A novel scrolling text reading paradigm for improving the performance of multiclass and hybrid brain computer interface systems
Ebru Ergün, Önder Aydemir, Onur Erdem Korkmaz
TL;DR
This paper introduces a new way to use brain signals by having people read scrolling text in different directions, improving brain-computer interface performance.
Contribution
A novel scrolling text reading paradigm for hybrid BCI systems is introduced and validated.
Findings
The proposed BCI paradigm achieved 96.28% ± 1.30% classification accuracy for multi-class tasks.
Hybrid EEG and NIRS signals were effectively used to enhance system performance.
Segmenting data into temporal windows improved accuracy and speed of the BCI system.
Abstract
A Brain-Computer Interface (BCI) enables direct communication between the brain and external devices, such as computers or prosthetic limbs. This allows the brain to send commands while receiving sensory feedback from the device. Despite their potential, the performance limitations of existing BCI systems have motivated researchers to improve their efficiency and reliability. To address this challenge, the present study introduces a novel BCI paradigm centered on a cognitive task involving the reading of scrolling text in four different directions: right, left, up and down. The primary objective was to explore the electroencephalography (EEG) and near-infrared spectroscopy (NIRS) signals within this framework and assess the potential of hybrid BCI systems based on this innovative paradigm. The experimental protocol involved eight participants performing tasks across four classes of…
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Taxonomy
TopicsEEG and Brain-Computer Interfaces · Gaze Tracking and Assistive Technology · Optical Imaging and Spectroscopy Techniques