Neonatal motor development transitions from initially spontaneous to later increasingly complex voluntary movements. A delay in transitioning may indicate cerebral palsy (CP). The general movement optimality score (GMOS) evaluates infant movement variety and is used to diagnose CP, but depends on specialized physiotherapists, is time-consuming, and is subject to inter-observer differences. We hypothesised that an objective means of quantifying movements in young infants using motion tracking data may provide a more consistent early diagnosis of CP and reduce the burden on healthcare systems. This study assessed lower limb kinematic and muscle force variances during neonatal infant kicking movements, and determined that movement variances were associated with GMOS scores, and therefore CP. Electromagnetic motion tracking data (Polhemus) was collected from neonatal infants performing kicking movements (min 50° knee extension-flexion, <2 seconds) in the supine position over 7 minutes. Tracking data from lower limb anatomical landmarks (midfoot inferior, lateral malleolus, lateral knee epicondyle, ASIS, sacrum) were applied to subject-scaled musculoskeletal models (Gait2354_simbody, OpenSim). Inverse kinematics and static optimisation were applied to estimate lower limb kinematics (knee flexion, hip flexion, hip adduction) and muscle forces (quadriceps femoris, biceps femoris) for isolated kicks. Functional principal component analysis (fPCA) was carried out to reduce kicking kinematic and muscle force waveforms to PC scores capturing ‘modes’ of variance. GMOS scores (lower scores = reduced variety of movement) were collected in parallel with motion capture by a trained operator and specialised physiotherapist. Pearson's correlations were performed to assess if the standard deviation (SD) of kinematic and muscle force waveform PC scores, representing the intra-subject variance of movement or muscle activation, were associated with the GMOS scores.Abstract
Objectives
Methods
