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肌电图平均功率频率的变异性:斜方肌研究。

Variability of the EMG mean power frequency: A study on the trapezius muscle.

机构信息

Department of Biomechanics, University College of Health Sciences, Jönköping, Sweden; Department of Orthopedics, University of Linköping, Linköping, Sweden.

出版信息

J Electromyogr Kinesiol. 1991 Dec;1(4):237-43. doi: 10.1016/1050-6411(91)90010-3.

Abstract

Calculation of the EMG mean power frequency (MPF) is a common procedure applied in evaluation of the frequency shift associated with local muscle fatigue. Variations of the MPF that are unrelated to muscle fatigue may jeopardize the estimation of the frequency shift. Different kinds of variation include random variation and systematic variation due to changes in posture or load. In a previous article we have evaluated the systematic linear variation of the MPF. The aim of the present study was to examine the random variation. Data sequences of 10 s, each obtained from nonfatigued trapezius muscle of 19 healthy subjects, were examined over a functional range of load and joint angles with multiple regression analysis. The random variation was evaluated with residual analysis. The residual standard deviation within the whole group was 10% for surface recordings and 13% for intramuscular recordings. If only within-subject variation was considered, the corresponding values were 5 and 8%. Based on this, confidence and prediction intervals for the regression models were calculated. Ninety-five percent confidence intervals were ±1-3% around the regression surfaces, whereas 95% prediction intervals for single measurements were as large as ±20-26% for the whole group, and ±11-20% if only within-subject variations were considered. Assessment of localized muscle fatigue using single MPF estimates should therefore be avoided. Multiple measurements and regression analysis are discussed as methods to minimize the effects of random variations.

摘要

肌电图均方根频率(MPF)的计算是评估与局部肌肉疲劳相关的频率偏移的常用方法。与肌肉疲劳无关的 MPF 变化可能会影响频率偏移的估计。不同类型的变化包括随机变化和由于姿势或负荷变化引起的系统变化。在之前的一篇文章中,我们已经评估了 MPF 的系统线性变化。本研究的目的是检查随机变化。从 19 名健康受试者的非疲劳斜方肌中获得的每个 10 秒的数据序列,通过多元回归分析在功能负荷和关节角度范围内进行了检查。通过残差分析评估随机变化。整个组内的残差标准差为表面记录的 10%,为肌内记录的 13%。如果仅考虑组内变化,则相应的值分别为 5%和 8%。基于此,为回归模型计算了置信和预测区间。回归曲面周围的 95%置信区间为±1-3%,而整个组的单个测量的 95%预测区间为±20-26%,如果仅考虑组内变化,则为±11-20%。因此,应避免使用单个 MPF 估计值评估局部肌肉疲劳。讨论了多次测量和回归分析作为最小化随机变化影响的方法。

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