A Tale of Single-Channel Electroencephalography: Devices, Datasets, Signal Processing, Applications, and Future Directions
Yueyang Li, Weiming Zeng, Wenhao Dong, Dong Han, Lei Chen, Hongyu Chen, Zijian Kang, Sheng-yu Gong, Hongjie Yan, Wai Ting Siok, Nizhuan Wang
Abstract
Single-channel electroencephalography (EEG) is a cost-effective, comfortable, and noninvasive 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 article 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. In addition, 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.