pyCGM2.Model.modelDecorator.davisRegression

pyCGM2.Model.modelDecorator.davisRegression(mp_input: Dict[str, float], mp_computed: Dict[str, float], markerDiameter: float = 14.0, basePlate: float = 2.0) → Tuple[ndarray, ndarray]

Implements the Davis et al. regression for hip joint center estimation.

Parameters:

• mp_input (Dict[str, float]) – Dictionary of measured anthropometric parameters.

• mp_computed (Dict[str, float]) – Dictionary of computed anthropometric parameters.

• markerDiameter (float, optional) – Diameter of the marker. Defaults to 14.0.

• basePlate (float, optional) – Thickness of the base plate. Defaults to 2.0.

Returns:

Tuple[np.ndarray, np.ndarray] – Estimated positions of left and right hip joint centers.

Reference:

Davis, R., Ounpuu, S., Tyburski, D., & Gage, J. (1991). A gait analysis data collection and reduction technique. Human Movement Science, 10, 575–587.