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What is BCI Signal Classification via fNIRS about?
This research article evaluates the classification performance of functional near infrared spectroscopy (fNIRS) signals for developing a brain-computer interface (BCI) aimed at assisting motor-impaired individuals. The study compares different channel selection methods and features to enhance classification accuracy during upper limb movement tasks, achieving promising results with accuracies of up to 87.25%. The findings suggest that fNIRS can effectively differentiate between motor tasks and resting state
- Author
- Janani Arivudaiyanambi
- Language
- EN