基于子带能量比的OSAS筛查

发布时间：2018-05-09 10:48

本文选题：阻塞性呼吸暂停 + 鼾声　；参考：《大连理工大学》2011年硕士论文

【摘要】：阻塞性睡眠呼吸暂停综合征(OSAS)是一种发病率较高且具有一定潜在威胁的疾病。医学上,多导睡眠仪(PSG)是公认的检测OSAS的黄金标准,已被广泛地应用到OSAS检测中,但其检测费用昂贵,对检测环境要求较高等不足极大地制约了PSG的普及化使用。完全依靠PSG对众多OSAS潜在人群进行逐一排查难度非常大,据不完全统计,有80%-90%的患者得不到及时诊治。因此,找到一种对患者睡眠干扰小,成本低,易于操作,适用于大量人群检测的筛查方法成为亟待解决的问题。 OSAS又称为“鼾症”,鼾声是OSAS最直接的临床表征,其中包含了反应上气道异常的足够信息。此外,鼾声的获取简便快捷。基于上述原因,利用鼾声特性实现OSAS检测成为本领域研究的热点。本文从实际角度出发,对有环境噪声影响下的鲁棒性OSAS检测方法问题进行研究,系统的分析了家庭环境中基于鼾声特性的OSAS检测方法并对不同患病等级的OSAS患者进行相应研究。本文的研究内容主要有以下几个方面： 1)提出子带能量比筛查方法。该方法可作为一种类似于常规体检的检测方法,对众多潜在OSAS人群进行筛查,然后将筛查呈阳性的患者(OSAS高危者)交由PSG进一步检查确诊,从而大大减小PSG检测的负荷。 2)因为患者患病程度越高,则上气道阻塞程度越严重,其频谱能量集中频段越高。本文利用子带能量比的思想进一步对不同患病等级的OSAS患者进行研究。 3)既然将本文方法定位为OSAS的筛查方法,方法的抗噪性能是一个至关重要的因素,本文验证了此方法在强噪声干扰情况下的筛查能力。实验结果表明本方法能较好的克服背景噪声对检测的影响,在家庭环境中亦能达到较高的检测精度,其灵敏度为92.8%,特异性为92.7%,已基本满足OSAS筛查的实际应用要求。此外对不同患病等级患者的研究今后利用鼾声特性区分不同患病程度提供一种有效的研究思路。
[Abstract]:Obstructive sleep apnea syndrome (OSAS) is a disease with high incidence and potential threat. In medicine, polysomnography (PSG) is recognized as the gold standard for the detection of OSAS, which has been widely used in OSAS detection. However, its high detection cost and high environmental requirements have greatly restricted the widespread use of PSG. It is very difficult to investigate the potential population of OSAS by PSG completely. According to incomplete statistics, 80% to 90% of the patients can not be diagnosed and treated in time. Therefore, it is an urgent problem to find a screening method for patients with low sleep disturbance, low cost, easy to operate and suitable for mass detection. OSAS, also known as snoring, is the most direct clinical manifestation of OSAS, which contains enough information to respond to upper airway abnormalities. In addition, snore acquisition is convenient and fast. For the above reasons, using snoring characteristics to realize OSAS detection has become a hotspot in this field. In this paper, the problem of robust OSAS detection method under the influence of environmental noise is studied from the practical point of view. The OSAS detection method based on snoring characteristics in the home environment is systematically analyzed and the corresponding research on OSAS patients with different disease grades is carried out. The main contents of this paper are as follows: 1) the subband energy ratio screening method is proposed. This method can be used as a kind of detection method similar to the routine physical examination to screen many potential OSAS population, and then to submit the screening positive patients to PSG for further diagnosis, thus greatly reducing the load of PSG detection. 2) the higher the degree of disease, the more severe the obstruction of upper airway and the higher the frequency band of concentrated spectrum energy. In this paper, subband energy ratio is used to further study OSAS patients with different disease grades. 3) since this method is positioned as the screening method of OSAS, the anti-noise performance of the method is a crucial factor, and this paper verifies the screening ability of this method in the case of strong noise interference. The experimental results show that this method can overcome the influence of background noise on the detection and achieve a high detection accuracy in the home environment. The sensitivity is 92.8 and the specificity is 92.70.This method has basically met the practical application requirements of OSAS screening. In addition, the study of patients with different disease grades provides an effective way to distinguish different degrees of disease by using snoring characteristics in the future.
【学位授予单位】：大连理工大学
【学位级别】：硕士
【学位授予年份】：2011
【分类号】：R766;R319

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