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• W2762488501 abstract "Background: A deep characterization of neurological patients is a crucial step for a detailed knowledge of the pathology and maximal exploitation and customization of the rehabilitation therapy. The muscle synergies analysis was designed to investigate how muscles co-activate and how their eliciting commands change in time during movement production. Few studies investigated the value of muscle synergies for the characterization of neurological patients before rehabilitation therapies. In this paper, the synergy analysis was used to characterize a group of chronic post-stroke hemiplegic patients. Methods: Twenty-two post-stroke patients performed a session composed of a sequence of 3D reaching movements. They were assessed through an instrumental assessment, by recording kinematics and EMG to extract muscle synergies and their activation commands. Patients’ motor synergies were grouped by the means of cluster analysis. Consistency and characterization of each cluster was assessed and clinically profiled by comparison with standard motor assessments. Results: Motor synergies were successfully extracted on all 22 patients. 5 basic clusters were identified as a trade-off between clustering precision and synthesis power, representing: healthy-like activations, two shoulder compensatory strategies, two elbow predominance patterns. Each cluster was provided with a deep characterization and correlation with clinical scales, range of motion and smoothness. Conclusions: The clustering of Muscle Synergies enabled a pre-therapy characterization of patients. Such technique may affect several aspects of the therapy: prediction of outcomes, evaluation of the treatments, customization of doses and therapies. Keywords: Muscle Synergies, Centroids, Synergies Clustering, Reaching Performance Scale, Fugl-Meyer Assessment" @default.
• W2762488501 created "2017-10-20" @default.
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• W2762488501 date "2017-10-13" @default.
• W2762488501 modified "2023-10-10" @default.
• W2762488501 title "Muscle Synergies-Based Characterization and Clustering of Poststroke Patients in Reaching Movements" @default.
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• W2762488501 doi "https://doi.org/10.3389/fbioe.2017.00062" @default.
• W2762488501 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/5645509" @default.
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• W2762488501 hasPublicationYear "2017" @default.
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