mlsanityData to 7 Oct 2026

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

arXiv 2405.00726 ↗First posted 26 Apr 2024eess.SP cs.AI cs.HCcited by 10

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Abstract (arXiv)

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.

Key facts. Cited by 10 papers in the map (data through 7 Oct 2026). Builds on 14 of its 122 references that are in the map. First posted on arXiv 26 Apr 2024.

Builds on

14 of 122 references.

References · 14

  1. 2022Mind Reader: Reconstructing complex images from brain activitiescited by 85
  2. 2016Deep Learning Human Mind for Automated Visual Classificationcited by 76
  3. 2021Open Vocabulary Electroencephalography-To-Text Decoding and Zero-shot Sentiment Classificationcited by 67
  4. 2019ZuCo 2.0: A Dataset of Physiological Recordings During Natural Reading and Annotationcited by 65
  5. 2018EEG-GAN: Generative adversarial networks for electroencephalograhic (EEG) brain signalscited by 46
  6. 2015Learning Representations from EEG with Deep Recurrent-Convolutional Neural Networkscited by 45
  7. 2015Transfer Learning in Brain-Computer Interfacescited by 39
  8. 2023DeWave: Discrete EEG Waves Encoding for Brain Dynamics to Text Translationcited by 36
  9. 2020Brain2Word: Decoding Brain Activity for Language Generationcited by 15
  10. 2022On The Effects Of Data Normalisation For Domain Adaptation On EEG Datacited by 13
  11. 2017Converting Your Thoughts to Texts: Enabling Brain Typing via Deep Feature Learning of EEG Signalscited by 11
  12. 2017Effective and Extensible Feature Extraction Method Using Genetic Algorithm-Based Frequency-Domain Feature Search for Epileptic EEG Multi-classificationcited by 3
2 more
  1. 2021A General Framework for Revealing Human Mind with auto-encoding GANscited by 3
  2. 2023Ongoing EEG artifact correction using blind source separationcited by 2

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 1; 2025: 5; 2026: 4.

10 papers.