A Two-Stage GA-Based sEMG Feature Selection Method for User-Independent Continuous Estimation of Elbow Angles-Reference-Cited by-同舟云学术

A Two-Stage GA-Based sEMG Feature Selection Method for User-Independent Continuous Estimation of Elbow Angles

Published:2023 Issue: Volume:72 Page:1-9
ISSN:0018-9456
Container-title:IEEE Transactions on Instrumentation and Measurement
language:
Short-container-title:IEEE Trans. Instrum. Meas.

Author:

Li He¹^ORCID,Guo Shuxiang¹^ORCID,Bu Dongdong¹^ORCID,Wang Hanze¹^ORCID

Affiliation:

1. School of Life Science and the Key Laboratory of Convergence Biomedical Engineering System and Healthcare Technology, The Ministry of Industry and Information Technology, Beijing Institute of Technology, Beijing, China

Funder

National Natural Science Foundation of China

National High-Tech Research and Development Program (863 Program) of China

Special Project of Science (SPS) KAKENHI

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Instrumentation

Link

http://xplorestaging.ieee.org/ielx7/19/10012124/10124780.pdf?arnumber=10124780

Reference24 articles.

1. An intention-based online bilateral training system for upper limb motor rehabilitation

2. Continuous estimation of joint angle from electromyography using multiple time-delayed features and random forests

3. Inter-subject Variability Evaluation of Continuous Elbow Angle from sEMG using BPNN

4. Genetic Algorithm-Based Optimization for the Geometric Design of a Novel Orthopedic Implant

5. An user-independent gesture recognition method based on sEMG decomposition;xiong;Proc IEEE/RSJ Int Conf Intell Robots Syst (IROS),2015

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