Recording activity in proximal muscle networks with surface EMG in assessing infant motor development
| Autor: | Sampsa Vanhatalo, Oleksii Roienko, Leena Haataja, Taru Häyrinen, Anton Tokariev, Elina Ilen, Sini Hautala |
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| Přispěvatelé: | University of Helsinki, Helsinki University Hospital, BABA Center, Department of Design, Aalto-yliopisto, Aalto University, Children's Hospital, HUS Children and Adolescents, Kliinisen neurofysiologian yksikkö, HUS Medical Imaging Center, HUSLAB, Department of Neurosciences, Neuroscience Center, Clinicum |
| Rok vydání: | 2021 |
| Předmět: |
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medicine.medical_specialty Supine position Spontaneous movements Movement Neurodevelopment Posture CEREBRAL-PALSY TYPICALLY DEVELOPING INFANTS CHILDREN Electromyography 03 medical and health sciences 0302 clinical medicine Physical medicine and rehabilitation Child Development 3123 Gynaecology and paediatrics 030225 pediatrics Physiology (medical) Motor system Medicine Humans Surface electromyography Muscle activity SYNERGY Muscle Skeletal Motor skill Muscle networks PRETERM medicine.diagnostic_test business.industry Cardiac artefact Infant GENERAL MOVEMENTS Sensory Systems POSTURAL ADJUSTMENTS BRAIN NETWORKS HIGH-RISK Prone position Neurology Proximal Muscle Female Neurology (clinical) business Infants 030217 neurology & neurosurgery RESPONSES |
| Zdroj: | Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology. 132(11) |
| ISSN: | 1872-8952 |
| Popis: | Publisher Copyright: © 2021 International Federation of Clinical Neurophysiology 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. |
| Databáze: | OpenAIRE |
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