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Training can increase both muscle strength and fiber contraction speed

This is an excerpt from Biophysical Foundations of Human Movement, Third Edition by Bruce Abernethy, Vaughan Kippers, Stephanie Hanrahan, Marcus Pandy, Ali McManus, and Laurel Mackinnon.

Examine changes and adaptations in human movement with
Biophysical Foundations of Human Movement, Third Edition.

Biomechanical Adaptations to Injury

Adaptations are common following injury and surgical treatment. One interesting example found in the orthopaedics literature is a phenomenon known as quadriceps avoidance gait. This particular adaptation occurs in ACL-deficient (ACLD) patients; that is, patients who have suffered a complete rupture of the ACL. ACLD patients usually have difficulty with movements involving either lateral thrusts (e.g., cutting from side to side) or twisting (i.e., rotation of the femur relative to the tibia in the transverse plane).

Gait analysis has been done on ACLD patients during various activities of daily living, including level walking, jogging, walking up and down stairs, and even running, cutting, and pivoting. Kinematic and force-plate data were used to estimate the net muscle moments exerted at the knee in all three planes of movement: flexion–extension, abduction–
adduction, and internal–external rotation. Interestingly, the greatest functional changes between ACLD patients and healthy subjects occurred while walking at preferred speeds on level ground. During the midstance portion of the gait cycle, the ACLD patients exhibited a net extensor moment that was significantly lower than normal (figure 10.9, solid line). One interpretation of these findings is that the ACLD patients walk by reducing the demand on their quadriceps during stance (i.e., the quadriceps muscles are activated less in the ACL-deficient patients, giving rise to a quadriceps-avoidance gait pattern).

It is important to realise that a lower net extensor moment at the knee does not necessarily mean that the moment exerted by quadriceps is lower. Because the net moment at the knee is a combination of quadriceps and hamstrings muscle action, a lower extensor moment could result from an increase in the flexor moment applied by hamstrings. However, muscle electromyography results tend to support the interpretation that quadriceps moment is lower because the activation level of the quadriceps is lower in the ACLD patients.

Gait analysis results have also shown that the ACLD patients reduce their net extensor moment by 25% during jogging compared with a 100% reduction in walking. However, the net extensor moment in stair climbing was the same in ACLD patients and normal subjects. When taken together, these results suggest that the observed quadriceps avoidance in ACLD patients is not a result of quadriceps weakness but rather is due to a change in neuromuscular control.

Dependence of Motor Performance on Changes in Muscle Properties

Strength and quickness are critical determinants of performance in explosive movements such as jumping, throwing, and sprinting. Together, these two factors determine the amount of power developed instantaneously during a task (i.e., muscle power is given by the product of muscle force and muscle contraction speed; see “In Focus: At What Speed Must a Muscle Shorten to Develop Maximum Power?”). As discussed earlier in this chapter, resistance strength training can alter both muscle force and fibre contraction speed. This section describes the effects that changes in the contractile properties of muscle have on motor performance, specifically, how biomechanical performance depends on muscle strength and muscle fibre contraction speed.

Vertical jumping is one of the most heavily studied motor tasks. Many scientists have studied jumping with the aim of learning more about the biomechanics and control of this task and, specifically, how performance may be influenced by training. In a recent jump-training program that incorporated stretching, plyometric exercises, and weight lifting, female high school volleyball players demonstrated a mean increase of 4 cm (1.5 in.) in jump height after training. This represented an almost 10% increase in jump height as a result of the 6 wk period of training. Even larger increases in vertical jumping performance have been documented in the literature. One extreme example is the 1984 United States Olympic gold medal volleyball team, which showed a 10 cm (4 in.) increase in jump height after 2 yr of jump training.

Using Computer Modelling to Study Vertical Jumping Performance

It is gratifying to learn that jumping performance can be increased significantly by strength and neuromuscular training. However, it is difficult, if not impossible, to explain why these increases occur. Noninvasive measurements of biomechanical performance cannot pinpoint the factor or factors responsible for the increase in jump height. The reason is that several properties of the neuromuscular and musculoskeletal systems change simultaneously during the training regimen. Alternatively, computer models may be used to study the relationships between training effects and performance; that is, a model of the neuromusculoskeletal system may be used to predict how changes to specific parameters affect the performance of a motor

Models of the body similar to the one shown in figure 8.7 have been used to study how changes in muscle strength, muscle contraction speed, and motor unit recruitment affect jump height. The values of each of these parameters in the model were increased by amounts consistent with results obtained from strength-training programs. For example, the peak isometric strength and maximum shortening velocity of each muscle in the model were increased by 20% and the activation level of each muscle was increased by 10%. The three training effects were first applied to all muscles simultaneously and then to the ankle plantarflexors, knee extensors, and hip extensors separately. In this way, the modelling results were used to determine whether it is better to train all the leg muscles simultaneously or to isolate specific muscle groups such as the quadriceps (knee extensors) and gluteus maximus (hip

Insights Into the Effects of Training Provided by Computer Models

Increasing the peak isometric force of all the leg muscles in the model by 20% produced the largest increase in jump height. In this case, jump height increased by 7 cm, or 5% of that obtained before the simulated training effect. Increasing the maximum shortening velocity of each muscle by 20% or the activation level of each muscle by 10% increased jump height by only 4 cm, or 3% of that obtained for the nominal (untrained) model. When all three training effects were introduced simultaneously, jumping performance increased by nearly 17 cm, or 12% of that calculated for the untrained model. Thus, training programs that increase strength, fibre contraction speed, and motor recruitment (i.e., activation level) of all the leg muscles simultaneously are most beneficial to overall jumping performance.

