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

Saydul Akbar Murad, Nick Rahimi
4/26/2024
eess.SPcs.AIcs.HC

No confident code implementation found for this paper.

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.

View on arXivView PDF

Code Implementations

No confident code match yet

We couldn't find an author-owned or strongly-evidenced community implementation for this paper. Any repos shown below are weak matches — verify before relying on them.

No code implementations found yet.

Know of an implementation? Let us know in the comments below!

Similar Papers

Cite this paper

@article{murad2024unveiling,
  title  = {Unveiling Thoughts: A Review of Advancements in EEG Brain Signal Decoding into Text},
  author = {Saydul Akbar Murad and Nick Rahimi},
  year   = {2024},
  eprint = {2405.00726},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2405.00726v2}
}

Add a badge to your README

Shows whether official code is linked for this paper.

Code of Paper badge
[![Code of Paper](https://codeofpaper.com/badge/2405.00726.svg)](https://codeofpaper.com/paper/2405.00726)

Discussion