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 -