The modelling results also suggest that training the knee extensors is better than training either the ankle plantarflexors or the hip extensors. When peak isometric force and maximum shortening velocity of the quadriceps were increased by 20% and quadriceps activation was simultaneously increased by 10%, jump height increased by almost 10 cm, or 7% of the value calculated for the untrained model. The same changes made to either the ankle plantarflexors or the hip extensors produced increases in jump height of only 3 cm, or 2% of the value obtained for the untrained model.

The latter result is a little puzzling because the model calculations had previously shown that the quadriceps and gluteus maximus are the major energy producers—the prime movers—of the body in vertical jumping (see “In Focus: Which Muscles Are Most Important to Vertical Jumping Performance?” in chapter 8). It should be noted here that each time a change was introduced to the model, a new optimal pattern of muscle activations was found by re-solving the optimisation problem for a maximum-height jump. Thus, one interpretation of the result is that what matters most in terms of performance is the quadriceps:gluteus maximus muscle strength ratio and not the absolute strength of these muscles. In other words, jumping performance is most sensitive to a change in the knee-extensor:hip-extensor muscle strength ratio. Increasing quadriceps strength by 20% increases the knee-extensor:hip-extensor muscle strength ratio in the model, whereas increasing gluteus maximus muscle strength decreases this ratio. The same line of reasoning may be used to explain why increasing ankle plantarflexor muscle strength by 20% leads to an increase in jump height of just 3 cm in the model.

Training for strength is also better than training for quickness or speed. Figure 10.10 shows the effects of increasing muscle strength and muscle contraction speed on vertical jump height as predicted by the four-segment, eight-muscle, sagittal-plane model of the body described in chapter 8 (see figure 8.7). An increase in muscle strength was simulated in the model by simultaneously increasing body weight because muscle strength increases in proportion to muscle mass. Thus, changes in body strength:weight ratio are represented in figure 10.10 rather than changes in muscle strength alone. Also, jumping performance is normalised in these results by dividing by the value of jump height calculated for the untrained model. Similarly, body strength:weight ratio and muscle contraction speed are each normalised by dividing by the value of body strength:weight ratio and muscle contraction speed in the untrained model, respectively.

The simulation results show that the slope of the line predicted for changes in body strength:weight ratio is twice as large as that obtained when changes in muscle fibre contraction speed are made (compare solid and dashed lines in figure 10.10). Thus, muscle strength has a greater effect on vertical jump height than muscle fibre contraction speed, even when the accompanying increase in body mass is taken into account.

Another important lesson learned from the modelling studies is that musculoskeletal changes must be accompanied by appropriate changes in neuromuscular control; otherwise, the expected improvement in motor performance will not be seen. In vertical jumping, if the pattern of muscle activations remains unchanged subsequent to strength training, jump height actually decreases relative to the untrained state. Figure 10.11 shows a simulated jump in which the strength of the knee-extensor muscles has been increased by 20% but the control exerted over the joints is the same as that calculated for the untrained model before the training effect was introduced. When the pattern of muscle activations was not optimised to match the changes introduced to the neuromusculoskeletal model, the body left the ground prematurely (i.e., the centre of mass was at a lower height at liftoff than is optimal for a maximal jump).

One consequence of not optimising the pattern of muscle activations (i.e., the controls) is that a larger fraction of the total work produced by the muscles goes into rotating the body segments rather than accelerating the centre of mass upward. In a maximum-height jump, approximately 90% of the total work done by the leg muscles is used to propel the centre of mass upward. This number is closer to 80% when muscle coordination (i.e., the sequence and timing of muscle activations) is not optimal. So, even though jumping performance depends heavily on muscle strength, and to a lesser extent on muscle fibre contraction speed, optimal performance is also intimately related to neuromuscular control. For this reason, and as discussed at the beginning of this chapter, jump-training programs now focus on maneuvers that blend muscle strength with neural control.


Training can change both muscle strength and fibre contraction speed. Strength may be increased by increasing motor unit recruitment (net neural drive to the muscle) or by increasing muscle fibre size. Contraction speed may be altered by changing the shape of a muscle’s force–velocity curve or by changing the value of its intrinsic maximum shortening velocity. Early in a training program (2-8 wk), increases in muscle strength are brought by neural adaptations rather than by increases in muscle size. Training can also change the way muscle action is coordinated during activity (i.e., neuromuscular control). Neuromuscular training programs are usually designed to improve stability (balance and coordination) and proprioception (joint position sense) in addition to muscle strength. Training is vital for improving biomechanical performance and for preventing injuries during sport.

Read more from Biophysical Foundations of Human Movement, Third Edition by Bruce Abernethy, Vaughan Kippers, Stephanie Hanrahan, Marcus Pandy, Ali McManus, and Laurel Mackinnon.

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