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等长次最大活动期间的肌电图频率:肱二头肌的统计模型

EMG frequency during isometric, submaximal activity: a statistical model for biceps brachii.

作者信息

Solnik Stanisław, DeVita Paul, Grzegorczyk Krzysztof, Koziatek Anna, Bober Tadeusz

机构信息

University of Physical Education, Wrocław, Poland.

出版信息

Acta Bioeng Biomech. 2010;12(3):21-8.

Abstract

The purpose of this study was to develop a statistical model to describe the electromyography (EMG) signal frequency changes during a submaximal isometric contraction. Thirty subjects performed a 30-second isometric contraction of the biceps brachii muscle at 80% of the maximal voluntary isometric force. Surface EMG electrodes recorded electrical activity of the biceps brachii. Zero-Crossing-Rate was calculated to identify EMG frequency shifts. The mean frequencies for every one-second period were used to calculate a linear relationship between frequency and time. A significant relationship (p<0.05) between slope and initial frequency value was identified. The model described EMG frequency changes during submaximal effort of biceps brachii up to 15 seconds. The prediction error was 9.8%. Modifying this equation to initial values of frequency of each participant decreased prediction error to 7.2%. These results demonstrate that despite individual differences between subjects it is possible to derive single equation that describes EMG alterations during submaximal, isometric contractions across a homogeneous group of people.

摘要

本研究的目的是建立一个统计模型,以描述次最大等长收缩过程中肌电图(EMG)信号频率的变化。30名受试者以最大自主等长力量的80%对肱二头肌进行30秒的等长收缩。表面肌电图电极记录肱二头肌的电活动。计算过零率以识别肌电图频率变化。每一秒时间段的平均频率用于计算频率与时间之间的线性关系。确定了斜率与初始频率值之间存在显著关系(p<0.05)。该模型描述了肱二头肌次最大用力至15秒期间的肌电图频率变化。预测误差为9.8%。将该方程修改为每个参与者的频率初始值后,预测误差降至7.2%。这些结果表明,尽管受试者之间存在个体差异,但仍有可能推导出一个单一方程,用于描述同一组人群在次最大等长收缩过程中的肌电图变化。

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