微动敏感床垫式睡眠监测系统相关生理参数提取

发布时间：2018-05-02 02:52

本文选题：微动敏感床垫式睡眠监测系统 + 睡眠呼吸暂停低通气综合症　；参考：《山东大学》2010年硕士论文

【摘要】： 睡眠是人体重要的生理状态,睡眠质量对人的健康至关重要。近20年来医学研究已经证明,现代人类的许多重大疾病,如高血压、冠心病、心律失常、糖尿病、心脑血管意外,以及精神心理疾患等,往往与睡眠中常发生的睡眠呼吸暂停综合症有关。因此,睡眠监测技术已成为现代医学诊断中不可缺少的内容。目前临床睡眠分析的主要手段是多导睡眠图(polysomnography, PSG),用仪器记录被测者整晚的脑电、眼动电和颏肌电等生理参数,计算机依据国际标准进行自动睡眠分期,几十年来PSG保持着睡眠分期金标准的地位。但PSG至少要在身上粘贴10枚以上电极,给被测者带来一定的生理心理负荷。微动敏感床垫式睡眠监测系统(Micro-movement Sensitive Mattress Sleep Monitoring System, MSMSMS)基本无需在体表粘贴电极即可记录被测者的躯体活动、呼吸活动、心率等情况,还可实现对睡眠呼吸暂停综合症进行诊断,获得被测者的整晚睡眠结构图等功能,是一种无电极,无负荷的睡眠监测方法。具有不影响自然睡眠、可靠性较好、自动分析、同时检测分析多床位等优点,有利于将睡眠监测普及到更广阔的人群,也有助于拓展与睡眠有关的生理和医学研究,在睡眠医学日益受到重视的今天,具有很大的应用潜力。本系统适用于常规、长期或集体睡眠监测,如用于监测执行特殊任务人群(如飞行员、火车司机、运动员等)的睡眠质量。新一代16位A／D微动敏感床垫式睡眠监测系统,通过硬件上的改进,扩大了信号的动态范围,具有之前系统无可比拟的优点。新系统直接从硬件中输出原始信号,所有的信号处理均在软件中进行。而本文的工作则是针对硬件输出原始信号而展开,首先对原始信号进行分离,进而提取床垫相关生理信息,包括被测者的在床状态(即离床)、体动、呼吸率、心率。从而为之后的睡眠分期和睡眠呼吸事件的判定提供依据。本文的主要工作为： (1)针对16位A／D的新一代床垫式睡眠监测系统,提出了合适的床垫信号预处理方法,分离出胸冲击、呼吸波和腿冲击,其中,呼吸波和腿冲击的分离相对简单。而由于床垫信号的特点,胸冲击的分离过程相对困难。本文利用软件处理信号的灵活性,将数字信号处理方法和小波变换相结合对原始信号进行分离,所得结果,能充分显示出所需信号的特征点,为准确提取床垫系统相关生理信息打下基础。 (2)针对原始信号和分离出的信号,提取离床、体动、呼吸率、心率。其中离床、体动、呼吸率在以前的床垫系统中已经使用。本文主要是针对新一代床垫系统的信号特点,提出了相对简单实用的算法,加快软件系统的运行速度。床垫心率为该睡眠监测系统第一次使用,该参数的使用,使得床垫监测摆脱了脉搏检测记录仪对被测者的束缚变为现实,真正实现了睡眠的无负荷监测。但由于被测者的睡姿、体重等各种原因,使得胸部冲击信号、腿部冲击信号表现形式不一,故提取床垫心率是本工作的重点和难点。而本研究所用算法通过大量实验验证,证明其准确性高,基本能反映出被测者整夜的心率变化,目前该算法已经嵌入床垫系统。 (3)研究了利用床垫心率提取SAHS病人的睡眠时相信息。通过去趋势波动分析(DFA)计算SAHS病人的床垫心率在各睡眠阶段的标度指数,结果显示,SAHS患者各个睡眠阶段的标度指数具有明显差异,与健康者之间也有不同。该结果为基于心率变异性对SAHS患者进行睡眠分期以及SAHS患者的判定提供了依据。
[Abstract]:Sleep is the important physiological state of the human body. The quality of sleep is crucial to human health. In recent 20 years, medical research has proved that many of the major diseases of modern human beings, such as hypertension, coronary heart disease, arrhythmia, diabetes, cardiovascular and cerebrovascular accidents, and mental disorders, often occur with sleep apnea syndrome often occurring in sleep. Therefore, sleep monitoring technology has become an indispensable part of modern medical diagnosis.
At present, the main means of clinical sleep analysis is polysomnography (PSG). The physiological parameters such as brain electricity, eye movement and mental electromyography are recorded by the instrument for the whole night, and the computer is automatically sleep staging according to the international standard. For decades, PSG maintains the status of the standard of sleep staging. At least, PSG has to paste 10 pieces on the body. The above electrodes give some physiological and psychological loads to the subjects.
The Micro-movement Sensitive Mattress Sleep Monitoring System (MSMSMS) basically does not need to paste electrode on the body surface to record the body activity, respiratory activity, heart rate and so on. It can also make a diagnosis of sleep apnea syndrome and get the whole night sleep structure map of the subjects. It is an electrode free, no load sleep monitoring method. It has the advantages of not affecting natural sleep, good reliability, automatic analysis, and detection and analysis of multiple beds. It is beneficial to popularize sleep monitoring to a wider population, and also help to expand the physiological and medical research related to sleep. It is becoming more and more important in sleep medicine. Today, it has great potential for application. This system is suitable for routine, long-term or collective sleep monitoring, such as monitoring the quality of sleep for special task groups (such as pilots, train drivers, athletes, etc.).
