2017
DOI: 10.3389/fnhum.2017.00130
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Assessment of Upper Limb Motor Dysfunction for Children with Cerebral Palsy Based on Muscle Synergy Analysis

Abstract: Muscle synergies are considered to be building blocks underlying motor behaviors. The goal of this study is to explore an objective and effective method to assess the upper limb motor dysfunction of cerebral palsy (CP) children from the aspect of muscle synergy analysis. Fourteen CP children and 10 typically developed (TD) children were recruited to perform three similar upper limb motion tasks related to the movements of elbow and shoulder joints, and surface electromyographic (sEMG) signals were recorded fro… Show more

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Cited by 44 publications
(63 citation statements)
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“…electromyography), which will allow for a more comprehensive understanding of the changes at the muscle activity level. Furthermore, the investigation of muscle synergies has been shown to offer insights into the complexity of motor control in uCP 46,47 .…”
Section: Discussionmentioning
confidence: 99%
“…electromyography), which will allow for a more comprehensive understanding of the changes at the muscle activity level. Furthermore, the investigation of muscle synergies has been shown to offer insights into the complexity of motor control in uCP 46,47 .…”
Section: Discussionmentioning
confidence: 99%
“…The neural basis of muscle synergies is reported as housed in the spinal cord (44) and the formation of spatiotemporal synergies by the brain (45) based on evidence from non-human species. Muscle synergy analysis is used to assess the efficacy of rehabilitation (46) as a physiological marker in patients suffering from stroke or trauma (47), an assessment tool of motor coordination in patients with cerebral palsy (48), and as a tool to evaluate recovery of bilateral control in stroke patients (49,50).…”
Section: Introductionmentioning
confidence: 99%
“…To obtain the synergistic pattern of multiple elements, although component-based algorithms, such as principal component analysis (PCA) ( 26 , 27 ) and independent component analysis (ICA) ( 28 ), have been introduced to extract synergies, non-negative matrix factorization (NMF) is a better choice ( 29 , 30 ) due to its non-negative constraint for all the matrices (the raw matrix and the obtained matrices). A few works have demonstrated that NMF can be used to extract muscle synergies from multi-channel sEMG signals in upper limb muscles during motion tasks ( 31 ), even to obtain activation patterns of muscle-tendon units and time-vary coefficient curves from high-density sEMG signals during dynamic motion tasks ( 32 ).…”
Section: Introductionmentioning
confidence: 99%