Tackling Challenges of Electroencephalogram on an Android Smartphone for Natural Environment Experimentation

Abstract

Electroencephalogram (EEG) is a non-invasive technique used to measure brain activity and has applications in cognitive studies, neuroscience, and clinical diagnostics. Traditional EEG experiments are often lab-confined, requiring stationary setups with multiple electrodes, which limits the mobility of human subjects and real-world applicability. Mobile EEG systems have emerged as a flexible alternative that enables brain activity monitoring of human subjects in natural settings using lightweight and portable equipment. Among these, smartphone-based mobile EEG offers a promising solution by combining portability, affordability, and real-time signal acquisition with computational capabilities. However, challenges such as artifact removal, data processing, and brain state classification on smartphones must be addressed for effective deployment. This research aims to address these gaps by developing smartphone-based EEG analysis frameworks with three major contributions.