Biomechanical models have been used in designing human work
environments to evaluate potential risks to workers before a work environment is
constructed. In order for work environments to be modeled correctly, most
biomechanical models require as input, an accurate body posture of the worker.
This information can be obtained by, either measuring the posture of workers for
the task of interest, or estimating the posture.
This research explores methods to estimate working postures by developing
a model that can predict a worker's posture. The model in this thesis represents the
body of the worker with ten links: neck, left and right forearms, left and right upper
arms, body, left and right thighs, and left and right calves. The work task inputs
consist of the magnitude and direction of the force applied to the hands, and the
distances between the hands and the floor. By using these inputs, the model can
predict a posture by optimizing an objective function of two criteria: Total Squared
Moment and Balance. Model constraints also ensure that a predicted posture is
feasible for human.
The output of the model is the predicted posture in terms of ten body joint
angles: neck, left and right elbows, left and right shoulders, hip, left and right
knees, left and right ankles. These joint angles are defined as angles relative to
horizontal.
The prediction posture can be used as a base reference when inputting
into other biomechanical models. By predicting posture from the model, one can
obtain postures of the workers without direct measurement of postures from the
workers, which can be expensive and time consuming. / Graduation date: 2002
| Identifer | oai:union.ndltd.org:ORGSU/oai:ir.library.oregonstate.edu:1957/30990 |
| Date | 01 May 2002 |
| Creators | Dendamrongvit, Thidarat |
| Contributors | Woldstad, Jeffrey C. |
| Source Sets | Oregon State University |
| Language | en_US |
| Detected Language | English |
| Type | Thesis/Dissertation |
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