A Novel Microwave Treatment for Sleep Disorders and Classification of Sleep Stages Using Multi-Scale Entropy.
A Novel Microwave Treatment for Sleep Disorders and Classification of Sleep Stages Using Multi-Scale Entropy.
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一种治疗睡眠障碍的新型微波疗法以及利用多尺度熵对睡眠阶段进行分类
DOI：
10.3390/e22030347
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发表时间：
2020-03-17
期刊：
影响因子：
--
通讯作者：
Zheng L
中科院分区：
文献类型：
--
作者：
Geng D;Yang D;Cai M;Zheng L
本研究的目的是开发一个非接触式睡眠阶段检测和睡眠障碍治疗的健康监测集成系统。因此，一种基于微波散射技术的脑活动检测方法代替头皮脑电图被开发用于评估睡眠阶段。首先，使用特定频率的微波穿透睡眠障碍患者的大脑功能部位，以改变大脑激活区域的发射频率，并分析和统计评估对睡眠改善的影响。然后，采用小波包算法对微波传输信号进行分解，从小波包系数中提取细化复合多尺度样本熵、细化复合多尺度波动色散熵和多元多尺度加权排列熵作为特征。最后，采用互信息-主成分分析特征选择方法优化特征集，并采用随机森林对睡眠阶段进行分类评价。结果表明，经过4次微波调制治疗后，睡眠效率不断提高，总体维持在80%以上，失眠率逐渐降低。四个睡眠阶段的总体分类准确率为86.4%。结果表明，具有一定频率的微波可以治疗睡眠障碍，并检测异常的大脑活动。因此，微波散射法在开发新的脑部疾病治疗、诊断和临床应用系统方面具有重要意义。
The aim of this study was to develop an integrated system of non-contact sleep stage detection and sleep disorder treatment for health monitoring. Hence, a method of brain activity detection based on microwave scattering technology instead of scalp electroencephalogram was developed to evaluate the sleep stage. First, microwaves at a specific frequency were used to penetrate the functional sites of the brain in patients with sleep disorders to change the firing frequency of the activated areas of the brain and analyze and evaluate statistically the effects on sleep improvement. Then, a wavelet packet algorithm was used to decompose the microwave transmission signal, the refined composite multiscale sample entropy, the refined composite multiscale fluctuation-based dispersion entropy and multivariate multiscale weighted permutation entropy were obtained as features from the wavelet packet coefficient. Finally, the mutual information-principal component analysis feature selection method was used to optimize the feature set and random forest was used to classify and evaluate the sleep stage. The results show that after four times of microwave modulation treatment, sleep efficiency improved continuously, the overall maintenance was above 80%, and the insomnia rate was reduced gradually. The overall classification accuracy of the four sleep stages was 86.4%. The results indicate that the microwaves with a certain frequency can treat sleep disorders and detect abnormal brain activity. Therefore, the microwave scattering method is of great significance in the development of a new brain disease treatment, diagnosis and clinical application system.
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影响因子：
4.3
作者：
Henz D;Schöllhorn WI;Poeggeler B
通讯作者：
Poeggeler B
影响因子：
2.9
作者：
Castroflorio, T.;Bargellini, A.;Manfredini, D.
通讯作者：
Manfredini, D.
DOI：
10.3390/e17031197
发表时间：
2015-03
期刊：
Entropy (Basel, Switzerland)
影响因子：
--
作者：
Costa MD;Goldberger AL
通讯作者：
Goldberger AL
影响因子：
4.4
作者：
Huber, R;Treyer, V;Achermann, P
通讯作者：
Achermann, P
影响因子：
6.1
作者：
Hariharan, M.;Sindhu, R.;Polat, Kemal
通讯作者：
Polat, Kemal