학술논문
Review of Deep Learning Methods for Automated Sleep Staging
Document Type
Conference
Source
2022 IEEE 12th Annual Computing and Communication Workshop and Conference (CCWC) Computing and Communication Workshop and Conference (CCWC), 2022 IEEE 12th Annual. :0080-0086 Jan, 2022
Subject
Language
Abstract
In order to diagnose sleep problems, it is critical to correctly identify sleep stages which is a labor-intensive task. Due to rising data volumes, advanced algorithms, and improvements in computational power and storage, artificial intelligence has been more popular in recent years. Automated sleep staging through cardiac rhythm is one of the active research areas that has gained attention over the last decade. In this study, we review four recent state-of-the-art deep learning methods for automated sleep staging, datasets developed in recent years, and discuss their performance evaluations.