Abstract: NeuroSync is a pioneering brain-computer interface (BCI) system designed for real-time character recognition, leveraging electroencephalography (EEG) signals to enable seamless communication and control. This paper presents the architecture, implementation, and evaluation of NeuroSync, emphasizing its potential to revolutionize human-computer interaction paradigms and empower individuals with diverse abilities. The system utilizes the BioAmp EXG pill for EEG signal acquisition, coupled with the ADS1115 analog-to-digital converter for precise digitization. A Raspberry Pi 3B+ serves as the computational hub, employing an ensemble model to classify incoming signals into eight characters (‘f’, ‘b’, ‘l’, ‘r’, ‘y’, ‘n’, ‘h’, ‘e’) each corresponding to a certain word. NeuroSync embodies a convergence of interdisciplinary expertise, drawing insights from neuroscience, machine learning, and embedded systems. NeuroSync has the capacity to enhance communication and augment human-machine interaction. This paper provides insights into the technical specifications, signal processing pipeline, machine learning architecture, and performance evaluation of NeuroSync, showcasing its potential to foster inclusive computing and improve the quality of life for individuals with disabilities.

Keywords: Brain-Computer Interface (BCI), Electroencephalography (EEG), Assistive technology, Real-time character recognition, Human-Computer Interaction (HCI)

| DOI: 10.17148/IARJSET.2024.11439