AnyBody Modeling System in Medical/Rehab
Detailed knowledge of the forces in the human body are of crucial importance to the successful design and implantation of prosthetic devices. For planning of rehabilitative exercises and development and prescription of orthotics devices, the influence of external forces in the internal equilibrium is of utmost importance. The AnyBody Modeling System is the ideal tool for this purpose because it is capable of capturing the true complexity of the musculoskeletal system.
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.
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:
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 very large proportion of wheelchair users experience load-induced shoulder pain. This happens after several years' use, and it can be a very serious condition for an individual relying entirely on the arms for ambulation. The wheelchair parameters such as wheel diameter, pushrim position, axle position, and camber influence the shoulder forces during use. But precisely how?
This is a field where the consequences of a design change do not appear until several years of use. This alone makes experimentation impossible. But it is also ethically unacceptable to fit wheelchairs to humans in any other way than following best practice. In other words, computer simulation is the only way to gain knowledge about the influence of the wheelchair design on body loads.
The depicted model investigates the gleno-humeral joint forces as a function of the axle position through a forward push on the pushrim. It is now possible to experiment with different design parameters to reduce the gleno-humeral forces as much as possible.