A Machine Learning Strategy for Locomotion Classification and Parameter Estimation Using Fusion of Wearable Sensors-Reference-Cited by-同舟云学术

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A Machine Learning Strategy for Locomotion Classification and Parameter Estimation Using Fusion of Wearable Sensors

Published:2021-05 Issue:5 Volume:68 Page:1569-1578
ISSN:0018-9294
Container-title:IEEE Transactions on Biomedical Engineering
language:
Short-container-title:IEEE Trans. Biomed. Eng.

Author:

Camargo Jonathan,Flanagan Will,Csomay-Shanklin Noel,Kanwar Bharat,Young Aaron

Funder

Fulbright fellowship awarded to Jonathan Camargo-Leyva

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Biomedical Engineering

Link

http://xplorestaging.ieee.org/ielx7/10/9410303/09376982.pdf?arnumber=9376982

Cited by 36 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. A Data-Driven Approach to Estimate Human Center of Mass State During Perturbed Locomotion Using Simulated Wearable Sensors;Annals of Biomedical Engineering;2024-04-01

2. Leveraging High-Density EMG to Investigate Bipolar Electrode Placement for Gait Prediction Models;IEEE Transactions on Human-Machine Systems;2024-04

3. Estimating human joint moments unifies exoskeleton control, reducing user effort;Science Robotics;2024-03-20

4. A multimodal framework based on deep belief network for human locomotion intent prediction;Biomedical Engineering Letters;2024-02-09

5. Actuator optimization and deep learning-based control of pediatric knee exoskeleton for community-based mobility assistance;Mechatronics;2024-02

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