An Automated Approach for General Movement Assessment: A Pilot Study

Camilla Fontana, Valeria Ottaviani, Chiara Veneroni, Sofia E. Sforza, Nicola Pesenti, Fabio Mosca, Odoardo Picciolini, Monica Fumagalli, Raffaele L. Dellacà

Research output: Contribution to journalArticlepeer-review

Abstract

Objective: The objective of the study was to develop an automatic quantitative approach to identify infants with abnormal movements of the limbs at term equivalent age (TEA) compared with general movement assessment (GMA). Methods: GMA was performed at TEA by a trained operator in neonates with neurological risk. GMs were classified as normal (N) or abnormal (Ab), which included poor repertoire and cramped synchronized movements. The signals from four micro-accelerometers placed on all limbs were recorded for 10 min simultaneously. A global index (KC_index), quantifying the characteristics of individual limb movements and the coordination among the limbs, was obtained by adding normalized kurtosis of the distribution of the first principal component of the acceleration signals to the cross-correlation of the jerk for the upper and lower limbs. Results: Sixty-eight infants were studied. A KC_index cut-off of 201.5 (95% CI: 199.9–205.0) provided specificity = 0.86 and sensitivity = 0.88 in identifying infants with Ab movements. Conclusions: KC_index provides an automatic and quantitative measure that may allow the identification of infants who require further neurological evaluation.

Original languageEnglish
Article number720502
JournalFrontiers in Pediatrics
Volume9
DOIs
Publication statusPublished - Aug 25 2021

Keywords

  • accelerometer
  • general movement assessment
  • infant
  • neurodevelopment
  • newborn

ASJC Scopus subject areas

  • Pediatrics, Perinatology, and Child Health

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