Sangeux2015Procedure#
- class pyCGM2.Processing.Representative.representativeProcedures.Sangeux2015Procedure#
Implementation of the representative cycle detection method as described by Sangeux in 2015.
This procedure identifies the most representative gait cycle based on the method described in Sangeux’s 2015 publication. It computes the frame-by-frame median deviation for specified kinematic outputs and selects the cycle with the smallest deviation.
- Reference:
Sangeux, M. (2015). A simple method to choose the most representative stride and detect outliers.
- __init__()#
Methods
__init__()setData(EventContext, Label, indexes)Populates the data for the procedure.
Sets the default data for the procedure according to Sangeux's 2015 method.
- setData(EventContext: str, Label: str, indexes: List[int])#
Populates the data for the procedure.
- Parameters:
EventContext (str) – The event context (e.g., ‘Left’ or ‘Right’).
Label (str) – The kinematic model output label.
indexes (List[int]) – The axis indexes to consider.
Example
`python proc = Sangeux2015Procedure() proc.setData("Left", "LHipAngles", [0, 2]) # 0: flexion and 2: transverse rotation `
- setDefaultData()#
Sets the default data for the procedure according to Sangeux’s 2015 method.
The default kinematic model outputs and their respective axis indexes are set for both left and right contexts.