Toward Robust and Accurate Myoelectric Controller Design Based on Multiobjective Optimization Using Evolutionary Computation

Myoelectric pattern recognition holds significant importance in designing control strategies for a range of applications, including upper limb prostheses and biorobotic hand movement systems. It serves as a crucial aspect in formulating effective control strategies for these applications. This study...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Veröffentlicht in:	IEEE sensors journal Jg. 24; H. 5; S. 6418 - 6429
Hauptverfasser:	Shaikh, Ahmed Aqeel, Mukhopadhyay, Anand Kumar, Poddar, Soumyajit, Samui, Suman
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York IEEE 01.03.2024 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Accuracy Classification Classifiers Control systems design Controllers Design optimization Electromyogram (EMG) Electromyography Evolutionary algorithms Evolutionary computation evolutionary computation (EC) Genetic algorithms Machine learning machine learning (ML) multiobjective optimization Multiple objective analysis myoelectric control Myoelectricity Optimization Pattern recognition Prostheses Robust control Sensors Sorting algorithms Supervised learning Support vector machines surface electromyography (sEMG) signal classification System effectiveness Training
ISSN:	1530-437X, 1558-1748
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Schreiben Sie den ersten Kommentar!