当前位置： SCI文献检索 > Journal of NeuroEngineering and Rehabilitation期刊下所有文献 > Model for prompt and effective classification of motion recovery after stroke considering muscle strength and coordination factors.

Model for prompt and effective classification of motion recovery after stroke considering muscle strength and coordination factors.

Abstract：

BACKGROUND:Muscle synergies are now widely discussed as a method for evaluating the existence of redundant neural networks that can be activated to enhance stroke rehabilitation. However, this approach was initially conceived to study muscle coordination during learned motions in healthy individuals. After brain damage, there are several neural adaptations that contribute to the recovery of motor strength, with muscle coordination being one of them. In this study, a model is proposed that assesses motion based on surface electromyography (sEMG) according to two main factors closely related to the neural adaptations underlying motor recovery: (1) the correct coordination of the muscles involved in a particular motion and (2) the ability to tune the effective strength of each muscle through muscle fiber contractions. These two factors are hypothesized to be affected differently by brain damage. Therefore, their independent evaluation will play an important role in understanding the origin of stroke-related motor impairments. RESULTS:The model proposed was validated by analyzing sEMG data from 18 stroke patients with different paralysis levels and 30 healthy subjects. While the factors necessary to describe motion were stable across heathy subjects, there was an increasing disassociation for stroke patients with severe motor impairment. CONCLUSIONS:The clear dissociation between the coordination of muscles and the tuning of their strength demonstrates the importance of evaluating these factors in order to choose appropriate rehabilitation therapies. The model described in this research provides an efficient approach to promptly evaluate these factors through the use of two intuitive indexes.

journal_name

J Neuroeng Rehabil

journal_title

Journal of neuroengineering and rehabilitation

authors

Costa-García Á,Ozaki KI,Yamasaki H,Itkonen M,S FA,Okajima S,Tanimoto M,Kondo I,Shimoda S

doi

10.1186/s12984-019-0611-z

subject

Has Abstract

pub_date

2019-11-04 00:00:00

pages

130

issue

issn

1743-0003

pii

10.1186/s12984-019-0611-z

journal_volume

pub_type

杂志文章

在线工具

Model for prompt and effective classification of motion recovery after stroke considering muscle strength and coordination factors.