Literature DB >> 17507240

EMG normalization to study muscle activation in cycling.

David M Rouffet1, Christophe A Hautier.   

Abstract

The value of electromyography (EMG) is sensitive to many physiological and non-physiological factors. The purpose of the present study was to determine if the torque-velocity test (T-V) can be used to normalize EMG signals into a framework of biological significance. Peak EMG amplitude of gluteus maximus (GMAX), vastus lateralis (VL), rectus femoris (RF), biceps femoris long head (BF), gastrocnemius medialis (GAS) and soleus (SOL) was calculated for nine subjects during isometric maximal voluntary contractions (IMVC) and torque-velocity bicycling tests (T-V). Then, the reference EMG signals obtained from IMVC and T-V bicycling tests were used to normalize the amplitude of the EMG signals collected for 15 different submaximal pedaling conditions. The results of this study showed that the repeatability of the measurements between IMVC (from 10% to 23%) and T-V (from 8% to 20%) was comparable. The amplitude of the peak EMG of VL was 99+/-43% higher (p<0.001) when measured during T-V. Moreover, the inter-individual variability of the EMG patterns calculated for submaximal cycling exercises differed significantly when using T-V bicycling normalization method (GMAX: 0.33+/-0.16 vs. 1.09+/-0.04, VL: 0.07+/-0.02 vs. 0.64+/-0.14, SOL: 0.07+/-0.03 vs. 1.00+/-0.07, RF: 1.21+/-0.20 vs. 0.92+/-0.13, BF: 1.47+/-0.47 vs. 0.84+/-0.11). It was concluded that T-V bicycling test offers the advantage to be less time and energy-consuming and to be as repeatable as IMVC tests to measure peak EMG amplitude. Furthermore, this normalization method avoids the impact of non-physiological factors on the amplitude of the EMG signals so that it allows quantifying better the activation level of lower limb muscles and the variability of the EMG patterns during submaximal bicycling exercises.

Entities:  

Mesh:

Year:  2007        PMID: 17507240     DOI: 10.1016/j.jelekin.2007.03.008

Source DB:  PubMed          Journal:  J Electromyogr Kinesiol        ISSN: 1050-6411            Impact factor:   2.368


  28 in total

1.  A method for detecting the temporal sequence of muscle activation during cycling using MRI.

Authors:  Christopher P Elder; Ryan N Cook; Kenneth L Wilkens; Marti A Chance; Otto A Sanchez; Bruce M Damon
Journal:  J Appl Physiol (1985)       Date:  2010-12-16

2.  Muscle fatigue in participants of indoor cycling.

Authors:  Ricardo de Melo Dos Santos; Flavio Costa E Costa; Thais Sepeda Saraiva; Bianca Callegari
Journal:  Muscles Ligaments Tendons J       Date:  2017-05-10

3.  Interindividual variability of electromyographic patterns and pedal force profiles in trained cyclists.

Authors:  François Hug; Jean Marc Drouet; Yvan Champoux; Antoine Couturier; Sylvain Dorel
Journal:  Eur J Appl Physiol       Date:  2008-07-16       Impact factor: 3.078

4.  Role of vision in sighted and blind soccer players in adapting to an unstable balance task.

Authors:  María Campayo-Piernas; Carla Caballero; David Barbado; Raúl Reina
Journal:  Exp Brain Res       Date:  2017-02-14       Impact factor: 1.972

5.  Comparison of human gastrocnemius forces predicted by Hill-type muscle models and estimated from ultrasound images.

Authors:  Taylor J M Dick; Andrew A Biewener; James M Wakeling
Journal:  J Exp Biol       Date:  2017-02-15       Impact factor: 3.312

6.  Shifting gears: dynamic muscle shape changes and force-velocity behavior in the medial gastrocnemius.

Authors:  Taylor J M Dick; James M Wakeling
Journal:  J Appl Physiol (1985)       Date:  2017-08-31

7.  Physiological responses to incremental, interval, and continuous counterweighted single-leg and double-leg cycling at the same relative intensities.

Authors:  Martin J MacInnis; Nathaniel Morris; Michael W Sonne; Amanda Farias Zuniga; Peter J Keir; Jim R Potvin; Martin J Gibala
Journal:  Eur J Appl Physiol       Date:  2017-05-11       Impact factor: 3.078

8.  Prevalence of musculoskeletal disorders among Indian railway sahayaks.

Authors:  Mohammed Rajik Khan; Nishant Kumar Singh
Journal:  Int J Occup Environ Health       Date:  2018-08-27

9.  Quantifying Achilles tendon force in vivo from ultrasound images.

Authors:  Taylor J M Dick; Allison S Arnold; James M Wakeling
Journal:  J Biomech       Date:  2016-08-08       Impact factor: 2.712

10.  ELECTROMYOGRAPHIC ANALYSIS OF SHOULDER GIRDLE MUSCLES DURING COMMON INTERNAL ROTATION EXERCISES.

Authors:  Omid Alizadehkhaiyat; David H Hawkes; Graham J Kemp; Simon P Frostick
Journal:  Int J Sports Phys Ther       Date:  2015-10
View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.