Gait analysis comparison between manual marking, 2D pose estimation algorithms, and 3D marker-based system.

ABSTRACT:

Introduction

Recent advances in Artificial Intelligence (AI) and Computer Vision (CV) have led to automated pose estimation algorithms using simple 2D videos. This has created the potential to perform kinematic measurements without the need for specialized, and often expensive, equipment. Even though there's a growing body of literature on the development and validation of such algorithms for practical use, they haven't been adopted by health professionals. As a result, manual video annotation tools remain pretty common. Part of the reason is that the pose estimation modules can be erratic, producing errors that are difficult to rectify. Because of that, health professionals prefer the use of tried and true methods despite the time and cost savings pose estimation can offer.

Met

SUBMITTER: Menychtas D 

PROVIDER: S-EPMC10511642 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature