Biceps Brachii Kasi İçin Maksimal ve Sabit Yük Altinda Submaksimal Kasilmalara Göre Elektromiyografik Normalizasyon Yöntemlerinin Güvenilirliği ve Korelasyonu

Öz

Yüzeyel elektromiyografi (yEMG) sinyal genliğinin normalleştirilmesi, farklı kaslar, bireyler, seanslar arasında karşılaştırılabilir veriler sağlamak için gerekli bir işlem olarak kabul edilir. Önceki çalışmalar genellikle maksimal istemli kasılma normalizasyon yöntemini kullanmayı önermiştir. Ancak, bu yöntem bazı yEMG çalışmalarında her zaman mümkün ya da en iyi yöntem olmayabilir. Bu çalışmanın iki temel amacı vardır. Birincisi, farklı yükler altında iki farklı submaksimal izometrik kasılma normalizasyon prosedürünün (görsel geri beslemeli ve geri beslemesiz) güvenilirliğini araştırmaktır. İkincisi, maksimal istemli kasılma ve submaksimal izometrik kasılma görevlerinden elde edilen normalizasyon değerleri arasındaki korelasyonu araştırmaktır. Bu deneysel çalışmaya 18 genç sağlıklı katılımcı gönüllü olarak katılmıştır. Denekler üç kas kasılması görevi gerçekleştirdiler. Bunlar sırasıyla şöyledir: (i) maksimal istemli kasılma görevi: biseps brachii kasının izometrik maksimal istemli kasılması, (ii) kuvvet eşleştirme görevi: 2.5 kg, 5.0 kg, 7.5 kg ve 10.0 kg yük ve görsel geri bildirim ile, (iii) yük tutma görevi: görsel geri bildirim olmadan 2,5 kg, 5,0 kg, 7,5 kg ve 10,0 kg ağırlıkları tutmak. yEMG genlik normalizasyon değerleri üç görev için incelenmiştir. Çalışmanın sonuçları, kuvvet eşleştirme ve yük tutma görevlerinden elde edilen normalizasyon değerlerinin güvenilirliğin yüksek (güvenirlik katsayısı 0.863 ve 0.958 arasında) ya da çok yüksek (güvenirlik katsayısı 0.970 ve 0.995 arasında) olduğunu göstermiştir. Maksimal istemli kasılma normalizasyon yönteminin bazı sınırlılıkları nedeniyle, bazı yEMG çalışmaları için maksimale göre normalizasyon her zaman mümkün ya da en iyi yöntem olmayabilir. Bu gibi durumlarda, submaksimal izometrik yük tutma görevi, biceps brachii kası için maksimal istemli kasılma görevine tekrarlanabilir bir alternatif olabilir.

Anahtar Kelimeler

• elektromiyografi
• normalizasyon
• biseps brachii

Reliability of and Correlation Among Electromyographic Normalization Procedures for Biceps Brachii Muscle: A Comparison of Maximal and Submaximal Isometric Voluntary Contractions

Öz

Normalization of surface electromyography (sEMG) signal amplitude is considered as a necessary operation to enable comparable data on different muscles, individuals, and sessions. Previous studies usually suggested using the maximal contraction normalization procedure. However, that procedure might not always be possible or the best method in some sEMG studies. The purpose of this study is therefore twofold. The first is to investigate reliability of two different constant load normalization procedures (with and without feedback) at different constant-force submaximal contractions. The second is to investigate correlation of normalization factors obtained from maximal voluntary and standardized submaximal tasks. 18 young healthy participants took part in the study. Subjects performed three muscle contraction tasks, namely, (i) maximal voluntary contraction (MVC) task: isometric maximal contraction of biceps brachii muscle, (ii) force matching task (FM): matching 2.5 kg, 5.0 kg, 7.5 kg and 10.0 kg force with visual feedback, and (iii) load holding (LH) task: holding 2.5 kg, 5.0 kg, 7.5 kg and 10.0 kg weights without visual feedback. sEMG amplitude normalization factors were examined for three tasks. The results of the study suggested that the reliability of sEMG amplitude normalization factors from FM and LH tasks for four target forces or loads were high (intraclass correlation (ICC): 0.863-0.958) to very high (ICC: 0.970-0.995). Due to some limitations of the MVC maximal contraction normalization procedure, normalization to the maximal might not always be possible or the best method for some sEMG studies. In such cases, submaximal isometric load holding tasks could be an alternative to the MVC task for biceps brachii muscle.

