Raw Bibliometric Data for Hardware-Software Co-Design and Embedded Hardware Deployment for EEG-Based Epileptic Seizure Detection by Scopus included reviews, articles and conference papers

This dataset contains the raw bibliographic metadata exported from the Scopus database on June 14, 2026, used for a systematic review and bibliometric analysis framework. The study focuses on mapping the global research landscape regarding interdisciplinary hardware-software co-design methodologies, deep learning models (such as EEGNet), hyperparameter optimization algorithms (such as the Grey Wolf Optimizer), and physical embedded hardware deployment targets (specifically SoC-FPGAs) tailored for real-time EEG-based epileptic seizure detection. The data is provided in a standardized BibTeX (.bib) format, containing comprehensive structural citation fields including titles, author affiliations, keywords, abstracts, digital object identifiers (DOIs), and citation counts. This file serves as the strict baseline input vector for bibliometrix and biblioshiny R-toolchain parsing execution, ensuring the absolute reproducibility and transparent auditing of the associated science-mapping evaluation.