EPAT's efficiency is showcased through batch data processing, optimized algorithms, streamlined workflows, a well-designed codebase for execution and low overhead, high modularity for diverse EEG studies, a user-friendly interface easing the learning curve, and robust batch processing capabilities for large datasets, enhancing overall EEG research productivity. 🧠

EPAT employs a process-oriented pipeline, consistent with workflows recommended in EEG research, improving efficiency, and reducing errors. Tailored for clinical needs, its design focuses on resolving clinical issues rather than purely methodological advancements. EPAT also enables customization to meet different research needs, offering a balance between clinical workflows and basic research demands, and facilitating future standardization of procedures. 🌟

 EPAT's unique data structure supports extensive analysis and allows for data export for additional analysis in other common software tools. The design of EPAT emphasizes tight integration between modules, each focusing on specific processing or analysis tasks while ensuring seamless data interfacing and transfer between them. ✍️

The design concept and goal of EPAT are to provide an efficient, easy-to-use, flexible, unified, and repeatable EEG data processing tool so that users can easily process and analyze complex EEG data. 🍀