CKATool: A clinical kinematic analysis toolbox for upper limb rehabilitation

Area of Science:

• Biomechanics
• Rehabilitation Science
• Movement Science

Background:

• Quantitative analysis of upper limb movement is crucial in rehabilitation and movement science.
• Existing tools may lack comprehensive kinematic metrics or interactive visualization capabilities.

Purpose of the Study:

• To introduce CKATool, a Python-based toolbox for analyzing upper limb kinematics.
• To provide a flexible and extensible platform for researchers and clinicians.
• To facilitate open and reproducible research in movement analysis.

Main Methods:

• Development of CKATool using Python, implementing kinematic metrics in six domains.
• Integration of the Rerun platform for interactive 3D visualization.
• Validation using three public datasets (Arm-CODA, 3D-ARM-Gaze, IntelliRehabDS).

Main Results:

• CKATool successfully processed and visualized data from diverse upper limb tasks.
• The toolbox demonstrated compatibility with various experimental setups.
• All implemented kinematic metrics were functional and validated.

Conclusions:

• CKATool provides a valuable resource for upper limb kinematic analysis.
• The toolbox supports diverse research needs and promotes open science.
• CKATool enhances the analysis and visualization of movement data in clinical and research settings.