Cadence Estimation (CAD)#

Methods to calculate cadence either from initial contacts or using dedicated cadence algorithms.

Cadence from ICs#

CadFromIc(*[, step_time_smoothing, ...])

Calculate cadence per second directly from initial contacts.

CadFromIcDetector([ic_detector, ...])

Calculate cadence per second by detecting initial contacts using a provided IC detector.

Base Classes#

Base classes for all Cadence calculation methods.

BaseCadCalculator()

Base class for cadence calculation algorithms.

Docu-helper#

base_cad_docfiller(func)

Decorator to fill common parts of the docstring for subclasses of BaseCadenceCalculator.

Pipelines#

pipeline.CadEmulationPipeline(algo)

Run a cadence estimation algorithm in isolation per gait sequence/WB on a Gait Dataset.

Evaluation#

As the structure of the Cadence output is very similar to the output of the full pipeline, we recommend using the pipeline level evaluation functions to create custom evaluations.

Evaluation Scores#

These scores are expected to be used in combination with Evaluation and EvaluationCV or directly with cross_validation and validation.

cad_score

Scorer class instance for Cadence algorithms.

cad_per_datapoint_score(pipeline, datapoint)

Evaluate the performance of the cadence pipeline on a single datapoint.

cad_final_agg(agg_results, single_results, ...)

Aggregate the results of the cadence evaluation.