CIN_code: Markerless Gait Analysis Pipeline for Critical Illness Neuropathy (CIN)

This repository contains the code and example data used to generate gait kinematic graphs for a patient with suspected critical illness neuropathy (CIN). The pipeline was developed using the OpenCap markerless motion-capture platform and includes fully reproducible scripts for loading OpenCap output, computing joint-angle Z-scores, and generating publication-ready figures. This archive is provided as supplementary material for the associated manuscript. 📁 Contents of the Repository 1. opencap_graph_code/ Python scripts for: loading OpenCap .pkl or .csv kinematic data computing Z-scores against a normative dataset detecting gait-cycle segments exceeding threshold (|Z| > 2) generating three-panel kinematic plots (hip/knee/ankle) exporting figures as high-resolution PNG/PDF for publication Key files: CIN_opencap_pipeline.ipynb — full notebook version of the analysis 2. example_data/ gait_1.mot — example OpenCap motion file used to demonstrate the pipeline Example preprocessed joint-angle arrays (if available) Normative mean ± SD dataset (if provided in the manuscript) ▶️ How to Run the Code Requirements Python ≥ 3.9 Recommended libraries: numpy pandas scipy matplotlib seaborn pickle Quick Start Open the notebook: CIN_opencap_pipeline.ipynb Load the provided gait_1.mot file or your own OpenCap output. Run all cells to: preprocess gait cycles compute segment-level Z-scores generate kinematic deviation plots Output Figures The pipeline automatically generates: Hip/knee/ankle sagittal kinematic curves Control ±1 SD and ±2 SD shaded regions Red-highlighted gait-cycle segments where |Z| > 2 These figures match those presented in the manuscript. 📘 Data Description gait_1.mot OpenSim-compatible motion file exported from OpenCap.Contains time-series joint kinematics for: Hip flexion Knee flexion Ankle dorsiflexion Pelvis orientation (optional) Time is expressed in seconds, and all joint angles are in degrees.