The effect of sampling methods on the validity and reliability of the estimation of the orbital stability of human gait

Floquet multiplier (FM) is a commonly used metric for evaluating gait orbital stability in biomechanics. However, variability of human gait and noise from various sources can induce significant bias and variance in the estimation of FM. Furthermore, FM is employed in gait analysis without standardized protocols, leading to highly case-dependent outcomes. To address these challenges, we quantify the effects of sampling conditions on the accuracy and consistency of FM estimations. We recruited 20 healthy participants and conducted five trials of 10-minute walking per participant. Using individualized Jacobian matrices calculated from the walking experiments, we synthesized multiple sets of virtual time series with varying lengths and trial counts. Using stochastic linear models, we simulated the error dynamics depending on the sampling methods. The bias and variance of FM estimates decreased significantly with increased time series length, and a significant interaction was observed betwee..., , , # Floquet Multiplier (Gait Orbital Stability): Open-Source Dataset and Code

This repository provides open-source data and code for analyzing **orbital stability of human gait** using **Floquet Multipliers (FMs)**. Included are raw experimental data, simulation data, processed results, and Python scripts used for the analysis.

The full methodology and results are detailed in the following publication:\
🔗 [https://doi.org/10.1098/rsos.250106](https://doi.org/10.1098/rsos.250106)

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## 📂 Folder Structure

```text
Supplementary_Data
│
├── Code # Python scripts for data analysis
│ ├── FM_Clinical_Experiment.py
│ ├── FM_Simulation.py
│ └── FM_Functions.py
│
└── Data
│
├── RawData # Walking experiment data
│ └── WalkingData.joblib
│
├── RawData_Results # Intermediate and result files generated from walking experi...,