آمار

تعداد نشریات26
تعداد شماره‌ها326
تعداد مقالات2,803
تعداد مشاهده مقاله4,228,601
تعداد دریافت فایل اصل مقاله2,881,791
Imani, Fariborz, Meamarbashi, Abbas, Barghamadi, Mohsen. (1403). Estimation of Muscle Fiber Types Using Force-Time Curves During Submaximal Leg Press Task.. سامانه مدیریت نشریات علمی, 8(2), 1-13. doi: 10.22098/jast.2024.3093
Fariborz Imani; Abbas Meamarbashi; Mohsen Barghamadi. "Estimation of Muscle Fiber Types Using Force-Time Curves During Submaximal Leg Press Task.". سامانه مدیریت نشریات علمی, 8, 2, 1403, 1-13. doi: 10.22098/jast.2024.3093
Imani, Fariborz, Meamarbashi, Abbas, Barghamadi, Mohsen. (1403). 'Estimation of Muscle Fiber Types Using Force-Time Curves During Submaximal Leg Press Task.', سامانه مدیریت نشریات علمی, 8(2), pp. 1-13. doi: 10.22098/jast.2024.3093
Imani, Fariborz, Meamarbashi, Abbas, Barghamadi, Mohsen. Estimation of Muscle Fiber Types Using Force-Time Curves During Submaximal Leg Press Task.. سامانه مدیریت نشریات علمی, 1403; 8(2): 1-13. doi: 10.22098/jast.2024.3093

Estimation of Muscle Fiber Types Using Force-Time Curves During Submaximal Leg Press Task.

