A Computational Method to Identify Optimal Functional Muscle Synergies From Estimated Muscle Activations-Reference-Cited by-同舟云学术

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A Computational Method to Identify Optimal Functional Muscle Synergies From Estimated Muscle Activations

Published:2024 Issue: Volume:73 Page:1-14
ISSN:0018-9456
Container-title:IEEE Transactions on Instrumentation and Measurement
language:
Short-container-title:IEEE Trans. Instrum. Meas.

Author:

Chen Yaru¹^ORCID,Wang Yongxuan²^ORCID,Gao Fan³^ORCID,Dong Borui¹^ORCID,Chen Wenqian¹^ORCID,Liu Rong¹^ORCID

Affiliation:

1. Central Hospital, Dalian University of Technology, Dalian, Liaoning, China

2. School of Information Engineering, Dalian University, Dalian, Liaoning, China

3. Department of Kinesiology and Health Promotion, College of Education, University of Kentucky, Lexington, KY, USA

Funder

National Key Research and Development Program of China

Dalian Mentoring Program Project in the Field of Life and Health

China Postdoctoral Science Foundation Funded Project

Opening Fund of National Health Commission (NHC) Key Laboratory of Chronobiology

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx8/19/10367905/10555295.pdf?arnumber=10555295

Reference60 articles.

1. Booklet | Brain-inspired intelligent robotics: The intersection of robotics and neuroscience sciences

2. A Survey of Brain-Inspired Intelligent Robots: Integration of Vision, Decision, Motion Control, and Musculoskeletal Systems

3. Semiparametric Musculoskeletal Model for Reinforcement Learning-Based Trajectory Tracking

4. Hierarchical Motion Learning for Goal-Oriented Movements With Speed-Accuracy Tradeoff of a Musculoskeletal System

5. Learned parametrized dynamic movement primitives with shared synergies for controlling robotic and musculoskeletal systems

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