Bibliographic Details
| Title: |
Effect of innervation zones in estimating biceps brachii force–EMG relationship during isometric contraction |
| Authors: |
Rantalainen, Timo1,2,3,4 timo.rantalainen@deakin.edu.au, Kłodowski, Adam2, Piitulainen, Harri3,5 |
| Source: |
Journal of Electromyography & Kinesiology. Feb2012, Vol. 22 Issue 1, p80-87. 8p. |
| Subjects: |
Electromyography, Biceps brachii, Muscle contraction, Muscle strength measurement, Innervation, Medical statistics, Body mass index |
| Abstract: |
Abstract: Measuring muscle forces in vivo is invasive and consequently indirect methods e.g., electromyography (EMG) are used in estimating muscular force production. The aim of the present paper was to examine what kind of effect the disruption of the physiological signal caused by the innervation zone has in predicting the force/torque output from surface EMG. Twelve men (age 26 (SD ±3)years; height 179 (±6)cm; body mass 73 (±6)kg) volunteered as subjects. They were asked to perform maximal voluntary isometric contraction (MVC) in elbow flexion, and submaximal contractions at 10%, 20%, 30%, 40%, 50% and 75% of the recorded MVC. EMG was measured from biceps brachii muscle with an electrode grid of 5 columns×13 rows. Force–EMG relationships were determined from individual channels and as the global mean value. The relationship was deemed inconsistent if EMG value did not increase in successive force levels. Root mean squared errors were calculated for 3rd order polynomial fits. All subjects had at least one (4–52) inconsistent channel. Two subjects had inconsistent relationship calculated from the global mean. The mean root mean squared error calculated using leave one out method for the fits of the individual channels (0.33±0.17) was higher (P <0.001) than the error for the global mean fit (0.16±0.08). It seems that the disruption of the physiological signal caused by the innervation zone affects the consistency of the force–EMG relationship on single bipolar channel level. Multichannel EMG recordings used for predicting force overcame this disruption. [Copyright &y& Elsevier] |
|
Copyright of Journal of Electromyography & Kinesiology is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) |
| Database: |
Engineering Source |