Amplitude-Time Dual-View Fused EEG Temporal Feature Learning for Automatic Sleep Staging

• Published in: IEEE transaction on neural networks and learning systems Vol. 35; no. 5; pp. 6492 - 6506
• Main Authors: An, Panfeng, Zhao, Jianhui, Du, Bo, Zhao, Wenyuan, Zhang, Tingbao, Yuan, Zhiyong
• Format: Journal Article
• Language: English
• Published: United States IEEE 01.05.2024; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Adult; Algorithms; Amplitude; Amplitudes; Amplitude–time dual-view fusion; Artificial neural networks; attention; automatic sleep staging; Cognitive ability; Cognitive tasks; Convolutional neural networks; EEG; electroencephalogram (EEG); Electroencephalography; Electroencephalography - methods; Feature extraction; feature learning; Female; Human performance; Humans; hybrid dilation convolution; Learning; Learning systems; Machine Learning; Male; Neural networks; Neural Networks, Computer; Performance evaluation; Representation learning; Representations; Signal Processing, Computer-Assisted; Sleep; Sleep disorders; Sleep Stages - physiology; Young Adult

Electroencephalogram (EEG) plays an important role in studying brain function and human cognitive performance, and the recognition of EEG signals is vital to develop an automatic sleep staging system. However, due to the complex nonstationary characteristics and the individual difference between sub...