Markerless motion analysis : evaluation of OpenPose software for clinical gait analysis

Penev, Victor and Giardini, Mario E. and Ligeti, Alexandra and Riches, Phil (2024) Markerless motion analysis : evaluation of OpenPose software for clinical gait analysis. In: BioMedEng24, 2024-09-05 - 2024-09-06, Queen Mary University of London.

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Abstract

Motion analysis plays a crucial role in clinical, research, and rehabilitation settings. Markerless motion capture (MMC) could offer a cheaper, quicker and more accessible alternative to movement analysis than marker-based approaches. OpenPose is an open-source human pose estimation software which could potentially be used as part of a markerless approach.

ORCID iDs

Penev, Victor, Giardini, Mario E. ORCID logoORCID: https://orcid.org/0000-0003-4849-9683, Ligeti, Alexandra and Riches, Phil ORCID logoORCID: https://orcid.org/0000-0002-7708-4607;
CORE (COnnecting REpositories)