pykinematics.omc.calibration.compute_hip_center

pykinematics.omc.calibration.compute_hip_center(pelvis_data, thigh_data, R, origin, marker_names='default', tol=0.0001)

Compute the hip joint center location using a bias compensated least squares estimation.

Parameters:

pelvis_data : dict

Dictionary of all the marker data for the pelvis. Each key is a marker name.

thigh_data : dict

Dictionary of all the marker data for the thigh. Each key is a marker name

R : numpy.ndarray

Rotation matrix or array of rotation matrices representing the rotation from world to local reference frame.

origin : numpy.ndarray

Vector of the origin position to use when rotating and transforming the marker positions into a local reference frame.

marker_names : {‘default’, MarkerNames}, optional

Either ‘default’ to use the default marker names, or a MarkerNames object with the names used in pelvis_data and thigh_data specified.

tol : float, optional

Tolerance for the bias compensation of the joint center. Default is 1e-4.

Returns:

c : numpy.ndarray

Vector from the provided origin to the joint center, expressed in the local reference frame.

References

Halvorsen, Kjartan. “Bias compensated least squares estimate of the center of rotation.” J. of Biomech. Vol. 36. 2003. Gamage et al. “New least squares solution for estimating the average center of rotation and the axis of rotation.” J. of Biomech. Vol. 35. 2002