Polynomial regression was used to describe the relationship between lengths of the five muscles of interest and lower extremity joint angle(s). A difference between the genders was observed, so the male and female data were separated and five regression equations (one per muscle) were fitted to each data set. In an attempt to build general regression equations normalization and transformation of the data was performed, but these manipulations of the data did not lead to predictive equations. Addition of leg segment length, for the monoarticular muscles, and height, for the biarticular muscles, as independent variables did significantly increase model fit. The general regression model was quantitatively compared to the leg segment lengths and the actual observed values. It was also qualitatively compared to two other models. Results showed that while the general regression model is good at predicting muscle function, it is not a very accurate predictor of muscle length.
| Identifer | oai:union.ndltd.org:uottawa.ca/oai:ruor.uottawa.ca:10393/6241 |
| Date | January 2002 |
| Creators | St. Pierre, Taunya Allyson. |
| Contributors | Weber, J-M, |
| Publisher | University of Ottawa (Canada) |
| Source Sets | Université d’Ottawa |
| Detected Language | English |
| Type | Thesis |
| Format | 141 p. |
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