Time-Domain Versus Frequency-Embedded EEG Sequences for Sensorimotor BCI Using 1D-CNN

Time-Domain Versus Frequency-Embedded EEG Sequences for Sensorimotor BCI Using 1D-CNN

This study proposed a motor imagery (MI) classification pipeline featuring a 1−dimensional convolutional neural network (1D-CNN) with different time/frequency feature representation techniques. The objective was to classify right hand (RH) versus right foot (RF) MI tasks in both intra- an...

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Bibliographic Details
Main Authors: Simanto Saha, Mathias Baumert, Alistair Mcewan
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Brain–computer interface
electroencephalography
motor imagery
power spectral density
1-dimensional convolutional neural network
Online Access:https://ieeexplore.ieee.org/document/11113278/
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