Exploration of deep learning-driven multimodal information fusion frameworks and their application in lower limb motion recognition-Reference-Cited by-同舟云学术

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Exploration of deep learning-driven multimodal information fusion frameworks and their application in lower limb motion recognition

Published:2024-10 Issue: Volume:96 Page:106551
ISSN:1746-8094
Container-title:Biomedical Signal Processing and Control
language:en
Short-container-title:Biomedical Signal Processing and Control

Author:

Zhang Changhe^ORCID,Yu Zidong,Wang Xiaoyun,Chen Ze-Jian,Deng Chao^ORCID,Xie Sheng Quan

Publisher

Elsevier BV

Reference56 articles.

1. Analysis and experimental research on stability characteristics of squatting posture of wearable lower limb exoskeleton robot[J];Zheng;Futur. Gener. Comput. Syst.,2021

2. Electromyography-controlled lower extremity exoskeleton to provide wearers flexibility in walking[J];Chen;Biomed. Signal Process. Control,2023

3. Adaptive cooperative control of a soft elbow rehabilitation exoskeleton based on improved joint torque estimation[J];Wu;Mech. Syst. Sig. Process.,2023

4. Periodic event-triggered sliding mode control for lower limb exoskeleton based on human–robot cooperation[J];Wang;ISA Trans.,2022

5. Multi-level feature fusion for multimodal human activity recognition in Internet of Healthcare Things[J];Islam;Information Fusion,2023

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Dynamic graph topology generating mechanism: Framework for feature-level multimodal information fusion applied to lower-limb activity recognition;Engineering Applications of Artificial Intelligence;2024-11

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