An efficient deep learning-based motor imagery EEG classification framework for human–machine interface and assistive robotic control
- DOI
- 10.71939/jsme.2026.1246039
- Published
- 2026
- Container
- Not recorded
- Publisher
- Islamic Azad University Press
- Open access
- yes
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Cite this work
BibTeX
@article{allodium:10.71939/jsme.2026.1246039,
title = {An efficient deep learning-based motor imagery EEG classification framework for human–machine interface and assistive robotic control},
author = {Imad AL-Amrie, Mohammed and Nasri, Mehdi and Othman Ahmed, Zied and Fotouhi, Zohreh},
year = {2026},
doi = {10.71939/jsme.2026.1246039},
url = {https://doi.org/10.71939/jsme.2026.1246039}
}RIS
TY - JOUR TI - An efficient deep learning-based motor imagery EEG classification framework for human–machine interface and assistive robotic control AU - Imad AL-Amrie, Mohammed AU - Nasri, Mehdi AU - Othman Ahmed, Zied AU - Fotouhi, Zohreh PY - 2026 DO - 10.71939/jsme.2026.1246039 UR - https://doi.org/10.71939/jsme.2026.1246039 ER -
APA
Mohammed, I. A., Mehdi, N., Zied, O. A., & Zohreh, F. (2026). An efficient deep learning-based motor imagery EEG classification framework for human–machine interface and assistive robotic control. https://doi.org/10.71939/jsme.2026.1246039
Source records
- datacite · retrieved 2026-11-10T16:45:00.536Z