Forearm Orientation and Muscle Force Invariant Feature Selection Method for Myoelectric Pattern Recognition-Reference-Cited by-同舟云学术

Forearm Orientation and Muscle Force Invariant Feature Selection Method for Myoelectric Pattern Recognition

Published:2022 Issue: Volume:10 Page:46442-46471
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Islam Md. Johirul¹^ORCID,Ahmad Shamim²,Haque Fahmida³,Reaz Mamun Bin Ibne³^ORCID,Bhuiyan Mohammad A. S.⁴^ORCID,Islam Md. Rezaul¹

Affiliation:

1. Department of Electrical and Electronic Engineering, University of Rajshahi, Rajshahi, Bangladesh

2. Department of Computer Science and Engineering, University of Rajshahi, Rajshahi, Bangladesh

3. Department of Electrical, Electronic and Systems Engineering, Universiti Kebangsaan Malaysia, Bangi, Malaysia

4. Department of Electrical and Electronic Engineering, Xiamen University Malaysia, Bandar Sunsuria, Malaysia

Funder

Xiamen University Malaysia, Project number

Information and Communication Technology Division, Ministry of Posts, Telecommunications and Information Technology, Government of Bangladesh under reference number

Universiti Kebangsaan Malaysia

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/6287639/9668973/09762929.pdf?arnumber=9762929

Reference47 articles.

1. Feature reduction and selection for EMG signal classification

2. EMG feature evaluation for improving myoelectric pattern recognition robustness

3. A novel channel selection method for multiple motion classification using high-density electromyography

4. A novel hybrid whale optimization algorithm with flower pollination algorithm for feature selection: Case study Email spam detection

5. EMG Feature Selection and Classification Using a Pbest-Guide Binary Particle Swarm Optimization

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