Name
Abstract | ||
|---|---|---|
Manual scoring of sleep stages from polysomnography (PSG) records is essential to understand the sleep quality and architecture. Since the PSG requires specialized personnel, a lab environment, and uncomfortable sensors, non-contact sleep staging methods based on machine learning techniques have been investigated over the past years. In this study, we propose an attention-based bidirectional long ... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/JBHI.2021.3072644 | IEEE Journal of Biomedical and Health Informatics |
Keywords | DocType | Volume |
Sleep,Radar,Sleep apnea,Deep learning,Indexes,Brain modeling,Feature extraction | Journal | 25 |
Issue | ISSN | Citations |
10 | 2168-2194 | 0 |
PageRank | References | Authors |
0.34 | 0 | 8 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hyun Bin Kwon | 1 | 0 | 2.03 |
| Sang Ho Choi | 2 | 0 | 2.03 |
| Dongseok Lee | 3 | 2 | 1.74 |
| Dongyeon Son | 4 | 0 | 0.34 |
| Heenam Yoon | 5 | 0 | 1.01 |
| Mi Hyun Lee | 6 | 0 | 1.35 |
| Yu Jin Lee | 7 | 0 | 1.69 |
| Kwang Suk Park | 8 | 266 | 46.43 |