Validating the OpenBCI Nodes within the Node-RED Library through an EEG-based BCI Application for IoT

Abstract

Combining BCI applications with IoT devices and services offers significant benefits in various fields. While there are BCI software platforms currently available, there is a limited number of systems specifically designed to support developers in building BCI applications with IoT devices and services, particularly for users who may be less experienced in programming. To address these challenges, we tested and validated the OpenBCI toolkit utilizing BrainFlow library in the Node-RED platform for visual node-based programming. This was accomplished through a case study focused on controlling a robotic arm with an OpenBCI headset. The research findings indicated that bursts in Event-Related Synchronization in the frequency bands $\theta$ and $\gamma$ in the frontal lobe, and high $\beta$ in the left central and parietal lobes, were particularly significant for controlling a robotic arm through attention and concentration. Additionally, the average threshold for the ‘Mindfulness’ metric, provided by BrainFlow classifiers, was consistent around 0.30 with standard deviation of 0.08.