多导睡眠图
睡眠(系统调用)
脑电图
听力学
金标准(测试)
计算机科学
睡眠阶段
语音识别
频道(广播)
医学
物理医学与康复
人工智能
精神科
电信
操作系统
内科学
作者
Ghena Hammour,Giuseppe Atzori,Ciro della Monica,Kiran Kumar Guruswamy Ravindran,Victoria L. Revell,Derk‐Jan Dijk,Danilo P. Mandic
标识
DOI:10.1109/embc40787.2023.10340253
摘要
Sleep disorders are a prevalent problem among older adults, yet obtaining an accurate and reliable assessment of sleep quality can be challenging. Traditional polysomnography (PSG) is the gold standard for sleep staging, but is obtrusive, expensive, and requires expert assistance. To this end, we propose a minimally invasive single-channel single ear-EEG automatic sleep staging method for older adults. The method employs features from the frequency, time, and structural complexity domains, which provide a robust classification of sleep stages from a standardised viscoelastic earpiece. Our method is verified on a dataset of older adults and achieves a kappa value of at least 0.61, indicating substantial agreement. This paves the way for a non-invasive, cost-effective, and portable alternative to traditional PSG for sleep staging.
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