家用睡眠呼吸暂停综合征初筛方法研究

发布时间：2018-01-05 17:38

本文关键词：家用睡眠呼吸暂停综合征初筛方法研究　出处：《天津工业大学》2017年硕士论文　论文类型：学位论文

【摘要】：经济社会快速发展,科学技术飞速进步,人们的工作压力越来越大。工作强度以及工作压力的加大使得人们的睡眠休息不能得到充分保障,与睡眠相关的疾病成上升趋势,其中对于睡眠呼吸暂停综合症的诊断与治疗成为当下的热点。目前临床上对于睡眠呼吸暂停综合征检测的金标准是通过睡眠呼吸监测仪对受测者安静睡眠状态下的心电、眼电、鼾声、血氧、肌电等多项生理参数进行长时间监测,检测成本昂贵,检测时间长,测量及处理的数据量庞大,需要专门的睡眠检测环境及专业的人员进行睡眠数据的分析处理,并且由于几乎密布全身的传感器的存在,也给患者带来了不适感。针对上述现状,本文通过采用与睡眠呼吸暂停综合征的发生密切相关的呼吸及血氧饱和度两个关键因素并以BMI与打鼾为参考进行家庭环境下睡眠呼吸暂停综合症的初筛,从而解决目前临床上金标准检测的不便。设计了单导心电采集端和血氧饱和度采集端。首先利用睡眠呼吸提取算法从受测者的单导心电中提取出初筛模板,然后通过透射式血氧仪对受测者的血氧饱和度进行检测,最后将提取到的初筛曲线、血氧饱和度、BMI、打鼾进行融合,通过数据融合的方法达到对睡眠呼吸暂停综合征的初筛。最后,完成了对家用睡眠呼吸暂停综合征初筛系统的整体测试和调试。结果表明:呼吸信息提取算法准确有效,可以从单导心电中很好的提取出呼吸事件,所提取的呼吸信息与从呼吸传感器测得的呼吸波曲线在判断受测者呼吸正常与否上达到了很好的一致性,从而可以达到对受测者呼吸的初步诊断而又避免对受测者造成不适感;透射式血氧可以对受测者的血氧饱和度进行准确、实时的测量,同时可以对测量时的松紧程度进行调节。通过对160种判定条件的多次重复实验证明本系统整体运行稳定,测试结果准确,可以对睡眠呼吸暂停综合征进行很好的初筛,适合家庭环境下使用,从而有助于睡眠呼吸暂停综合征的及时发现与进一步诊疗。
[Abstract]:With the rapid development of economy and society, the rapid progress of science and technology, people's work pressure is increasing. The increase of work intensity and work pressure makes people's sleep rest can not be fully protected. Sleep-related diseases are on the rise. The diagnosis and treatment of sleep apnea syndrome has become a hot spot. At present, the golden standard for the detection of sleep apnea syndrome is to use sleep apnea monitor to test the subjects under the condition of quiet sleep. Michael's ECG. Many physiological parameters, such as eye electricity, snoring, blood oxygen, myoelectricity and so on, are monitored for a long time. The cost of detection is expensive, the detection time is long, and the amount of data measured and processed is huge. Need special sleep detection environment and professional personnel to analyze and process sleep data, and because of almost the presence of sensors throughout the body, it also brings discomfort to patients. The primary screening of sleep apnea syndrome in home environment was carried out by using two key factors of breathing and oxygen saturation closely related to the occurrence of sleep apnea syndrome and taking BMI and snoring as reference. In order to solve the inconvenience of the current clinical gold standard detection, we designed the sampling end of single conduction ECG and blood oxygen saturation. Firstly, the template was extracted from the single conductance ECG by using sleep breathing extraction algorithm. Then the blood oxygen saturation of the subjects was detected by transmission oxygen analyzer. Finally, the first screen curve, blood oxygen saturation (BMIs), and snoring were fused. Through the data fusion method to achieve the sleep apnea syndrome screening. Finally. The whole test and debugging of the first screen system of household sleep apnea syndrome were completed. The results show that the respiratory information extraction algorithm is accurate and effective, and can extract respiratory events from single conduction ECG very well. The obtained respiration information is in good agreement with the respiratory wave curve measured from the respiratory sensor in judging whether the subjects are breathing normally or not. Thus, the preliminary diagnosis of the subjects' breathing can be achieved and the discomfort of the subjects can be avoided. Transmission oxygen can be used to measure the oxygen saturation accurately and in real time. At the same time, we can adjust the degree of tightness in the measurement. Through repeated experiments of 160 kinds of judging conditions, it is proved that the system runs stably as a whole and the test results are accurate. Sleep apnea syndrome can be well screened, suitable for use in the home environment, thus contributing to the timely discovery of sleep apnea syndrome and further diagnosis and treatment.
【学位授予单位】：天津工业大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：R766

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