EEG-Based Motion Intention Detection for Robotic Rehabilitation: Evaluating Classification and Regression Algorithms

Rehabilitation robots have shown significant efficacy in restoring lost motor functions in stroke survivors by providing compliant assistance during rehabilitation tasks. However, accurately understanding the desired motion intention (DMI) of the subjects is a significant challenge in providing effe...

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Veröffentlicht in:	SN computer science Jg. 5; H. 8; S. 1057
Hauptverfasser:	Khan, Abdul Manan, Khan, Fatima, Dwivedi, Anshu Kumar, Semwal, Vijay Bhaskar, Martha, Sheshikala, Bijalwan, Vishwanath
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Singapore Springer Nature Singapore 01.12.2024 Springer Nature B.V
Schlagworte:	Accuracy Algorithms Classification Compliance Computer Imaging Computer Science Computer Systems Organization and Communication Networks Data Structures and Information Theory Decision trees Deep learning Discriminant analysis Effectiveness Electroencephalography Information Systems and Communication Service Machine learning Methods Motion perception Neural networks Original Research Pattern Recognition and Graphics Real time Recovery (Medical) Regression Rehabilitation Rehabilitation robots Research Advancements in Intelligent Computing Robot dynamics Robot learning Robotics Robots Software Engineering/Programming and Operating Systems Support vector machines Vision Deep learning EEG signals Rehabilitation Desired motion intention C-RNN Machine learning
ISSN:	2661-8907, 2662-995X, 2661-8907
Online-Zugang:	Volltext
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