The Upper Extremity Function of Stroke Patients in the View of Surface Electromyography

Bastlová, Petra; Frgalová, Ivana Barbora; Kolářová, Barbora; Elfmark, Milan; Krobot, Alois

doi:10.5507/pol.2014.007

Cited by 3 publications

(1 citation statement)

References 18 publications

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“…Compensatory movements can occur via the recruitment of additional agonist muscles, thereby distributing the muscle force on other agonists (McCrea et al, 2005 ). Previous studies showed that in patients lacking the activity of the Pm muscle, have an increased activation of Tr as compensation (Bastlová et al, 2014 ). The findings of the present study seem to integrate this statement suggesting that patients lacking Da and/or Tr activity might partially compensate with pectoralis, as in Cluster 3, even if with lower motor outcome.…”

Section: Discussionmentioning

confidence: 99%

Muscle Synergies-Based Characterization and Clustering of Poststroke Patients in Reaching Movements

Scano

Chiavenna

Malosio

et al. 2017

Front. Bioeng. Biotechnol.

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BackgroundA 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 coactivate 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 article, the synergy analysis was used to characterize a group of chronic poststroke hemiplegic patients.MethodsTwenty-two poststroke patients performed a session composed of a sequence of 3D reaching movements. They were assessed through an instrumental assessment, by recording kinematics and electromyography 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.ResultsMotor synergies were successfully extracted on all 22 patients. Five 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.ConclusionThe clustering of muscle synergies enabled a pretherapy characterization of patients. Such technique may affect several aspects of the therapy: prediction of outcomes, evaluation of the treatments, customization of doses, and therapies.

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Section: Discussionmentioning

confidence: 99%