Markerless human pose estimation for biomedical applications: a survey

TL;DR

This survey reviews the use of markerless human pose estimation in biomedical fields, highlighting its advantages, current applications, and potential for remote healthcare and rehabilitation.

Contribution

It provides a comprehensive overview of 25 HPE approaches and 40 studies, analyzing their features and trends specific to biomedical applications.

Findings

HPE is increasingly used in motor development and rehabilitation.

Markerless HPE enables remote diagnosis and therapy.

Current approaches show promising accuracy and usability.

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.