Biomedical Engineering Reference
In-Depth Information
the effects of environmental physics on the motion. PD is a novel approach for
simulating, specifically
predicting
, human motion. It avoids direct integration of
differential-algebraic equations in order to create the resulting simulations for
redundant digital human models. Cause and effect is at the center of this formu-
lation
using a digital human environment, a user is able to model the human
by selecting their anthropometry, body type, weight, strength, and fatigue limits.
The user is also able to load the digital human model with various loads, for
example perhaps inflict a biomechanicalinjurythatwouldrestrictajointrange
of motion or lower the strength value of a particular group of muscles. Upon
selecting a motion or a task, PD provides for a computational platform that lets
us know the human reaction to these conditions
...
indeed, it answers the ques-
tion: “How would the human have reacted if they were under these conditions?”
It is a human simulator.
The topic aims to illustrate the entire methodology beginning with a system-
atic method for modeling the kinematics, then creating an optimization formula-
tion, writing the dynamics, and formulating the PD problem. Human
performance measures are also introduced as cost functions (objective functions)
that drive the motion, a theory that has been proven effective for producing nat-
ural motions. Such motion prediction capabilities have a wide variety of practi-
cal applications, such as in automotive industry, military, clinical and
biomechanical analyses, and design of equipment. Several such applications are
illustrated through detailed examples.
...
References
Abdel-Malek, K., Yu, W., Jaber, M., 2001a. Realistic Posture Prediction. 2001 SAE
Digital Human Modeling and Simulation.
Abdel-Malek, K., Wei, Y., Mi, Z., Tanbour, E., Jaber, M., 2001b. Posture prediction versus
inverse kinematics. In: Proceedings of the 2001 ASME Design Engineering Technical
Conferences and Computers and Information in Engineering Conference, Pittsburgh,
PA, pp. 37
45.
Abdel-Malek, K., Yu, W., Jaber, M., Duncan, J., 2001d. Realistic posture prediction for
maximum dexterity. SAE Technical Paper 2001-01-2110. doi: 10.427/2001-01-2110.
Abdel-Malek, K., Yang, J., Yu, W., Duncan, J., 2004b. Human performance measures:
mathematics. Proceedings of the ASME Design Engineering Technical Conferences
(DAC 2004), Salt Lake City, UT.
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