Anahtar Kelimeler

• electromyography
• biceps brachii
• normalization

Kaynakça

1. 1. Athreya, D. N., Van Orden, G., and Riley, M. A. (2012). Feedback about isometric force production yields more random variations. Neuroscience Letters, 513(1), 37–41. https://doi.org/10.1016/j.neulet.2012.02.002
2. 2. Baweja, H. S., Patel, B. K., Martinkewiz, J. D., Vu, J., and Christou, E. A. (2009). Removal of visual feedback alters muscle activity and reduces force variability during constant isometric contractions. Experimental Brain Research, 197(1), 35–47. https://doi.org/10.1007/s00221-009-1883-5
3. 3. Baweja, H. S., Patel, B. K., Neto, O. P., and Christou, E. A. (2011). The interaction of respiration and visual feedback on the control of force and neural activation of the agonist muscle. Human Movement Science, 30(6), 1022–1038. https://doi.org/10.1016/j.humov.2010.09.007
4. 4. Besomi, M., Hodges, P. W., Clancy, E. A., Van Dieën, J., Hug, F., Lowery, M., Merletti, R., Søgaard, K., Wrigley, T., Besier, T., Carson, R. G., Disselhorst-Klug, C., Enoka, R. M., Falla, D., Farina, D., Gandevia, S., Holobar, A., Kiernan, M. C., McGill, K., … Tucker, K. (2020). Consensus for experimental design in electromyography (CEDE) project: Amplitude normalization matrix. Journal of Electromyography and Kinesiology, 53, 102438. https://doi.org/10.1016/j.jelekin.2020.102438
5. 5. Buckthorpe, M. W., Hannah, R., Pain, T. G., and Folland, J. P. (2012). Reliability of neuromuscular measurements during explosive isometric contractions, with special reference to electromyography normalization techniques: Reliability of Explosive Neuromuscular Measurements. Muscle and Nerve, 46(4), 566–576. https://doi.org/10.1002/mus.23322
6. 6. Burden, A. (2010). How should we normalize electromyograms obtained from healthy participants? What we have learned from over 25 years of research. Journal of Electromyography and Kinesiology, 20(6), 1023–1035. https://doi.org/10.1016/j.jelekin.2010.07.004
7. 7. Burnett, A., Green, J., Netto, K., and Rodrigues, J. (2007). Examination of EMG normalisation methods for the study of the posterior and posterolateral neck muscles in healthy controls. Journal of Electromyography and Kinesiology, 17(5), 635–641. https://doi.org/10.1016/j.jelekin.2006.06.003
8. 8. Carter, R. E., and Lubinsky, J. (2016). Rehabilitation research: Principles and applications (Fifth edition). Elsevier.

