Quantified Assessment of Infant's Gross Motor Abilities Using a Multisensor WearableElisa Taylor 1, Manu Airaksinen 1, Anastasia Gallen 1, Tuuli Immonen 2, Elina Ilén 3, Taru Palsa 1,2, Leena M. Haataja 1,2, Sampsa Vanhatalo 1,4
1BABA Center, Pediatric Research Center, Department of Clinical Neurophysiology, New Children's Hospital and HUS Imaging, Helsinki, University Hospital, 2Department of Pediatric Neurology, Children's Hospital, Helsinki University Hospital and University of Helsinki, 3Department of Materials Science and Engineering, Universitat Politècnica de Catalunya, 4Department of Physiology, University of Helsinki
This paper outlines the assessment of infants' gross motor performance with a multisensor wearable and its fully automated deep learning-based analysis pipeline. The method quantifies the posture and movement patterns of infants from lying supine until they master walking independently.
