Open Access

ARTICLE

Movement Function Assessment Based on Human Pose Estimation from Multi-View

by Lingling Chen^1,2,*, Tong Liu¹, Zhuo Gong¹, Ding Wang¹

1 School of Artificial Intelligence, Hebei University of Technology, Tianjin, 300400, China
2 Intelligent Rehabilitation Device and Detection Technology Engineering Research Centre of the Ministry of Education, Tianjin, 300400, China

* Corresponding Author: Lingling Chen. Email:

(This article belongs to the Special Issue: Artificial Intelligence enabled Smart Health Care Decision Support Systems)

Computer Systems Science and Engineering 2024, 48(2), 321-339. https://doi.org/10.32604/csse.2023.037865

Received 18 November 2022; Accepted 17 February 2023; Issue published 19 March 2024

Abstract

Human pose estimation is a basic and critical task in the field of computer vision that involves determining the position (or spatial coordinates) of the joints of the human body in a given image or video. It is widely used in motion analysis, medical evaluation, and behavior monitoring. In this paper, the authors propose a method for multi-view human pose estimation. Two image sensors were placed orthogonally with respect to each other to capture the pose of the subject as they moved, and this yielded accurate and comprehensive results of three-dimensional (3D) motion reconstruction that helped capture their multi-directional poses. Following this, we propose a method based on 3D pose estimation to assess the similarity of the features of motion of patients with motor dysfunction by comparing differences between their range of motion and that of normal subjects. We converted these differences into Fugl–Meyer assessment (FMA) scores in order to quantify them. Finally, we implemented the proposed method in the Unity framework, and built a Virtual Reality platform that provides users with human–computer interaction to make the task more enjoyable for them and ensure their active participation in the assessment process. The goal is to provide a suitable means of assessing movement disorders without requiring the immediate supervision of a physician.

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Keywords

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