Abstract

Electroencephalography (EEG) is a tool that is used to record the brain's electrical activity. This brain monitoring process is used to diagnose tumors or mental illnesses, as well as to identify sleep disorders and behavioral changes. EEG signals also enable researchers to decode the specific contents of working memory (WM) and understand how the brain processes information over time. Due to the complexity of the data, various advanced statistical methods are employed to analyze EEG data. One such method is functional data analysis (FDA), which has recently become popular in digital health monitoring. In this study, we will use FDA approach in a case study to analyze the EEG signals of 20 children who received three different types of information (visual, spatial or verbal) during a game. Then, we will use the obtained information to decode the WM content. Our goal is to compare the performance of the FDA-based approach with that of alternative methods.