Gait analysis Gait analysis is one of the real success stories of biomechanics. Today, gait laboratories are used routinely for investigation of a variety of conditions, for diagnostics and planning of surgery, and for rehabilitation. However, traditional gait analysis is almost exclusively about kinematics. It is possible to compute joint moments in the open-chain mechanisms formed by the lower extremities, but traditional gait analysis reveals little if anything about the internal forces in the body. Musculoskeletal analysis, as it can be performed by the AnyBody Modeling System, has the potential to change this.
This example presents an analysis of a gait cycle documented by Vaughan, Davis and O'Connor in their textbook "Dynamics of Human Gait - 2nd edition". The authors have kindly made the data available in the public domain on the homepage of the International Society of Biomechanics. We have used the dataset labeled "Man". Because the AnyBody Modeling System has such general capabilities of driving the kinematics, we are able to control the movement directly by means of the recorded marker trajectories. You can see the markers on the figure as small blue and grey spheres. Click here to see a video animation (8.2 MB).
Here is a disclaimer: What we present here is a demonstration model. We do not have the correct anthropometric data for the test subject, and consequently some amount of discrepancy must be expected. In particular, since we drive the model directly by markers, differences in the segment lengths between the test subject and the model may lead to errors in the kinematics.
The ground reaction forces are also a part of the data set, and they are applied under the feet at the moving pressure centers. The model is balanced by a reaction force on the pelvis. This means that the weight and inertia of the lacking upper body are automatically compensated for by the reaction forces.
Vaughan at al also present normalized EMG data for selected muscles, and these can be compared with the muscle activity patterns simulated by AnyBody. Some of the results can be seen below:
 Computed muscle activation (left) and normalized EMG for soleus.
|  Computed muscle activation (magenta curve) and normalized EMG (blue curve) for tibialis anterior.
|  Computed muscle activity (left) and normalized EMG for gastrocnemius.
|  Computed muscle activity (magenta curve) and normalized EMG (blue curve) for rectus femoris.
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When sufficient reliability of the gait model has been obtained, computations may replace more labor-intensive EMG measurements, and it is possible to use the technology to evaluate joint forces, which are very difficult to measure scientifically and impossible to measure in a clinical setting.
A more complete presentation of the model and results is available here (pdf).
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