Evidence map›Paper›PMID 41691292›Full record

ArticleJournal of neuroengineering and rehabilitation2026

Cluster-based muscle synergy analysis scheme for assessing crawling motor function in children with cerebral palsy.

Chengxiang Li, Xiang Chen, Xu Zhang, De Wu, Guanglin Li, Peng Fang

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In one paragraph

Article in Journal of neuroengineering and rehabilitation, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Chengxiang LiSchool of Information Science and Technology, University of Science and Technology of China, Hefei, China.
Xiang ChenSchool of Information Science and Technology, University of Science and Technology of China, Hefei, China. xch@ustc.edu.cn.
Xu ZhangSchool of Information Science and Technology, University of Science and Technology of China, Hefei, China.
De WuDepartment of Pediatrics, the First Affiliated Hospital of Anhui Medical University, Hefei, China.
Guanglin LiShenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China.
Peng FangShenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China. peng.fang@siat.ac.cn.

Funding

National Natural Science Foundation of China 61671417, U21A20479Shenzhen Engineering Laboratory of Neural Rehabilitation Technology N/AShenzhen Municipal Fundamental Research Program JCYJ20241202124935047Youth Innovation Promotion Association of the Chinese Academy of Sciences Y2022094
6 · The paper itself

Abstract

objectiveThis study aims to evaluate the crawling motor function in children with cerebral palsy (CP) using a cluster-based muscle synergy analysis scheme.

methodsSurface electromyography (sEMG) signals were recorded from 26 muscles across the body in 14 typically developing (TD) subjects and 10 children with CP while they performed eight prescribed crawling modes. The sEMG signals were preprocessed, and muscle synergies were extracted using a non-negative matrix factorization (NNMF) algorithm. A hierarchical clustering algorithm, incorporating synergy similarity constraints, was employed to cluster synergies from TD subjects performing the same crawling mode, identifying common synergies within each mode. A subsequent clustering process revealed common synergies across different modes. Using the common synergies of TD subjects as a benchmark, four evaluation metrics based on synergy similarity were developed to assess the crawling motor function in children with CP.

resultsThe analysis successfully extracted common synergies within and across crawling modes in TD subjects. Under the condition of auditory cueing, children with CP showed a significantly lower number and similarity of common synergy structures while maintaining a comparable number of common recruitment curves relative to the TD subjects.

conclusionThe cluster-based muscle synergy analysis scheme effectively assesses the crawling motor function in children with CP.

Indexed as

Cerebral PalsyMuscle, SkeletalAlgorithmsChildCluster AnalysisClustering AlgorithmsElectromyographyFemaleHumansMaleCerebral palsyHand-knee crawlingHierarchical clusteringMuscle synergy

Identifiers

PMID41691292
PMCPMC13011333

What Socratic holds

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LicenceCC BY-NC-ND
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.