A Synergy of Convolutional Neural Networks for Sensor-Based EEG Brain–Computer Interfaces to Enhance Motor Imagery Classification

A Synergy of Convolutional Neural Networks for Sensor-Based EEG Brain–Computer Interfaces to Enhance Motor Imagery Classification

Enhancing motor disability assessment and its imagery classification is a significant concern in contemporary medical practice, necessitating reliable solutions to improve patient outcomes. One promising avenue is the use of brain–computer interfaces (BCIs), which establish a direct communication pa...

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Bibliographic Details
Main Authors: Souheyl Mallat, Emna Hkiri, Abdullah M. Albarrak, Borhen Louhichi
Format: Article
Language:English
Published: MDPI AG 2025-01-01
Series:Sensors
Subjects:
brain–computer interface
electroencephalography
deep learning
convolutional neural network
Online Access:https://www.mdpi.com/1424-8220/25/2/443
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