An open-source, high-performance tool for automated sleep staging

被引:0
|
作者
Vallat, Raphael [1 ]
Walker, Matthew P. [1 ]
机构
[1] Univ Calif Berkeley, Dept Psychol, Ctr Human Sleep Sci, 3210 Tolman Hall, Berkeley, CA 94720 USA
来源
ELIFE | 2021年 / 10卷
关键词
automated sleep staging; machine-learning; sleep scoring; algorithm; YASA; NREM sleep; REM sleep; slow wave; sleep spindle; sleep apnea; Other; Human; METAANALYSIS; MEDICINE; EVENTS; BRAINS; APNEA; AGE;
D O I
10.7554/eLife.70092; 10.7554/eLife.70092.sa1; 10.7554/eLife.70092.sa2
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
The clinical and societal measurement of human sleep has increased exponentially in recent years. However, unlike other fields of medical analysis that have become highly automated, basic and clinical sleep research still relies on human visual scoring. Such human-based evaluations are time-consuming, tedious, and can be prone to subjective bias. Here, we describe a novel algorithm trained and validated on +30,000 hr of polysomnographic sleep recordings across heterogeneous populations around the world. This tool offers high sleep-staging accuracy that matches human scoring accuracy and interscorer agreement no matter the population kind. The software is designed to be especially easy to use, computationally low-demanding, open source, and free. Our hope is that this software facilitates the broad adoption of an industry-standard automated sleep staging software package.
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页数:24
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