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

Giardini, Mario E. ORCID: https://orcid.org/0000-0003-4849-9683

Riches, Phil ORCID: https://orcid.org/0000-0002-7708-4607

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• Item metadata

  Item type:	Conference or Workshop Item(Poster)
  ID code:	90470
  Dates:	Date Event 6 September 2024 Published
  Subjects:	Medicine > Biomedical engineering. Electronics. Instrumentation
  Department:	Strategic Research Themes > Health and Wellbeing Faculty of Engineering > Biomedical Engineering
  Depositing user:	Pure Administrator
  Date deposited:	04 Sep 2024 11:48
  Last modified:	15 Dec 2024 02:00
  Related URLs:	Event
  URI:	https://strathprints.strath.ac.uk/id/eprint/90470