The probability density function of the surface electromyogram and its dependence on contraction force in the vastus lateralis.

IF 2.9 4区 医学 Q3 ENGINEERING, BIOMEDICAL
Javier Rodriguez-Falces, Armando Malanda, Cristina Mariscal, Silvia Recalde, Javier Navallas
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Abstract

Introduction: The probability density function (PDF) of the surface electromyogram (sEMG) depends on contraction force. This dependence, however, has so far been investigated by having the subject generate force at a few fixed percentages of MVC. Here, we examined how the shape of the sEMG PDF changes with contraction force when this force was gradually increased from zero.

Methods: Voluntary surface EMG signals were recorded from the vastus lateralis of healthy subjects as force was increased in a continuous manner vs. in a step-wise fashion. The sEMG filling process was examined by measuring the EMG filling factor, computed from the non-central moments of the rectified sEMG signal.

Results: (1) In 84% of the subjects, as contraction force increased from 0 to 10% MVC, the sEMG PDF shape oscillated back and forth between the semi-degenerate and the Gaussian distribution. (2) The PDF-force relation varied greatly among subjects for forces between 0 and ~ 10% MVC, but this variability was largely reduced for forces above 10% MVC. (3) The pooled analysis showed that, as contraction force gradually increased, the sEMG PDF evolved rapidly from the semi-degenerate towards the Laplacian distribution from 0 to 5% MVC, and then more slowly from the Laplacian towards the Gaussian distribution for higher forces.

Conclusions: The study demonstrated that the dependence of the sEMG PDF shape on contraction force can only be reliably assessed by gradually increasing force from zero, and not by performing a few constant-force contractions. The study also showed that the PDF-force relation differed greatly among individuals for contraction forces below 10% MVC, but this variability was largely reduced when force increased above 10% MVC.

外侧肌表面肌电图的概率密度函数及其与收缩力的关系。
简介表面肌电图(sEMG)的概率密度函数(PDF)取决于收缩力。然而,迄今为止,对这种依赖性的研究都是通过让受试者在几种固定的 MVC 百分比下产生力来进行的。在此,我们研究了当收缩力从零开始逐渐增加时,肌电图 PDF 的形状如何随收缩力而变化:方法:我们从健康受试者的外侧阔肌记录了持续增加力量与逐步增加力量时的自主表面肌电信号。结果:(1)在 84% 的受试者中,当收缩力从 0 增加到 10% MVC 时,肌电图 PDF 的形状在半退化分布和高斯分布之间来回摆动。(2)不同受试者的 PDF 与收缩力的关系在收缩力为 0 到 10% MVC 之间时变化很大,但当收缩力超过 10%MVC时,这种变化就大大减小了。(3) 汇总分析表明,随着收缩力的逐渐增加,从 0 到 5% MVC,sEMG PDF 迅速从半退化分布向拉普拉斯分布演化,然后在更大的收缩力下,从拉普拉斯分布向高斯分布演化的速度更慢:该研究表明,只有通过从零开始逐渐增加力量,而不是通过进行几次恒定力量的收缩,才能可靠地评估 sEMG PDF 形状对收缩力的依赖性。研究还表明,当收缩力低于 10% MVC 时,不同个体的 PDF 与收缩力的关系差异很大,但当收缩力增加到 10% MVC 以上时,这种差异就会大大减小。
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来源期刊
BioMedical Engineering OnLine
BioMedical Engineering OnLine 工程技术-工程:生物医学
CiteScore
6.70
自引率
2.60%
发文量
79
审稿时长
1 months
期刊介绍: BioMedical Engineering OnLine is an open access, peer-reviewed journal that is dedicated to publishing research in all areas of biomedical engineering. BioMedical Engineering OnLine is aimed at readers and authors throughout the world, with an interest in using tools of the physical and data sciences and techniques in engineering to understand and solve problems in the biological and medical sciences. Topical areas include, but are not limited to: Bioinformatics- Bioinstrumentation- Biomechanics- Biomedical Devices & Instrumentation- Biomedical Signal Processing- Healthcare Information Systems- Human Dynamics- Neural Engineering- Rehabilitation Engineering- Biomaterials- Biomedical Imaging & Image Processing- BioMEMS and On-Chip Devices- Bio-Micro/Nano Technologies- Biomolecular Engineering- Biosensors- Cardiovascular Systems Engineering- Cellular Engineering- Clinical Engineering- Computational Biology- Drug Delivery Technologies- Modeling Methodologies- Nanomaterials and Nanotechnology in Biomedicine- Respiratory Systems Engineering- Robotics in Medicine- Systems and Synthetic Biology- Systems Biology- Telemedicine/Smartphone Applications in Medicine- Therapeutic Systems, Devices and Technologies- Tissue Engineering
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