RESEARCH PAPER
Differences in myoelectric manifestations of fatigue during isometric muscle actions
1
Medical Univesity of Lublin, Poland
2
University of Life Sciences in Lublin, Poland
Corresponding author
Ann Agric Environ Med. 2018;25(2):296-299
KEYWORDS
TOPICS
ABSTRACT
Introduction:
Muscle fatigue has been studied for a long time with the use of a wide variety of exercise models, protocols and assessment methods, among which surface electromyography (sEMG) is most commonly used. The main sEMG parameters (amplitude and frequency) are prevalently used to evaluate the level of muscle fatigue in static and dynamic contractions.
Objective:
The purpose of this study is to determine and compare 2 separate indices: IF1 basis of the sEMG signal amplitude analysis and IF2 basis of the sEMG median frequency analysis, related to muscles fatigue during an isometric contraction.
Material and methods:
The study was performed on 60 professional runners divided into 2 equal groups. The first group comprised sprinters, competing in short distance track and field events (100 and 200 meters). The second group consisted of middle-distance runners, competing in middle-distance track and field events (800 and 1,500 meters). The electrical activity of the VMO muscles of the right and left lower limbs was recorded simultaneously during isometric activity in a squatting position. The sEMG data was used to determine and compare IF1 and IF2 indices.
Results:
During isometric measurement, sprinters presented a much more significant increase in the mean amplitude of sEMG signal in comparison to middle-distance runners (mean IF1 difference: 0.228; p=0.007). Analysis of the median frequency did not show significant differences between the 2 groups (mean IF2 difference: 0.037; p=0.12).
Conclusions:
Change in sEMG amplitude during isometric exercise may be related to muscles fatigue. The use of fatigue indices, based on sEMG amplitude, as an objective indicator of the efficacy of an endurance training programme for sportsmen requires further research.
Muscle fatigue has been studied for a long time with the use of a wide variety of exercise models, protocols and assessment methods, among which surface electromyography (sEMG) is most commonly used. The main sEMG parameters (amplitude and frequency) are prevalently used to evaluate the level of muscle fatigue in static and dynamic contractions.
Objective:
The purpose of this study is to determine and compare 2 separate indices: IF1 basis of the sEMG signal amplitude analysis and IF2 basis of the sEMG median frequency analysis, related to muscles fatigue during an isometric contraction.
Material and methods:
The study was performed on 60 professional runners divided into 2 equal groups. The first group comprised sprinters, competing in short distance track and field events (100 and 200 meters). The second group consisted of middle-distance runners, competing in middle-distance track and field events (800 and 1,500 meters). The electrical activity of the VMO muscles of the right and left lower limbs was recorded simultaneously during isometric activity in a squatting position. The sEMG data was used to determine and compare IF1 and IF2 indices.
Results:
During isometric measurement, sprinters presented a much more significant increase in the mean amplitude of sEMG signal in comparison to middle-distance runners (mean IF1 difference: 0.228; p=0.007). Analysis of the median frequency did not show significant differences between the 2 groups (mean IF2 difference: 0.037; p=0.12).
Conclusions:
Change in sEMG amplitude during isometric exercise may be related to muscles fatigue. The use of fatigue indices, based on sEMG amplitude, as an objective indicator of the efficacy of an endurance training programme for sportsmen requires further research.
REFERENCES (28)
1.
Bogdanis GC. Effects of Physical Activity and Inactivity on Muscle Fatigue. Front Physiol. 2012; 3: 142.
2.
Rimmer JH, Schiller W, Chen M-D. Effects of disability-associated low energy expenditure deconditioning syndrome. Exerc Sport Sci Rev. 2012; 40(1): 22–9.
3.
Al-Mulla MR, Sepulveda F, Colley M. A Review of Non-Invasive Techniques to Detect and Predict Localised Muscle Fatigue. Sensors. 2011; 11(4): 3545–94.
4.
Zając A, Chalimoniuk M, Maszczyk A, Gołaś A, Lngfort J. Central and Peripheral Fatigue During Resistance Exercise – A Critical Review. J Hum Kinet. 2015; 49: 159–69.
5.
Shi J, Chang Q, Zheng Y-P. Feasibility of controlling prosthetic hand using sonomyography signal in real time: preliminary study. J Rehabil Res Dev. 2010; 47(2): 87–98.
6.
Orizio C, Gobbo M, Diemont B, Esposito F, Veicsteinas A. The surface mechanomyogram as a tool to describe the influence of fatigue on biceps brachii motor unit activation strategy. Historical basis and novel evidence. Eur J Appl Physiol. 2003; 90(3–4): 326–36.
7.
Guo J-Y, Zheng Y-P, Huang Q-H, Chen X. Dynamic monitoring of forearm muscles using one-dimensional sonomyography system. J Rehabil Res Dev. 2008; 45(1): 187–95.
8.
Vedsted P, Blangsted AK, Søgaard K, Orizio C, Sjøgaard G. Muscle tissue oxygenation, pressure, electrical, and mechanical responses during dynamic and static voluntary contractions. Eur J Appl Physiol. 2006; 96(2): 165–77.
9.
Subbu R, Weiler R, Whyte G. The practical use of surface electromyography during running: does the evidence support the hype? A narrative review. BMJ Open Sport Exerc. Med. 2015; 1(1): e000026.
