A Tale of Single-channel Electroencephalogram: Devices, Datasets, Signal Processing, Applications, and Future Directions

TL;DR

This paper reviews the development, devices, datasets, signal processing, and applications of single-channel EEG, highlighting its growing importance and potential in various fields including sleep, emotion, education, and clinical diagnosis.

Contribution

It provides a comprehensive overview of single-channel EEG, clarifies configurations, and discusses recent advancements and future directions in the field.

Findings

Single-channel EEG is increasingly used in diverse applications.

AI-based EEG generation techniques show promise for parity or superiority.

The review highlights ongoing development and future research directions.

Abstract

Single-channel electroencephalogram (EEG) is a cost-effective, comfortable, and non-invasive method for monitoring brain activity, widely adopted by researchers, consumers, and clinicians. The increasing number and proportion of articles on single-channel EEG underscore its growing potential. This paper provides a comprehensive review of single-channel EEG, focusing on development trends, devices, datasets, signal processing methods, recent applications, and future directions. Definitions of bipolar and unipolar configurations in single-channel EEG are clarified to guide future advancements. Applications mainly span sleep staging, emotion recognition, educational research, and clinical diagnosis. Ongoing advancements of single-channel EEG in AI-based EEG generation techniques suggest potential parity or superiority over multichannel EEG performance.