Page 173 - Biomedical Engineering and Design Handbook Volume 1, Fundamentals

150 BIOMECHANICS OF THE HUMAN BODY

FIGURE 6.21 The subject in this example walks with a stiff knee gait. His peak knee flexion angle during weight
acceptance is less than 10°. This is re-created during standing (left panel) and provides the subject with a kines-
thetic sense of the flexion angle. The subject is encouraged to flex his knee to 25° (right panel). The real-time knee
flexion angle (26.7°) is displayed and the subject can modify his flexion angle accordingly. The screen is updated
every 30 ms.

(i.e., first peak in Fig. 6.17). Individuals who do not flex sufficiently during weight acceptance may
be at greater risk for developing tibial stress fractures. The real-time capabilities of the Qualisys
system can be used to help guide a patient on how they should adjust their pattern to match a target.
An example of this is shown in Fig. 6.21. The subject walks with a stiff knee gait and flexes less than
10° during weight acceptance. This is re-created while standing to give the subject visual feedback
regarding the flexion angle. In the right panel the subject is encouraged to practice flexing his knee
to 25°. Although this early phase of retraining is done while standing, it provides the subject with a
kinesthetic awareness of his knee positioning. Once the subject can achieve the desired angle
without visual guidance (i.e., numbers being displayed) he then practices walking so that the knee
flexion during weight acceptance is within a prescribed range. Performance can be monitored in real
time and used to direct changes that need to be made to achieve the desired target angle.

6.5 CONCLUDING REMARKS

In this chapter we have examined forward and inverse dynamics approaches to the study of human
motion. We have outlined the steps involved when using the inverse approach to studying movement
with a particular focus on human gait. This is perhaps the most commonly used method for examin-
ing joint kinetics. The forward or direct dynamics approach requires that one start with knowledge
of the neural command signal, the muscle forces, or, perhaps, the joint torques. These are then used
to compute kinematics.
Before concluding, a brief word might be said for hybrid approaches that combine both forward
and inverse dynamics approaches to meet in the middle. These methods record both the neural com-
mand signal (i.e., the EMG) and the joint position information using standard motion analysis meth-
ods as described in Sec. 6.4. The EMG is processed so as to determine muscle forces, which are then
summed together to yield joint moments. These same joint moments can also be computed from the
inverse dynamics. This provides a means by which to calibrate the EMG to muscle force relation-
ships. This method has been shown to work well with gait studies (Bessier, 2000) and has great
potential for studying altered muscle function associated with pathological gait, which cannot be
readily examined using optimization techniques.
The biomechanics of human movement is growing field, spanning many disciplines. As new tech-
niques are developed and shared across these disciplines, the field will continue to grow, allowing us
to peer deeper into the mechanics of movement.