30 citations · 127 across the 33 of their papers we have counts for
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eess.SP2021★ 2 cited
EEG-Inception: An Accurate and Robust End-to-End Neural Network for EEG-based Motor Imagery Classification
Ce Zhang, Young-Keun Kim, Azim Eskandarian
Classification of EEG-based motor imagery (MI) is a crucial non-invasive application in brain-computer interface (BCI) research. This paper proposes a novel convolutional neural ne…
eess.SP2020★ 13 cited
A Computationally Efficient Multiclass Time-Frequency Common Spatial Pattern Analysis on EEG Motor Imagery
Ce Zhang, Azim Eskandarian
Common spatial pattern (CSP) is a popular feature extraction method for electroencephalogram (EEG) motor imagery (MI). This study modifies the conventional CSP algorithm to improve…
eess.SP2020★ 2 cited
A Survey and Tutorial of EEG-Based Brain Monitoring for Driver State Analysis
Ce Zhang, Azim Eskandarian
Drivers cognitive and physiological states affect their ability to control their vehicles. Thus, these driver states are important to the safety of automobiles. The design of advan…