Processing Motion Data C3D Files: a Python Script Repository for Human Gait Analysis

Quantitative gait analysis commonly relies on marker-based optoelectronic motion capture (mocap) systems, which provide high-resolution kinematic data and can be synchronized with force plates, electromyographic (EMG) sensors, and other biomechanical devices. Although the C3D file format is widely used to store these multimodal data, extracting, segmenting, and processing C3D content often requires proprietary software or manual procedures that limit reproducibility and hinder large-scale analyses. This work presents an open, script-based framework for processing locomotion trials, combining Vicon ProCalc models with two Python pipelines designed to automate stride segmentation and compute spatio-temporal and mechanical parameters of human gait. The first pipeline (“python_operations”) performs stride detection using kinematic criteria based on foot marker vertical velocity. It interactively identifies initial foot contacts, segments the trial into strides, and exports markers, model outputs, and EMG signals into portable CSV and NumPy (npy) formats. Additional utilities prepare EMG data for muscle synergy analysis using the open-source R package musclesyneRgies. The second pipeline (“energetics”) loads the stride-based npy files and computes key gait variables, including stride time, stride length, duty factor, center-of-mass energies, external and internal mechanical work, recovery indices, and congruence. The pipeline also generates diagnostic plots of kinetic, potential, and total energies for each stride. All scripts, Vicon models, and example datasets are provided in the public GitLab repository fromC3d_to_energetics, enabling full reproducibility and facilitating adaptation to different research needs. The proposed framework offers a transparent, customizable, and extensible solution for researchers requiring automated processing of C3D files and detailed mechanical analysis of human locomotion.