A hybrid CNN model for classification of motor tasks obtained from hybrid BCI system
Abstract The Hybrid-Brain Computer Interface (BCI) has shown improved performance, especially in classifying multi-class data. Two non-invasive BCI modules are combined to achieve an improved classification which are Electroencephalogram (EEG) and functional Near Infra-red Spectroscopy (fNIRS). Clas...
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Main Authors: | , , , |
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Format: | Article |
Language: | English |
Published: |
Nature Portfolio
2025-01-01
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Series: | Scientific Reports |
Subjects: | |
Online Access: | https://doi.org/10.1038/s41598-024-84883-2 |
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