Markerless human pose estimation for biomedical applications: a survey

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dc.identifier.uri http://dx.doi.org/10.15488/17314
dc.identifier.uri https://www.repo.uni-hannover.de/handle/123456789/17442
dc.contributor.author Avogaro, Andrea
dc.contributor.author Cunico, Federico
dc.contributor.author Rosenhahn, Bodo
dc.contributor.author Setti, Francesco
dc.date.accessioned 2024-04-30T11:01:42Z
dc.date.available 2024-04-30T11:01:42Z
dc.date.issued 2023
dc.identifier.citation Avogaro, A.; Cunico, F.; Rosenhahn, B.; Setti, F.: Markerless human pose estimation for biomedical applications: a survey. In: Frontiers in Computer Science 5 (2023), 1153160. DOI: https://doi.org/10.3389/fcomp.2023.1153160
dc.description.abstract Markerless Human Pose Estimation (HPE) proved its potential to support decision making and assessment in many fields of application. HPE is often preferred to traditional marker-based Motion Capture systems due to the ease of setup, portability, and affordable cost of the technology. However, the exploitation of HPE in biomedical applications is still under investigation. This review aims to provide an overview of current biomedical applications of HPE. In this paper, we examine the main features of HPE approaches and discuss whether or not those features are of interest to biomedical applications. We also identify those areas where HPE is already in use and present peculiarities and trends followed by researchers and practitioners. We include here 25 approaches to HPE and more than 40 studies of HPE applied to motor development assessment, neuromuscolar rehabilitation, and gait & posture analysis. We conclude that markerless HPE offers great potential for extending diagnosis and rehabilitation outside hospitals and clinics, toward the paradigm of remote medical care. eng
dc.language.iso eng
dc.publisher Lausanne : Frontiers Media
dc.relation.ispartofseries Frontiers in Computer Science 5 (2023)
dc.rights CC BY 4.0 Unported
dc.rights.uri https://creativecommons.org/licenses/by/4.0
dc.subject biomedical application eng
dc.subject gait analysis eng
dc.subject general movement assessment (GMA) eng
dc.subject human pose estimation (HPE) eng
dc.subject markerless motion capture eng
dc.subject rehabilitation eng
dc.subject survey eng
dc.subject.ddc 004 | Informatik
dc.title Markerless human pose estimation for biomedical applications: a survey eng
dc.type Article
dc.type Text
dc.relation.essn 2624-9898
dc.relation.doi https://doi.org/10.3389/fcomp.2023.1153160
dc.bibliographicCitation.volume 5
dc.bibliographicCitation.firstPage 1153160
dc.description.version publishedVersion eng
tib.accessRights frei zug�nglich
dc.bibliographicCitation.articleNumber 1153160


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