classify_bouts¶

Gait bout classification using acceleration data in the vertical direction from the lumbar location.

Parameters:

result_file: str: Optional argument that accepts .h5 filepath string to save resulting predictions to. None by default. (ie. myfolder/myfile.h5)

Returns:

pandas.core.frame.DataFrame: Pandas dataframe containing results of bout classification procedure (classify_bouts)

extract_features¶

Inverted pendulum and continuous wavelet based method of gait feature detection

Parameters:

subject_height: int or float

Height of the subject. Accepts centimeters by default.

subject_height_units: str

Units of provided subject height. Centimeters by default.

sensor_height_ratio: float

Height of the sensor relative to subject height. Calculated: sensor height / subject height

result_file: str

Optional argument that accepts .csv filepath string to save resulting gait feature dataframe to. None by default. (ie. myfolder/myfile.csv)

classified_gait: str or pandas.core.frame.DataFrame

Pandas dataframe containing results of gait bout classification procedure (classify_bouts)

OR

File path of .h5 file containing results of gait bout classification procedure (classify_bouts)

ic_prom: int

Prominance of initial contact peak detection

fc_prom: int

Prominance of final contact peak detection

Returns:

pandas.core.frame.DataFrame: Pandas dataframe containing results of feature extraction procedure (extract_features)

Visualization of bouts, initial contacts, and final contacts of lumbar based gait feature extraction

Parameters:

gait_features: pandas.DataFrame or str

Pandas dataframe containing results of extract_features function

OR

File path of .csv file containing results of extract_features function

result_file: str

Optional argument that accepts .html filepath string to save resulting gait event plot to. None by default. (ie. myfolder/myfile.html)

show_plot: bool

Optional boolean argument that specifies whether your plot is displayed. True by default.