Your browser doesn't support javascript.
loading
Spasticity Assessment Based on the Maximum Isometrics Voluntary Contraction of Upper Limb Muscles in Post-stroke Hemiplegia.
Wang, Hui; Huang, Pingao; Li, Xiangxin; Samuel, Oluwarotimi Williams; Xiang, Yun; Li, Guanglin.
Afiliación
  • Wang H; CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China.
  • Huang P; Shenzhen College of Advanced Technology, University of Chinese Academy of Sciences, Shenzhen, China.
  • Li X; CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China.
  • Samuel OW; Shenzhen College of Advanced Technology, University of Chinese Academy of Sciences, Shenzhen, China.
  • Xiang Y; CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China.
  • Li G; CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China.
Front Neurol ; 10: 465, 2019.
Article en En | MEDLINE | ID: mdl-31133969
ABSTRACT

Background:

The assessment of muscle properties is an essential prerequisite in the treatment of post-stroke patients with limb spasticity. Most existing spasticity assessment approaches do not consider the muscle activation with voluntary contraction. Including voluntary movements of spastic muscles may provide a new way for the reliable assessment of muscle spasticity.

Objective:

In this study, we investigated the effectiveness and reliability of maximum isometrics voluntary contraction (MIVC) based method for spasticity assessment in post-stroke hemiplegia.

Methods:

Fourteen post-stroke hemiplegic patients with arm spasticity were asked to perform two tasks MIVC and passive isokinetic movements. Three biomechanical signals, torque, position, and time, were recorded from the impaired and non-impaired arms of the patients. Three features, peak torque, keep time of the peak torque, and rise time, were computed from the recorded MIVC signals and used to evaluate the muscle voluntary activation characteristics, respectively. For passive movements, two features, the maximum resistance torque and muscle stiffness, were also obtained to characterize the properties of spastic stretch reflexes. Subsequently, the effectiveness and reliability of the MIVC-based spasticity assessment method were evaluated with spearman correlation analysis and intra class correlation coefficients (ICCs) metrics.

Results:

The results indicated that the keep time of peak torque and rise time in the impaired arm were higher in comparison to those in the contralateral arm, whereas the peak torque in the impaired side was significantly lower than their contralateral arm. Our results also showed a significant positive correlation (r = 0.503, p = 0.047) between the keep time (tk) and the passive resistant torque. Furthermore, a significantly positive correlation was observed between the keep time (tk) and the muscle stiffness (r = 0.653, p = 0.011). Meanwhile, the ICCs for intra-time measurements of MIVC ranged between 0.815 and 0.988 with one outlier.

Conclusion:

The findings from this study suggested that the proposed MIVC-based approach would be promising for the reliable and accurate assessment of spasticity in post-stroke patients.
Palabras clave

Texto completo: 1 Base de datos: MEDLINE Idioma: En Revista: Front Neurol Año: 2019 Tipo del documento: Article

Texto completo: 1 Base de datos: MEDLINE Idioma: En Revista: Front Neurol Año: 2019 Tipo del documento: Article