CoordinationMetricsToolbox 0.1.1

A toolbox for measuring and analyzing coordination metrics.

CoordinationMetricsToolbox

Coordination Metrics Toolbox

The Coordination Metrics Toolbox is a comprehensive suite of tools designed to measure and analyze coordination metrics in various projects.

Installation

Download this repository At the root of this repository, run pip install .

Or pip install CoordinationMetricsToolbox

Informations

This work comes from the article : Dubois, O., Roby-Brami, A., Parry, R. et al. A guide to inter-joint coordination characterization for discrete movements: a comparative study. J NeuroEngineering Rehabil 20, 132 (2023). https://doi.org/10.1186/s12984-023-01252-2

Not all metrics have been implemented since some of them needs additional informations suche as joints position over time.

2 more metrics have been added : Joints contribution variation based on Principal Component Analysis (JcvPCA) and Joint Synchronization Variation based on Continuous Relative Phase (JsvCRP). These metrics are under publication for PLOS-One

Tutorial

An exemple with simulated data is available in test_coord_metric.py. CSV files containing a time column and joint angles trajectories can also be loaded to build a CoodinationMetric object form which different metrics can be computed.

The format expected for the data is the following one :

time	joint_i	joint_j	joint_k	ee_x	ee_y	ee_z

Columns in italic (ee_x, ee_y, ee_z) which are the position of the end-effector are optional. However, without thoses columns, the number of metrics that can be computed is limited.

The file generate_testing_dataset.py can also be used to generate different datasets based on sinusoids. You can personalize this file to generate your own datasets.

The full documentation of the toolbox can be found here

Generate local documentation

Go to the doc file and execute make html