[Developmental neurology - networked medicine and new perspectives]

U Tacke1, H Weigand-Brunnhölzl2, A Hilgendorff2,3

  • 1Abteilung für Neuropädiatrie und Entwicklung, Universitäts-Kinderspital beider Basel (UKBB), Spitalstraße 33, Postfach, 4031, Basel, Schweiz. Uta.Tacke@ukbb.ch.

Der Nervenarzt
|November 5, 2017
PubMed

Insights

Developmental neurology monitors infant development, focusing on high-risk infants. Early detection of developmental deviations through methods like general movements (GM) analysis enables timely interventions for better long-term outcomes.

Area of Science:

  • Neurology
  • Developmental Pediatrics

Background:

  • Developmental neurology is crucial for monitoring infant motor, cognitive, and psychosocial progress.
  • High-risk infants, including premature babies (before 32 weeks gestation) or those with low birth weight (<1500g), require specialized attention.
  • Early diagnosis of developmental deviations is essential for timely interventions.

Purpose of the Study:

  • To review current methods in developmental neurology, emphasizing recent advancements.
  • To highlight the predictive value of general movements (GM) in infant development assessment.
  • To demonstrate automated, markerless detection of spontaneous movements using depth imaging.

Main Methods:

  • Review of existing developmental neurology techniques.
  • Focus on the analysis of general movements (GM).
  • Development and demonstration of markerless automated movement detection using depth cameras.

Main Results:

  • General movements (GM) show significant predictive value for developmental outcomes.
  • Automated, markerless detection of spontaneous infant movements is feasible with current technology.
  • Distinct spontaneous movement patterns were observed in 12-week-old infants with varying diagnoses (healthy, genetic syndrome, cerebral palsy).

Conclusions:

  • Developmental neurology relies on early detection and intervention for optimal infant outcomes.
  • General movements (GM) analysis, particularly with automated detection, offers a promising tool for early diagnosis.
  • Objective analysis of spontaneous movements can aid in differentiating developmental trajectories in infants.