Unveiling Thoughts: A Review of Advancements in EEG Brain Signal Decoding into Text

TL;DR

This review summarizes recent progress and challenges in EEG-based brain signal decoding into text, highlighting current techniques, limitations, and future research directions to improve Brain-Computer Interface systems.

Contribution

It provides a comprehensive overview of EEG-to-text conversion methods, recent advancements, and outlines future research needs for more accurate and versatile BCI applications.

Findings

Significant progress in EEG-to-text decoding techniques

Existing challenges include accuracy and system constraints

Future directions involve exploring novel applications and improving performance

Abstract

The conversion of brain activity into text using electroencephalography (EEG) has gained significant traction in recent years. Many researchers are working to develop new models to decode EEG signals into text form. Although this area has shown promising developments, it still faces numerous challenges that necessitate further improvement. It's important to outline this area's recent developments and future research directions. In this review article, we thoroughly summarize the progress in EEG-to-text conversion. Firstly, we talk about how EEG-to-text technology has grown and what problems we still face. Secondly, we discuss existing techniques used in this field. This includes methods for collecting EEG data, the steps to process these signals, and the development of systems capable of translating these signals into coherent text. We conclude with potential future research directions, emphasizing the need for enhanced accuracy, reduced system constraints, and the exploration of novel applications across varied sectors. By addressing these aspects, this review aims to contribute to developing more accessible and effective Brain-Computer Interface (BCI) technology for a broader user base.