【24h】

Between-day reliability of a method for non-invasive estimation of muscle composition

机译:日间可靠性的无创估计肌肉成分的方法

获取原文
获取原文并翻译 | 示例
           

摘要

Tensiomyography is a method for valid and non-invasive estimation of skeletal muscle fibre type composition. The validity of selected temporal tensiomyographic measures has been well established recently; there is, however, no evidence regarding the method's between-day reliability. Therefore it is the aim of this paper to establish the between-day repeatability of tensiomyographic measures in three skeletal muscles. For three consecutive days, 10 healthy male volunteers (mean ± SD: age 24.6 ± 3.0. years; height 177.9 ± 3.9. cm; weight 72.4 ± 5.2. kg) were examined in a supine position. Four temporal measures (delay, contraction, sustain, and half-relaxation time) and maximal amplitude were extracted from the displacement-time tensiomyogram. A reliability analysis was performed with calculations of bias, random error, coefficient of variation (CV), standard error of measurement, and intra-class correlation coefficient (ICC) with a 95% confidence interval. An analysis of ICC demonstrated excellent agreement (ICC were over 0.94 in 14 out of 15 tested parameters). However, lower CV was observed in half-relaxation time, presumably because of the specifics of the parameter definition itself. These data indicate that for the three muscles tested, tensiomyographic measurements were reproducible across consecutive test days. Furthermore, we indicated the most possible origin of the lowest reliability detected in half-relaxation time.
机译:张力描记术是一种有效且无创地估计骨骼肌纤维类型组成的方法。近期选择的颞肌张力描记术措施的有效性已得到很好的证实。但是,没有证据表明该方法具有日间可靠性。因此,本文的目的是建立张力描记术在三块骨骼肌中的日间重复性。连续三天,以仰卧位检查了10名健康的男性志愿者(平均±SD:年龄24.6±3.0。岁;身高177.9±3.9。cm;体重72.4±5.2。kg)。从位移时间张肌张力图中提取了四个时间量度(延迟,收缩,维持和半松弛时间)和最大振幅。通过对偏差,随机误差,变异系数(CV),测量的标准误差和类内相关系数(ICC)进行计算,并以95%置信区间进行可靠性分析。对ICC的分析显示出极好的一致性(15个测试参数中有14个的ICC均超过0.94)。但是,半松弛时间观察到的CV较低,这可能是由于参数定义本身的细节所致。这些数据表明,对于所测试的三块肌肉,在连续的测试日中张力肌电图测量结果是可重现的。此外,我们指出了在半松弛时间中检测到的最低可靠性的最大可能来源。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号