9. 9. Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed). L. Erlbaum Associates.
10. 10. Dankaerts, W., O’Sullivan, P. B., Burnett, A. F., Straker, L. M., and Danneels, L. A. (2004). Reliability of EMG measurements for trunk muscles during maximal and sub-maximal voluntary isometric contractions in healthy controls and CLBP patients. Journal of Electromyography and Kinesiology, 14(3), 333–342. https://doi.org/10.1016/j.jelekin.2003.07.001
11. 11. De Luca, C. J. (1997). The use of surface electromyography in biomechanics. Journal of Applied Biomechanics, 13(2), 135–163. https://doi.org/10.1123/jab.13.2.135
12. 12. Donoghue, J. P., Sanes, J. N., Hatsopoulos, N. G., and Gaál, G. (1998). Neural discharge and local field potential oscillations in primate motor cortex during voluntary movements. Journal of Neurophysiology, 79(1), 159–173. https://doi.org/10.1152/jn.1998.79.1.159
13. 13. Farina, D., Leclerc, F., Arendt-Nielsen, L., Buttelli, O., and Madeleine, P. (2008). The change in spatial distribution of upper trapezius muscle activity is correlated to contraction duration. Journal of Electromyography and Kinesiology, 18(1), 16–25. https://doi.org/10.1016/j.jelekin.2006.08.005
14. 14. Faul, F., Erdfelder, E., Lang, A.-G., and Buchner, A. (2007). G*Power 3: A flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behavior Research Methods, 39(2), 175–191. https://doi.org/10.3758/BF03193146
15. 15. Fischer, S. L., Belbeck, A. L., and Dickerson, C. R. (2010). The influence of providing feedback on force production and within-participant reproducibility during maximal voluntary exertions for the anterior deltoid, middle deltoid, and infraspinatus. Journal of Electromyography and Kinesiology, 20(1), 68–75. https://doi.org/10.1016/j.jelekin.2009.01.007
16. 16. Halaki, M., and Ginn, K. (2012). Normalization of EMG signals: To normalize or not to normalize and what to normalize to? In G. R. Naik (Ed.), Computational ıntelligence in electromyography analysis—A perspective on current applications and future challenges. InTech. https://doi.org/10.5772/49957
17. 17. Hermens, H. J., Freriks, B., Disselhorst-Klug, C., and Rau, G. (2000). Development of recommendations for SEMG sensors and sensor placement procedures. Journal of Electromyography and Kinesiology, 10(5), 361–374. https://doi.org/10.1016/S1050-6411(00)00027-4
18. 18. Hug, F., and Tucker, K. (2018). Surface electromyography to study muscle coordination. In Handbook of Human Motion (pp. 451–470). Springer International Publishing. https://doi.org/10.1007/978-3-319-14418-4_184
19. 19. Ito, M., Kawakami, Y., Ichinose, Y., Fukashiro, S., and Fukunaga, T. (1998). Nonisometric behavior of fascicles during isometric contractions of a human muscle. Journal of Applied Physiology, 85(4), 1230–1235. https://doi.org/10.1152/jappl.1998.85.4.1230
20. 20. Kazennikov, O. V., and Levik, I. S. (2009). Study of the motor cortex excitability in the task of holding load. Fiziologiia Cheloveka, 35(5), 71–78.
21. 21. Martinek, R., Ladrova, M., Sidikova, M., Jaros, R., Behbehani, K., Kahankova, R., and Kawala-Sterniuk, A. (2021). Advanced bioelectrical signal processing methods: Past, present, and future approach—Part III: Other biosignals. Sensors, 21(18), 6064. https://doi.org/10.3390/s21186064
22. 22. McGraw, K. O., and Wong, S. P. (1996). Forming inferences about some intraclass correlation coefficients. Psychological Methods, 1(1), 30–46. https://doi.org/10.1037/1082-989X.1.1.30
23. 23. Merletti, R., and Parker, P. (Eds.). (2004). Electromyography: Physiology, engineering, and noninvasive applications. IEEE/John Wiley and Sons.
24. 24. Mirka, G. A. (1991). The quantification of EMG normalization error. Ergonomics, 34(3), 343–352. https://doi.org/10.1080/00140139108967318
25. 25. Pieter Clarys, J., Scafoglieri, A., Tresignie, J., Reilly, T., and Van Roy, P. (2010). Critical appraisal and hazards of surface electromyography data acquisition in sport and exercise. Asian Journal of Sports Medicine, 1(2), 69–80.
26. 26. Soylu, A. R., and Arpinar-Avsar, P. (2010). Detection of surface electromyography recording time interval without muscle fatigue effect for biceps brachii muscle during maximum voluntary contraction. Journal of Electromyography and Kinesiology, 20(4), 773–776. https://doi.org/10.1016/j.jelekin.2010.02.006
27. 27. Staudenmann, D., Roeleveld, K., Stegeman, D. F., and van Dieën, J. H. (2010). Methodological aspects of SEMG recordings for force estimation – A tutorial and review. Journal of Electromyography and Kinesiology, 20(3), 375–387. https://doi.org/10.1016/j.jelekin.2009.08.005
28. 28. Tracy, B. L., Dinenno, D. V., Jorgensen, B., and Welsh, S. J. (2007). Aging, visuomotor correction, and force fluctuations in large muscles. Medicine and Science in Sports and Exercise, 39(3), 469–479. https://doi.org/10.1249/mss.0b013e31802d3ad3