaviors and its implications for population surveillance. Sci Rep 12, 5525 (2022).

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Diabetes Research Centre


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