Biomechanically Accurate Gait Analysis: A 3d Human Reconstruction Framework for Markerless Estimation of Gait Parameters

TL;DR

This paper introduces a biomechanically interpretable 3D human reconstruction framework for markerless gait analysis, achieving accurate joint kinematic estimation comparable to marker-based systems and surpassing pose-estimation methods.

Contribution

It presents a novel approach that extracts biomechanically meaningful markers from video data and integrates them with OpenSim for accurate, markerless gait analysis.

Findings

Strong agreement with marker-based measurements

Significant improvements over pose-estimation methods

Scalable and interpretable gait assessment framework

Abstract

This paper presents a biomechanically interpretable framework for gait analysis using 3D human reconstruction from video data. Unlike conventional keypoint based approaches, the proposed method extracts biomechanically meaningful markers analogous to motion capture systems and integrates them within OpenSim for joint kinematic estimation. To evaluate performance, both spatiotemporal and kinematic gait parameters were analysed against reference marker-based data. Results indicate strong agreement with marker-based measurements, with considerable improvements when compared with pose-estimation methods alone. The proposed framework offers a scalable, markerless, and interpretable approach for accurate gait assessment, supporting broader clinical and real world deployment of vision based biomechanics