Walking representation and simulation based on multi-source image fusion and multi-agent reinforcement learning for gait rehabilitation-Reference-Cited by-同舟云学术

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Walking representation and simulation based on multi-source image fusion and multi-agent reinforcement learning for gait rehabilitation

Published:2024-10 Issue: Volume:156 Page:102945
ISSN:0933-3657
Container-title:Artificial Intelligence in Medicine
language:en
Short-container-title:Artificial Intelligence in Medicine

Author:

Zhu Yean^ORCID,Xiao Meirong,Robbins Dan,Wu Xiaoying,Lu Wei,Hou Wensheng

Funder

Chongqing University

National Natural Science Foundation of China

National Key Research and Development Program of China

Key Science and Technology Research Project in Jiangxi Province Department of Education

Publisher

Elsevier BV

Reference51 articles.

1. Dual-channel cascade pose estimation network trained on infrared thermal image and groundtruth annotation for real-time gait measurement;Zhu;Med Image Anal,2022

2. Applying the knowledge-to-action framework to implement gait and balance assessments in inpatient stroke rehabilitation;Moore;Arch Phys Med Rehabil,2020

3. Extraction and selection of gait recognition features using skeleton point detection and improved fuzzy decision;Zhu;Med Eng Phys,2020

4. Gait acquisition and analysis system for osteoarthritis based on hybrid prediction model;Chen;Comput Med Imaging Graph,2020

5. A novel vision-based real-time method for evaluating postural risk factors associated with musculoskeletal disorders;Li;Appl Ergon,2020

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