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Updated: Jul 16, 2026

Quantified Assessment of Infant's Gross Motor Abilities Using a Multisensor Wearable
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Nonlinear Measures Applied to Spontaneous Infant Movement Analysis: A Scoping Review.

Joana Ferreira1,2,3,4, Marta Freitas5,6, Sofia Gaspar4

  • 1Research Center in Physical Activity, Health and Leisure (CIAFEL), Faculty of Sport, University of Porto (FADEUP), 4200-450 Porto, Portugal.

Sensors (Basel, Switzerland)
|July 15, 2026
PubMed
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Nonlinear measures analyze infant movement dynamics for neurodevelopmental insights. Standardized protocols are needed for clinical use of these complex movement analysis tools.

Area of Science:

  • Neuroscience and Developmental Pediatrics
  • Biomedical Engineering and Movement Science

Background:

  • Spontaneous infant movement analysis is crucial for understanding central nervous system maturation and motor control development.
  • Nonlinear measures offer dynamic insights into movement beyond linear methods but face clinical implementation challenges due to a lack of standardization.

Purpose of the Study:

  • To systematically map and characterize nonlinear measures used in the analysis of spontaneous infant movement.
  • To identify assessment contexts, instruments, data collection protocols, and key variables employed in nonlinear movement analysis.

Main Methods:

  • A scoping review adhering to JBI methodology and PRISMA-ScR guidelines.
  • Searches across major scientific databases (PubMed, Web of Science, IEEE Xplore, ScienceDirect, Google Scholar) from January 2005 to December 2025.
Keywords:
early motor developmentmotor complexitymovement variabilityneurodevelopmental assessment

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  • Inclusion of 18 studies analyzing nonlinear measures of infant spontaneous movement.

    • Main Results:

    • Nonlinear measures were categorized into five families: entropy-based (n=10), state-space/dynamical systems (n=4), recurrence-based (n=3), symbolic/discrete-state (n=3), and variance/frequency-based (n=1).
    • Studies utilized laboratory (n=6) and real-world environments (n=10), employing kinematic (video, accelerometers, wearables) and kinetic (pressure mats, force platforms) assessments.
    • Analysis extended from single joints to inter-limb and whole-body coordination.

    Conclusions:

    • Significant heterogeneity exists in nonlinear movement analysis protocols, hindering clinical translation.
    • Future research must prioritize methodological harmonization, theoretical clarity, and consensus on data requirements, parameter selection, and reporting standards.
    • Adoption of multivariate frameworks integrating complementary nonlinear metrics is recommended for objective neurodevelopmental assessment.