Comparative Analysis of Tri-Polar Concentric Ring and Conventional Electrodes for Overt and Covert Speech

Source abstract

Brain-Computer Interface (BCI) is a system that enables the human brain to interact with the external environment without using muscles. Electroencephalography (EEG) is a commonly used modality for measuring neural brain activity. However, its low signal-to-noise ratio (SNR) and electrode reference problems lead to poor spatial resolution. As a result, EEG signals are often contaminated with physiological artifacts such as muscle movements. Therefore, this study used novel tripolar concentric ring electrodes (TCREs) that are used to record brain activity related to the overt and covert speech. Brain signals associated with overt and covert speech were recorded using TCREs and disc electrodes. Classification algorithms, including K-Nearest Neighbors (KNN), Fully Connected Neural Networks (FCNNN), and Convolutional Neural Networks (CNN), were used to classify the TCRE and conventional EEG signals. The data was collected from 16 healthy participants. The experimental results demonstrate that TCREs provide superior performance compared to conventional disc electrodes. In addition to that, the 0.5–1.2s interval, corresponding to the peak stimulus window, exhibits a maximum power of 250µV. The average accuracy achieved during this epoch was 86.25%, whereas the remaining epoch shows an accuracy of 83.5% using TCREs.