A Tale of Single-channel Electroencephalogram: Devices, Datasets, Signal Processing, Applications, and Future 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, neurofeedback, educational research, and clinical diagnosis. Additionally, we discuss about the artificial intelligence (AI)-based EEG generation techniques, advancements through the integration of advanced signal processing with AI, innovations in hardware development, and strategies for the integration of wearables enabled by the Internet of Things (IoT), collectively establishing a foundational roadmap for future developments in single-channel EEG systems and their applications.
Link to publication in IEEE
