This operation calculates joint and marker statistics from either a dynamic trial or a ROM trial. Both the Functional Skeleton Calibration and the Functional Skeleton Calibration - Markers Only operation runs this operation after calculating the skeleton parameters.
This operation calculates joint and marker statistics for the subject. Joint and particularly marker statistics are used in the labeling algorithms. Joint statistics tell the labelers how much a particular joint is expected to move. Marker statistics give information about how much soft tissue motion is expected for the markers. Good marker statistics can improve labeling significantly.
This operation assumes that the skeleton has already been calibrated. It does not change any joint or marker positions. If it is run on an uncalibrated skeleton, the covariances and ranges calculated will be large.
For joints, this operation calculates values for: mean, covariance, range center, and range matrix. For markers, it calculates mean and covariance. The statistics are calculated from all of the frames in the trial.
The values stored in the mean and covariance are not calculated directly from the data. During a ROM trial the subject has only a few joints moving at a time, the rest are not moving much. If you plot the joint position samples over a trial you tend to see a large peak of samples and a few spread across the joint range.
In some cases, such as the knee, a mean and covariance calculated from the samples does a very bad job of representing the distribution. In the case of the knee, the majority of the samples are collected with the knee straight. This leads to a mean that is nearly straight and a covariance that suggests the knee can bend forward and backward equally well.
Instead of calculating the mean and covariance directly, a range and range center is calculated. This applies to both joints and markers. It is then assumed that the samples that really represent the distribution are uniformly distributed across the range. If you look in the VSK, you can see that joint means and joint range centers are the same.
Calculate Skeleton Joint & Marker Statistics can be used when a skeleton has been calibrated using a single frame but doesn't label well. This operation can be used on a dynamic trial to calculate better joint and marker statistics which will improve the labeling performance.
For information on how to use this operation in common Nexus workflows, see Subject calibration workflows.