Related Experiment Video
Updated: Oct 18, 2025
Quantified Assessment of Infant's Gross Motor Abilities Using a Multisensor Wearable
Published on: May 17, 2024
Recording activity in proximal muscle networks with surface EMG in assessing infant motor development
Sini Hautala1, Anton Tokariev2, Oleksii Roienko3
1Baba Center, Children's Hospital, Helsinki University Hospital and University of Helsinki, Helsinki, Finland; Department of Clinical Neurophysiology, HUS Medical Imaging Center, University of Helsinki, Helsinki University Hospital and University of Helsinki, Helsinki, Finland.
Objective:
To develop methods for recording and analysing infant's proximal muscle activations.
Methods:
Surface electromyography (sEMG) of truncal muscles was recorded in three months old infants (N = 18) during spontaneous movement and controlled postural changes. The infants were also divided into two groups according to motor performance. We developed an efficient method for removing dynamic cardiac artefacts to allow i) accurate estimation of individual muscle activations, as well as ii) quantitative characterization of muscle networks.
Results:
The automated removal of cardiac artefacts allowed quantitation of truncal muscle activity, which showed predictable effects during postural changes, and there were differences between high and low performing infants.The muscle networks showed consistent change in network density during spontaneous movements between supine and prone position. Moreover, activity correlations in individual pairs of back muscles linked to infant́s motor performance.
Conclusions:
The hereby developed sEMG analysis methodology is feasible and may disclose differences between high and low performing infants. Analysis of the muscle networks may provide novel insight to central control of motility.
Significance:
Quantitative analysis of infant's muscle activity and muscle networks holds promise for an objective neurodevelopmental assessment of motor system.
