Details
| Original language | English |
|---|---|
| Article number | 1153160 |
| Journal | Frontiers in Computer Science |
| Volume | 5 |
| Publication status | Published - 6 Jul 2023 |
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.
Keywords
- biomedical application, gait analysis, general movement assessment (GMA), human pose estimation (HPE), markerless motion capture, rehabilitation, survey
ASJC Scopus subject areas
- Computer Science(all)
- Computer Science (miscellaneous)
- Computer Science(all)
- Human-Computer Interaction
- Computer Science(all)
- Computer Vision and Pattern Recognition
- Computer Science(all)
- Computer Science Applications
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In: Frontiers in Computer Science, Vol. 5, 1153160, 06.07.2023.
Research output: Contribution to journal › Review article › Research › peer review
}
TY - JOUR
T1 - Markerless human pose estimation for biomedical applications
T2 - a survey
AU - Avogaro, Andrea
AU - Cunico, Federico
AU - Rosenhahn, Bodo
AU - Setti, Francesco
N1 - Funding Information: This study was carried out within the PNRR research activities of the consortium iNEST (Interconnected North-Est Innovation Ecosystem) funded by the European Union Next-GenerationEU (Piano Nazionale di Ripresa e Resilienza (PNRR) - Missione 4 Componente 2, Investimento 1.5 - D.D. 1058 23/06/2022, ECS_00000043).
PY - 2023/7/6
Y1 - 2023/7/6
N2 - 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.
AB - 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.
KW - biomedical application
KW - gait analysis
KW - general movement assessment (GMA)
KW - human pose estimation (HPE)
KW - markerless motion capture
KW - rehabilitation
KW - survey
UR - http://www.scopus.com/inward/record.url?scp=85165301871&partnerID=8YFLogxK
U2 - 10.3389/fcomp.2023.1153160
DO - 10.3389/fcomp.2023.1153160
M3 - Review article
AN - SCOPUS:85165301871
VL - 5
JO - Frontiers in Computer Science
JF - Frontiers in Computer Science
M1 - 1153160
ER -