本文關(guān)鍵詞：家用睡眠呼吸暫停綜合征初篩方法研究　出處：《天津工業(yè)大學(xué)》2017年碩士論文　論文類型：學(xué)位論文

  更多相關(guān)文章： 睡眠呼吸暫停綜合征 單導(dǎo)心電 血氧飽和度 EDR

【摘要】：經(jīng)濟(jì)社會快速發(fā)展,科學(xué)技術(shù)飛速進(jìn)步,人們的工作壓力越來越大。工作強(qiáng)度以及工作壓力的加大使得人們的睡眠休息不能得到充分保障,與睡眠相關(guān)的疾病成上升趨勢,其中對于睡眠呼吸暫停綜合癥的診斷與治療成為當(dāng)下的熱點(diǎn)。目前臨床上對于睡眠呼吸暫停綜合征檢測的金標(biāo)準(zhǔn)是通過睡眠呼吸監(jiān)測儀對受測者安靜睡眠狀態(tài)下的心電、眼電、鼾聲、血氧、肌電等多項(xiàng)生理參數(shù)進(jìn)行長時(shí)間監(jiān)測,檢測成本昂貴,檢測時(shí)間長,測量及處理的數(shù)據(jù)量龐大,需要專門的睡眠檢測環(huán)境及專業(yè)的人員進(jìn)行睡眠數(shù)據(jù)的分析處理,并且由于幾乎密布全身的傳感器的存在,也給患者帶來了不適感。針對上述現(xiàn)狀,本文通過采用與睡眠呼吸暫停綜合征的發(fā)生密切相關(guān)的呼吸及血氧飽和度兩個(gè)關(guān)鍵因素并以BMI與打鼾為參考進(jìn)行家庭環(huán)境下睡眠呼吸暫停綜合癥的初篩,從而解決目前臨床上金標(biāo)準(zhǔn)檢測的不便。設(shè)計(jì)了單導(dǎo)心電采集端和血氧飽和度采集端。首先利用睡眠呼吸提取算法從受測者的單導(dǎo)心電中提取出初篩模板,然后通過透射式血氧儀對受測者的血氧飽和度進(jìn)行檢測,最后將提取到的初篩曲線、血氧飽和度、BMI、打鼾進(jìn)行融合,通過數(shù)據(jù)融合的方法達(dá)到對睡眠呼吸暫停綜合征的初篩。最后,完成了對家用睡眠呼吸暫停綜合征初篩系統(tǒng)的整體測試和調(diào)試。結(jié)果表明:呼吸信息提取算法準(zhǔn)確有效,可以從單導(dǎo)心電中很好的提取出呼吸事件,所提取的呼吸信息與從呼吸傳感器測得的呼吸波曲線在判斷受測者呼吸正常與否上達(dá)到了很好的一致性,從而可以達(dá)到對受測者呼吸的初步診斷而又避免對受測者造成不適感;透射式血氧可以對受測者的血氧飽和度進(jìn)行準(zhǔn)確、實(shí)時(shí)的測量,同時(shí)可以對測量時(shí)的松緊程度進(jìn)行調(diào)節(jié)。通過對160種判定條件的多次重復(fù)實(shí)驗(yàn)證明本系統(tǒng)整體運(yùn)行穩(wěn)定,測試結(jié)果準(zhǔn)確,可以對睡眠呼吸暫停綜合征進(jìn)行很好的初篩,適合家庭環(huán)境下使用,從而有助于睡眠呼吸暫停綜合征的及時(shí)發(fā)現(xiàn)與進(jìn)一步診療。
[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.
【學(xué)位授予單位】：天津工業(yè)大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：R766

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