Overview¶
Getting Started¶
- Ensure the code is running on your system
Clone or download the repository
Run the pycgm_embed.py file
Check the SampleData folder for a newly created .csv results file
- Change the file to calculate
Open the pyCGM_Helpers.py file
Modify/Add a file directory and name
Change the loading value in main() function of the pycgm_embed.py file
Setting up the calculation¶
- Besides the pyCGM code, the three types of data needed are:
A dictionary of subject measurements that correspond to the PlugInGait naming conventions from a vsk file
An ordered list of data for a static trial where each index is a frame, and each frame contains a dictionary of marker names with a xyz value.
An ordered list of data for a dynamic trial where each index is a frame, and each frame contains a dictionary of marker names with a xyz value.
While this data can be passed directly to the calcAngles() function in pycgmCalc.py, there are some easy helper functions that will load the data from a .vsk file, formated .csv file, and .c3d file through the pycgmIO.py module.
The global axis is defined differently in each file. Therefore you can change the rotation of the global axis before calling the calcAngles() function like so:
calSM['GCS'] = pycgmStatic.rotmat(x=0,y=0,z=180)
Static Calibration¶
- There are some automatic switches that will happen based on the data used.
If the ASIS to Trocanter distances are not 0, the values will be used. Otherwise they will be calculated.
If the Inter ASIS distance is not 0 it will be used, otherwise it is averaged from the static trial.
If there is no Knee/Ankle width value or it is set to 0, it will be calculated by the MKN and MMA markers.