Biomedical Engineering Reference
In-Depth Information
software and research done in musculoskeletal modeling and simulation and (4) a
specific study using multi-body simulation with a clinical application purpose.
Musculoskeletal modeling and simulation is not yet a simple task despite research
advances and efforts to decrease its complexity over the years. Currently, modeling
processes require time, resources and expertise and must be carefully validated.
Thus, this topic is far from being completely explored. A great deal of research
is still needed to accurately represent the human system. At this time and in the
next years, research is and will be channeled to the development of subject-specific
modelswith higher accuracy. Advances in imaging techniques, re-assessment of basic
modeling assumptions and better modeling approaches will provide more accurate
and improved simulations as well as greater insight into the clinical area.
Acknowledgments
This study was funded by the German Federal Ministry of Education and
Research (BMBF AZ: 01EZ0775).
The authors like to thank TU Berlin and Otto Bock Healthcare GmbH, Duderstadt, Germany for
cooperation in TExoPro and EU Marie Curie Actions-Marie Curie Research Training Networks/
Multi-scale Biological Modalities for Physiological Human articulation 289897 (FP7-PEOPLE-
2011-ITN) for their funding
References
1. Shihab, A., & Moataz, E. (2011). Development and validation of a three-dimensional biome-
chanical model of the lower extremity. In V. Klika (Ed.),
Theoretical biomechanics
.ISBN:
978-953-307-851-9, InTech, DOI:
10.5772/24156
.
2. Erdemir, A., Scott M., Walter H., van den Bogert, A. J., et al. (2007). Model-based estimation
of muscle forces exerted during movements.
Clinical Biomechanics (Bristol, Avon)
,
22
(2),
131-154.
3. Schwarze, M., Hurschler, C., Seehaus, F., Oehler, S., & Welke, B. (2013). Loads on the
prosthesis-socket interface of above-knee amputees during normal gait: Validation of a multi-
body simulation.
Journal of Biomechanics
,
46
(6), 1201-1206.
4. Welke, B., Schwarze, M., Hurschler, C., Calliess, T., & Seehaus, F. (2013). Multi-body simu-
lation of various falling scenarios for determining resulting loads at the prosthesis interface of
transfemoral amputees with osseointegrated fixation.
Journal of Orthopaedic Research
,
31
(7),
1123-1129.
5. Simon, S. R. (2004). Quantification of human motion: Gait analysis-benefits and limitations
to its application to clinical problems.
Journal of Biomechanics
,
37
(12), 1869-1880.
6. Hausdorff, J. M., Merit, E. C., Renée F., Jeanne Y. W., & Ary L. G. (1998). Gait variability and
basal ganglia disorders: Stride-to-stride variations of gait cycle timing in parkinson's disease
and Huntington's disease.
Movement Disorders
,
13
(3), 428-437.
7. Hausdorff, J. M., Apinya, L., Merit, E. C., Amie, L. P., David, K., Ary, L. G., et al. (2000).
Dynamic markers of altered gait rhythm in amyotrophic lateral sclerosis.
Journal of Applied
Physiology
,
88
(6), 2045-2053.
8. Hausdorff, J. M., Schaafsma, J. D., Balash, Y., Bartels, A. L., Gurevich, T., &Giladi, N. (2003).
Impaired regulation of stride variability in Parkinson's disease subjects with freezing of gait.
Experimental Brain Research
,
149
(2), 187-194.
9. Bowen, J. D., & Gerry S. M. B. A. (2010). Gait Assessment. In
The hip and pelvis in sports
medicine and primary care
(pp. 71-86). New York: Springer.
