A Spatiotemporal Feature Extraction Technique Using Superlet-CNN Fusion for Improved Motor Imagery Classification

A Spatiotemporal Feature Extraction Technique Using Superlet-CNN Fusion for Improved Motor Imagery Classification

In the realm of Brain-Computer Interface (BCI) research, the precise decoding of motor imagery electroencephalogram (MI-EEG) signals is pivotal for the realization of systems that can be seamlessly integrated into practical applications, enhancing the autonomy of individuals with mobility impairment...

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Bibliographic Details
Main Authors: Neha Sharma, Manoj Sharma, Amit Singhal, Nuzhat Fatema, Vinay Kumar Jadoun, Hasmat Malik, Asyraf Afthanorhan
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Motor imagery (MI)
deep neural network (DNN)
superlet transform (SLT)
brain-computer interface (BCI)
Online Access:https://ieeexplore.ieee.org/document/10802872/
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https://ieeexplore.ieee.org/document/10802872/

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