Journal of Advanced Sport Technology
دوره 8، شماره 2 - شماره پیاپی 17، شهریور 2024، صفحه 1-13    اصل مقاله (612.88 K)
نوع مقاله: Original research papers
شناسه دیجیتال (DOI): 10.22098/jast.2024.3093
نویسندگان
Fariborz Imani1؛ Abbas Meamarbashi* 1؛ Mohsen Barghamadi2
1Department of Sports Biomechanics, Faculty of Educational Sciences and Psychology, University of Mohaghegh Ardabili, Ardabil, Iran
2Department of Sports Biomechanics,, Faculty of Educational Sciences and Psychology, University of Mohaghegh Ardabili, Ardabil, Iran
چکیده
In the field of sports sciences and especially sports physiology, one of the most important and interesting topics is the estimation of the composition of the muscle fiber types, especially among the athletes, so the main approach of this research was to find out the relationship between the number of repetitions and the parameters obtained from the force-time curves in a sub-maximal repetitive task with the leg press machine until exhaustion to estimate the dominant type of muscle fibers. The research was a semi-experimental study. The statistical sample in this research was included 19 university students. The test process was carried out in two days for each subject with an interval of 48 hours to prevent muscle soreness. The first day included recording data related to anthropometry and the One Repetition Maximum Test (1RM) on leg press machine. The second day consisted of a repetitive exercise until 70% 1RM until exhaustion. Using the Visual FoxPro software, the raw force-time data was processed in the repetitive test and applied information was extracted. The Shapiro-Wilk test was used to determine the normality of the data distribution. Pearson's or Spearman's correlation test was used to check the relationship between the parameters with a significance level of p<0.05. There was a correlation between the number of repetitions and the sub area under the force-time curve in the first group (low repetitions) (r=-0.828, p<0.001), and in the third group (high number of repetitions) (r=-0.636, p<0.001). This research showed that there is an inverse relationship between the number of repetitions and the level of the force-time sub-curve in a submaximal task. The results of this study contribute to the development of a field test that can be used to predict muscle fiber composition, as well as to demonstrate the dynamic and physiological mechanism responsible for variability in the number of repetitions in a submaximal task.
کلیدواژه‌ها
Slow-Twitch Muscle Fiber؛ Fast-Twitch Muscle Fiber؛ One Repetition Maximum (1RM)؛ Leg-Press Machine
مراجع
  1. Casolo a, maeo s, balshaw tg, lanza mb, martin nrw, nuccio s, et al. Non-invasive muscle biopsy: estimation of muscle fibre size from a neuromuscular interface. Biorxiv. 2022:2022.10.21.513157.
  2. Suter e, herzog w, sokolosky j, wiley jp, macintosh br. Muscle fiber type distribution as estimated by cybex testing and by muscle biopsy. Med sci sports exerc. 1993;25(3):363-70.
  3. Scott w, stevens j, binder–macleod sa. Human skeletal muscle fiber type classifications. Physical therapy. 2001;81(11):1810-6.
  4. Christiansen d, macinnis mj, zacharewicz e, xu h, frankish bp, murphy rm. A fast, reliable and sample-sparing method to identify fibre types of single muscle fibres. Scientific reports. 2019;9(1):1-10.
  5. Douris pc, white bp, cullen rr, keltz we, meli j, mondiello dm, et al. The relationship between maximal repetition performance and muscle fiber type as estimated by noninvasive technique in the quadriceps of untrained women. The journal of strength & conditioning research. 2006;20(3):699-703.
  6. Brown le, weir jp, brown l, weir dj, editors. Asep procedures recommendation i: accurate assessment of muscular strength and power2001.
  7. Karp jr. Muscle fiber types and training. Strength & conditioning journal. 2001;23(5):21.
  8. Fry ac, housh tj, cramer jb, weir jp, beck tw, schilling bk, et al. Noninvasive assessment of skeletal muscle myosin heavy chain expression in trained and untrained men. The journal of strength & conditioning research. 2017;31(9):2355-62.
  9. Terzis g, spengos k, manta p, sarris n, georgiadis g. Fiber type composition and capillary density in relation to submaximal number of repetitions in resistance exercise. The journal of strength & conditioning research. 2008;22(3):845-50.
  10. Hall ecr, lysenko ea, semenova ea, borisov ov, andryushchenko on, andryushchenko lb, et al. Prediction of muscle fiber composition using multiple repetition testing. Biol sport. 2021;38(2):277-83.
  11. Treers l. Investigating a non-invasive method for determining muscle fiber composition: massachusetts institute of technology; 2018.
  12. Tesch pa, wright je, vogel ja, daniels wl, sharp ds, sjödin b. The influence of muscle metabolic characteristics on physical performance. European journal of applied physiology and occupational physiology. 1985;54(3):237-43.
  13. Coyle ef, costill dl, lesmes gr. Leg extension power and muscle fiber composition. Med sci sports. 1979;11(1):12-5.
  14. Staron rs, hagerman fc, hikida rs, murray tf, hostler dp, crill mt, et al. Fiber type composition of the vastus lateralis muscle of young men and women. Journal of histochemistry & cytochemistry. 2000;48(5):623-9.
  15. Hunter gr, newcomer br, larson‐meyer de, bamman mm, weinsier rl. Muscle metabolic economy is inversely related to exercise intensity and type ii myofiber distribution. Muscle & nerve: official journal of the american association of electrodiagnostic medicine. 2001;24(5):654-61.
  16. Saltin b. Skeletal muscle adaptability: significance for metabolism and performance. Skeletal muscle. 1983.
  17. Bottinelli r, canepari m, pellegrino ma, reggiani c. Force-velocity properties of human skeletal muscle fibres: myosin heavy chain isoform and temperature dependence. J physiol. 1996;495 ( pt 2)(pt 2):573-86.
  18. Harridge sd, bottinelli r, canepari m, pellegrino ma, reggiani c, esbjörnsson m, et al. Whole-muscle and single-fibre contractile properties and myosin heavy chain isoforms in humans. Pflugers arch. 1996;432(5):913-20.
  19. Larsson l, moss rl. Maximum velocity of shortening in relation to myosin isoform composition in single fibres from human skeletal muscles. The journal of physiology. 1993;472(1):595-614.
  20. Gollnick pd, matoba h. The muscle fiber composition of skeletal muscle as a predictor of athletic success. An overview. Am j sports med. 1984;12(3):212-7.
  21. Kenney wl, wilmore jh, costill dl. Physiology of sport and exercise: human kinetics; 2021.
  22. Herda tj, housh tj, fry ac, weir jp, schilling bk, ryan ed, et al. A noninvasive, log-transform method for fiber type discrimination using mechanomyography. Journal of electromyography and kinesiology. 2010;20(5):787-94.
  23. Dahmane r, djordjevič s, šimunič b, valenčič v. Spatial fiber type distribution in normal human muscle: histochemical and tensiomyographical evaluation. Journal of biomechanics. 2005;38(12):2451-9.
  24. Dahmane r, valenčič v, knez n, eržen i. Evaluation of the ability to make non-invasive estimation of muscle contractile properties on the basis of the muscle belly response. Medical and biological engineering and computing. 2001;39(1):51-5.
  25. Houmard ja, smith r, jendrasiak gl. Relationship between mri relaxation time and muscle fiber composition. Journal of applied physiology. 1995;78(3):807-9.
  26. Winkler t, mersmann f, von roth p, dietrich r, bierbaum s, arampatzis a. Development of a non-invasive methodology for the assessment of muscle fibre composition. Frontiers in physiology. 2019;10.
  27. Aagaard p, andersen jl. Correlation between contractile strength and myosin heavy chain isoform composition in human skeletal muscle. Med sci sports exerc. 1998;30(8):1217-22.
  28. Widrick jj, trappe sw, costill dl, fitts rh. Force-velocity and force-power properties of single muscle fibers from elite master runners and sedentary men. Am j physiol. 1996;271(2 pt 1):c676-83.
  29. Thorstensson a, grimby g, karlsson j. Force-velocity relations and fiber composition in human knee extensor muscles. Journal of applied physiology. 1976;40(1):12-6.
  30. Kojima t. Force-velocity relationship of human elbow flexors in voluntary isotonic contraction under heavy loads. International journal of sports medicine. 1991;12(02):208-13.
  31. Martín-fuentes i, oliva-lozano jm, muyor jm. Evaluation of the lower limb muscles’ electromyographic activity during the leg press exercise and its variants: a systematic review. International journal of environmental research and public health. 2020;17(13):4626.
  32. Hoeger ww, barette sl, hale df, hopkins dr. Relationship between repetitions and selected percentages of one repetition maximum. J appl sport sci res. 1987;1(1):11-3.
  33. Housh dj, housh tj, weir jp, weir ll, johnson go, stout jr. Anthropometric estimation of thigh muscle cross-sectional area. Medicine & science in sports & exercise. 1995;27(5):784-91.
 

آمار
تعداد مشاهده مقاله: 32
تعداد دریافت فایل اصل مقاله: 30


سامانه مدیریت نشریات علمی. قدرت گرفته از سیناوب