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THE EFFECT OF SHORT TERM ISOKINETIC TRAINING ON LIMB VELOCITY

THE EFFECT OF SHORT TERM ISOKINETIC TRAINING ON LIMB VELOCITY. Lee E. Brown, EdD, CSCS,*D California State University, Fullerton. Preface. Acute performance gains are attributed to learning. Motor learning is a neural event demonstrated physically.

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THE EFFECT OF SHORT TERM ISOKINETIC TRAINING ON LIMB VELOCITY

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  1. THE EFFECT OF SHORT TERM ISOKINETIC TRAINING ON LIMB VELOCITY Lee E. Brown, EdD, CSCS,*D California State University, Fullerton

  2. Preface • Acute performance gains are attributed to learning. • Motor learning is a neural event demonstrated physically. • Neural adaptation has been shown relative to force. • Activation or rate coding are responsible.

  3. Introduction • Force is only a byproduct of acceleration. • Acceleration is the key to velocity. • Maximum velocity results in maximum energy or force. • KEY is to maximize the rate of force development.

  4. Sport Physics • Mass = quantity of matter a body contains. • Weight = mass x accel. of gravity. • Velocity = rate of change in position. • Acceleration = rate of change in velocity. • Force = mass x acceleration. • Torque = force x lever arm. • Work = torque x distance. • Power = work/time.

  5. Implements

  6. Objects

  7. Launching

  8. Medium

  9. Inertia

  10. Energy • Kinetic Energy = ½ mass x v2 • 300 grain bullet (M = (300 gr)/[7000 gr/lb 32.2 ft/sec2] = 0.00133 lb sec2/ft ) • v of 10f/s (.5x0.00133x102) = 0.06ft/lbs • v of 3000f/s (.5x0.00133x30002)=5958ft/lbs

  11. Measurement • Resultant implement velocity is derived from human movement. • Human movement is a function of neural and morphologic changes. • Measurement of velocity is fundamental to performance. • Isokinetics allows a window into human movement speed variability.

  12. (DCC) (RVD) (LR)

  13. Variables • RVD is sensitive to speed and human variability. • LR is a function of ACCROM. • Force is sensitive to speed and human variability. • DCC is machine controlled.

  14. * * * * * • Brown, L. E., Whitehurst, M., Gilbert, P.R. & Buchalter, D.N. (1995). The effect of velocity and gender on load range during knee extension and flexion exercise on an isokinetic device. J. Orthop. Sports Phys. Ther., 21(2), 107-112.

  15. Strength gains of untrained after initial 8-weeks are due to neural adaptation then muscular hypertrophy. Moritani, T. & deVries, H.A. (1979). Neural factors versus hypertrophy in the time course of muscle strength gain. American Journal of Physical Medicine, 58(3), 115-30.

  16. Strength gains following short-term training utilizing isokinetic dynamometry are velocity specific (fast only) and related to neural adaptation. (~25% improvement) * Prevost, M.C., Nelson, A.G., & Maraj, B.K.V. (1999). The effect of two days of velocity-specific isokinetic training on torque production. Journal of Strength and Conditioning Research, 13(1), 35-39.

  17. Rationale • Force is only a function of velocity. • Max velocity is a function of acceleration. • Therefore, training specificity should be reflected in acceleration and any force increase should be reflected in a concomitant increase in acceleration.

  18. Hypotheses • The fast training group will decrease RVD at the fast speed only. • The slow group will exhibit no RVD change at any speed. • The slow group will increase force at the slow speed only. • The control group will exhibit no change at any speed.

  19. Testing and Training Design • 60 college age male and female subjects. • Three random groups (control, fast and slow). • Five maximal repetitions at 60 and 240 d/s. • Test on day one and day seven. • Two training sessions separated by 48 hours consisting of 3 sets of 8 repetitions at 60 or 240 d/s.

  20. Data Collection and Analysis • Diverted the signal to an A/D board sampling at 1000Hz. • Raw ASCII data exported to Excel as time, force, velocity and position columns. • Three univariate (RVD, LR, & Force ) four-way mixed factorial (2 speeds X 2 times X 2 genders X 3 groups ) ANOVA’s to analyze the data.

  21. CV r ICC SEM % Error RVD 13.15 .27 .40 .11 9.64 LR .49 .40 .58* .23 .30 DCCROM 16.37 .42 .59 .10 11.23 Force 22.18 .89* .94* 6.45 5.42 Reliability at 60 d/s

  22. CV r ICC SEM % Error RVD 9.00 .77* .87* .43 3.19 LR 3.43 .71* .83* .57 1.40 DCCROM 1.60 .37* .55* .23 1.05 Force 29.72 .95* .97* 3.99 5.13 Reliability at 240 d/s

  23. Results • Significantly high variable reliability at fast speeds but not slow.

  24. Reliability • First study to evaluate velocity reliability. • Reliability of force consistent with: • Farrell, 1986 • Brown, 1992 & 1993 • Mean values consistent with: • Farrell, 1986 • Taylor, 1991 • Brown, 1992 & 1993 • Wilson, 1997 • Greenblatt, 1997

  25. DCCROM at 60 d/s

  26. DCCROM at 240 d/s

  27. Force at 60 d/s

  28. Force at 240 d/s

  29. Results • No significant differences in force or DCCROM by time for any group.

  30. Force and Deceleration • Force inconsistent with Prevost, 1999. • Probably due to data reduction techniques. • DCCROM consistent with: • Farrell, 1986 • Taylor, 1991 • Brown, 1995

  31. RVD at 60 d/s

  32. LR at 60 d/s

  33. RVD at 240 d/s

  34. LR at 240 d/s

  35. Results • Significant decrease in RVD by time for the slow group at the slow speed and for the fast group at the fast speed. • Significant increase in LR by time for the slow group at the slow speed and for the fast group at the fast speed.

  36. Acceleration and Load Range • Reduction in RVD results in LR increase. • Reduction of RVD with maintenance of force results in an increase in rate of force development.

  37. Conclusions • Acute improvements may be explained as the result of neural adaptations. • Increased motor unit recruitment or firing rate. • Increased rate of force development may maximize human performance. • Future research should determine optimum frequency and volume for velocity specific training.

  38. Next Class • RVD, RFD Fmm lab • Chapter 6 • Abstract homework

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