Video and Wearable Sensor Technologies for Early Detection of Cerebral Palsy in Infants: A Scoping Review

Charlotte F Wahle1, Aura M Elias1, Nora A Galoustian1

  • 1David Geffen School of Medicine, University of California, Los Angeles, CA 90095, USA.

PubMed

Insights

Innovative technologies like wearable sensors and video analysis show promise for early screening of cerebral palsy (CP) in infants. Further research with larger datasets is needed to confirm their diagnostic potential.

Area of Science:

  • Pediatric Neurology
  • Biomedical Engineering
  • Developmental Pediatrics

Background:

  • Early diagnosis and intervention significantly improve outcomes for infants with neurodevelopmental disorders like cerebral palsy (CP).
  • Emerging technologies offer new avenues for detecting neurodevelopmental conditions in pre-ambulatory children.

Purpose of the Study:

  • To conduct a scoping review on innovative technologies for early screening, diagnosis, and phenotyping of cerebral palsy (CP) in pre-ambulatory infants.
  • To assess the current literature on technology-assisted motor assessment for neurodevelopmental disorders.

Main Methods:

  • Searches were conducted in PubMed, Embase, and Cochrane databases.
  • Forty-eight studies were included after screening by four independent reviewers.
  • Key technologies reviewed included wearable sensors and video-based motion analysis.

Main Results:

  • Wearable sensors and video analysis are frequently used for quantifying infant movements and detecting motor abnormalities.
  • These technologies show potential for screening cerebral palsy (CP), autism spectrum disorder (ASD), and spinal muscular atrophy (SMA).
  • Studies demonstrated promising feasibility but were often limited by small sample sizes and varied validation methods.

Conclusions:

  • Technology-assisted motor assessment holds significant potential for early diagnosis and phenotyping of CP and other neurodevelopmental disorders.
  • Larger, multi-site, longitudinal datasets are crucial to validate these technologies for clinical use.
  • Further research is needed to overcome limitations in sample size and validation methods.

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