Markerless Gait Deviation Analysis for Robot-Assisted Rehabilitation – Dataset and Python Pipeline

This repository contains the complete reproducible dataset and Python analysis pipeline used in the study: “Individualized Gait Deviation Analysis Using Smartphone-Based Markerless Motion Capture to Support Robot-Assisted Gait Rehabilitation.” The project includes patient-specific gait kinematic data extracted using OpenCap and processed through OpenSim 4.5 to generate joint angle trajectories. The accompanying Python pipeline provides: Gait-cycle normalization Z-score deviation mapping using a normative dataset Phase-wise deviation extraction Radar-chart visualization of gait abnormalities Automated reproducibility pipeline (master script) Processed pickle files for rapid re-analysis The dataset and code enable full reproducibility of the individualized deviation profiling for four pediatric patients (P001–P004) undergoing robot-assisted gait rehabilitation. Folder structure: /P001–P004 # Patient-specific processed kinematic data/processed_pickle # Z-score matrices, phase-wise tables (tables.pkl)/results # Saved radar charts and plots20251209_gait_robot.ipynb This Zenodo entry is intended to support transparency, reproducibility, and reuse in gait analysis and rehabilitation research.