Mathis D'Haene

Mr. Mathis D'Haene

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Research Focus & Metrics

Academic Career Length

3Years (2024-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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5 November 2024 in Sensors
Verified
Journal Article
Open access
PDF file
MDMathis D'Haene
Mathis D'Haene
FCFREDERIC CHORIN
FREDERIC CHORIN
SCSerge Sébastien Colson
Serge Sébastien Colson
OGOlivier Guérin
Olivier Guérin
RZRaphaël Zory
Raphaël Zory
EPElodie Piche
Elodie Piche
Gait analysis is essential for evaluating walking patterns and identifying functional limitations. Traditional marker-based motion capture tools are costly, time-consuming, and require skilled operators. This study evaluated a 3D Marker-less Motion Capture (3D MMC) system using pose and depth estimations with the gold-standard Motion Capture (MOCAP) system for measuring hip and knee joint angles during gait at three speeds (0.7, 1.0, 1.3 m/s). Fifteen healthy participants performed gait tasks which were captured by both systems. The 3D MMC system demonstrated good accuracy (LCC > 0.96) and excellent inter-session reliability (RMSE < 3°). However, moderate-to-high accuracy with constant biases was observed during specific gait events, due to differences in sample rates and kinematic methods. Limitations include the use of only healthy participants and limited key points in the pose estimation model. The 3D MMC system shows potential as a reliable tool for gait analysis, offering enhanced usability for clinical and research applications.