10.
Donaldson S, Donaldson M, Snelling L. SEMG evaluations: an overview. Appl Psychophysiol Biofeedback. 2003; 28(2): 121–7.
11.
Calder KM, Stashuk DW, McLean L. Physiological characteristics of motor units in the brachioradialis muscle across fatiguing low-level isometric contractions. J Electromyogr Kinesiol Off J Int Soc Electrophysiol Kinesiol. 2008; 18(1): 2–15.
12.
Farina D, Merletti R. Comparison of algorithms for estimation of EMG variables during voluntary isometric contractions. J. Electromyogr. Kinesiol. Off. J. Int. Soc. Electrophysiol. Kinesiol. 2000; 10(5): 337–49.
13.
Allison GT, Fujiwara T. The relationship between EMG median frequency and low frequency band amplitude changes at different levels of muscle capacity. Clin Biomech Bristol Avon. 2002; 17(6): 464–9.
14.
Abboud J, Nougarou F., Descarreaux M. Muscle activity adaptations to spinal tissue creep in the presence of muscle fatigue. PLoS ONE. 2016; 11:e0149076. 10.1371/journal.pone.0149076.
15.
González-Izal M, Malanda A, Gorostiaga E, Izquierdo M. Electromyographic models to assess muscle fatigue. J Electromyogr Kinesiol Off J Int Soc Electrophysiol Kinesiol. 2012; 22(4): 501–12.
16.
Hyong IH. Effects of squats accompanied by hip joint adduction on the selective activity of the vastus medialis oblique. J Phys Ther Sci. 2015; 27(6): 1979–81.
17.
Park J, Lee D, Kim J-S, Hong J-H, You J-H, Park I. Effects of visibility and types of the ground surface on the muscle activities of the vastus medialis oblique and vastus lateralis. J Phys Ther Sci. 2015; 27(8): 2435–7.
18.
Hermens HJ, Freriks B, Disselhorst-Klug C, Rau G. Development of recommendations for SEMG sensors and sensor placement procedures. J Electromyogr Kinesiol. 2000; 10(5): 361–74.
19.
Van Lunen BL, Roberts J, Branch JD, Dowling EA. Association of Menstrual-Cycle Hormone Changes with Anterior Cruciate Ligament Laxity Measurements. J Athl Train. 2003; 38(4): 298–303.
20.
Halson SL. Monitoring Training Load to Understand Fatigue in Athletes. Sports Med Auckl Nz. 2014; 44(Suppl 2): 139–47.
21.
Vigotsky AD, Beardsley C, Contreras B, Steele J, Ogborn D, Phillips SM. Greater electromyographic responses do not imply greater motor unit recruitment and ‘hypertrophic potential’ cannot be inferred. J Strength Cond Res. 2017; 31(1): 1-4. doi: 10.1519/JSC.0000000000001249.
22.
Stania M, Chmielewska D, Kwaśna K, Smykla A, Taradaj J, Juras G. Bioelectrical activity of the pelvic floor muscles during synchronous whole-body vibration – a randomized controlled study. BMC Urol. 2015; 15: 107.
23.
Contessa P, Adam A, De Luca CJ. Motor unit control and force fluctuation during fatigue. J Appl Physiol. 2009; 107(1): 235–43.
24.
Mottram CJ, Jakobi JM, Semmler JG, Enoka RM. Motor-unit activity differs with load type during a fatiguing contraction. J Neurophysiol. 2005; 93(3): 1381–92.
25.
Balshaw TG, Pahar M, Chesham R, Macgregor LJ, Hunter AM. Reduced firing rates of high threshold motor units in response to eccentric overload. Physiol Rep. 2017; 5(2): e13111. doi: 10.14814/phy2.13111.
26.
Enoka, RM, Duchateau J. Inappropriate interpretation of surface EMG signals and muscle fiber characteristics impedes understanding of the control of neuromuscular function. J Appl Physiol. 2015; 119(12): 1516–8.
27.
Farina D. Interpretation of the surface electromyogram in dynamic contractions. Exerc Sport Sci Rev. 2006; 34(3): 121–7.
28.
Farina D, Merletti R, Nazzaro M, Caruso I. Effect of joint angle on EMG variables in leg and thigh muscles. IEEE Eng. Med. Biol. Mag. 2001; 20(6): 62–71.
| eISSN: | 1898-2263 |
| ISSN: | 1232-1966 |
Improvement of visual identification of the journal - task financed under the agreement No. 618/P-DUN/2019 by the Minister of Science and Higher Education allocated to the activities of disseminating science.
Generation of the DOI (Digital Object Identifier) - task financed under the agreement No. 618/P-DUN/2019 by the Minister of Science and Higher
© 2006-2024 Journal hosting platform by Bentus
We process personal data collected when visiting the website. The function of obtaining information about users and their behavior is carried out by voluntarily entered information in forms and saving cookies in end devices. Data, including cookies, are used to provide services, improve the user experience and to analyze the traffic in accordance with the Privacy policy. Data are also collected and processed by Google Analytics tool (more).
You can change cookies settings in your browser. Restricted use of cookies in the browser configuration may affect some functionalities of the website.
You can change cookies settings in your browser. Restricted use of cookies in the browser configuration may affect some functionalities of the website.
