1. Recording activity in proximal muscle networks with surface EMG in assessing infant motor development.
- Author
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Hautala S, Tokariev A, Roienko O, Häyrinen T, Ilen E, Haataja L, and Vanhatalo S
- Subjects
- Female, Humans, Infant, Male, Child Development physiology, Electromyography methods, Movement physiology, Muscle, Skeletal growth & development, Posture physiology
- Abstract
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., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.)
- Published
- 2021
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