Prediction of Maximal Surface Electromyographically Based Voluntary Contractions of Erector Spinae Muscles From Sonographic Measurements During Isometric Contractions

被引:3
|
作者
Cuesta-Vargas, Antonio I. [1 ,2 ]
Gonzalez-Sanchez, Manuel [1 ]
机构
[1] Univ Malaga, Dept Physiotherapy, Dept Fisioterapia, Malaga 29071, Spain
[2] Queensland Univ Technol, Sch Clin Sci, Fac Hlth, Kelvin Grove, Qld, Australia
关键词
electromyography; musculoskeletal ultrasound; regression analysis; sonography; spine; JOINT MOMENTS; ARCHITECTURE; MODEL; ULTRASOUND; THICKNESS; FLEXION; FORCES; ANGLE; REST;
D O I
10.7863/ultra.33.3.399
中图分类号
O42 [声学];
学科分类号
070206 ; 082403 ;
摘要
Objectives-Currently, there are no studies combining electromyography (EMG) and sonography to estimate the absolute and relative strength values-of erector spinae (ES) muscles in healthy individuals. The purpose of this study was to establish whether the maximum voluntary contraction (MVC) of the ES during isometric contractions could be predicted from the changes in surface EMG as well as in fiber pennation and thickness as measured by sonography. Methods Thirty healthy adults performed 3 isometric extensions at 45 from the vertical to calculate the MVC force. Contractions at 33% and 100% of the MVC force were then used during sonographic and EMG recordings. These measurements were used to observe the architecture and function of the muscles during contraction. Statistical analysis was performed using bivariate regression and regression equations. Results The slope for each regression equation was statistically significant (P < .001) with R-2 values of 0.837 and 0.986 for the right and left ES, respectively. The standard error estimate between the sonographic measurements and the regression-estimated pennation angles for the right and left ES were 0.10 and 0.02, respectively. Conclusions Erector spinae muscle activation can be predicted from the changes in fiber pennation during isometric contractions at 33% and 100% of the MVC force. These findings could be essential for developing a regression equation that could estimate the level of muscle activation from changes in the muscle architecture.
引用
收藏
页码:399 / 404
页数:6
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