Tataraidze Alexander, Anishchenko Lesya, Korostovtseva Lyudmila, Kooij Bert Jan, Bochkarev Mikhail, Sviryaev Yurii
Annu Int Conf IEEE Eng Med Biol Soc. 2015;2015:362-5. doi: 10.1109/EMBC.2015.7318374.
This paper presents an algorithm for the detection of wakeful state, rapid eye movement sleep (REM) and non-REM sleep based on the analysis of respiratory movements acquired through a bioradar. We used the data from 29 subjects without sleep-related breathing disorders who underwent a polysomnography study at a sleep laboratory. A leave-one-subject-out cross-validation procedure was used for testing the classification performance. Cohen's kappa of 0.56 ± 0.16 and accuracy of 75.13 ± 9.81 % were achieved when compared to polysomnography results. The results of our work contribute to the development of home sleep monitoring systems.
本文提出了一种基于对通过生物雷达获取的呼吸运动进行分析来检测清醒状态、快速眼动睡眠（REM）和非快速眼动睡眠的算法。我们使用了来自29名无睡眠相关呼吸障碍受试者的数据，这些受试者在睡眠实验室进行了多导睡眠图研究。采用留一法交叉验证程序来测试分类性能。与多导睡眠图结果相比，得到的科恩kappa系数为0.56±0.16，准确率为75.13±9.81%。我们的工作成果有助于家庭睡眠监测系统的发展。