The new generation of 16 bit A / D microdynamic mattress sleep monitoring system has expanded the dynamic range of the signal through the improvement of hardware. It has the unparalleled advantages of the previous system. The new system directly outputs the original signal from the hardware and all the signal processing is carried out in the software. The work of this paper is to output the original signal for the hardware. First, the original signal was separated and the mattress related physiological information was extracted, including the bed state (that is, the bed), the body movement, the respiration rate and the heart rate, which provided the basis for the subsequent sleep stages and the sleep breathing events.
(1) according to the new generation of mattress sleep monitoring system of 16 bit A / D, a suitable mattress signal pretreatment method is put forward to separate the chest shock, respiratory wave and leg impact. Among them, the separation of the respiratory wave and the leg impact is relatively simple. It is flexible to separate the original signal by combining the digital signal processing method with the wavelet transform. The results can fully display the characteristic points of the required signal and lay the foundation for the accurate extraction of the related physiological information of the mattress system.
(2) to extract off bed, body movement, respiration rate and heart rate for the original signal and separated signals, which has been used in the former mattress system. This paper mainly aims at the signal characteristics of the new generation mattress system, and puts forward a relatively simple and practical algorithm to speed up the running speed of the software system. The heart rate of the mattress is the sleep. The sleep monitoring system is used for the first time. The use of this parameter makes the mattress monitoring get rid of the constraints of the pulse detection recorder to the reality of the measured person. It really realizes the non load monitoring of sleep. But because of the sleeping posture, weight and other reasons of the subjects, the chest impact letter number and the leg impact signal are different, so the mattress is extracted. Heart rate is the key and difficult point of this work. And the algorithm used in this study is verified by a large number of experiments to prove its high accuracy, which can basically reflect the heart rate changes all night, and the algorithm has been embedded in the mattress system at present.
(3) the sleep phase information of SAHS patients was extracted with the heart rate of the mattress. The scale index of the mattress heart rate of SAHS patients at each sleep stage was calculated by detrending fluctuation analysis (DFA). The results showed that the scale index of each sleep stage of SAHS patients was significantly different, and was different from those of the healthy people. The result was based on the heart rate change. Heterosexual provides a basis for sleep stages of SAHS patients and SAHS patients.

【学位授予单位】：山东大学
【学位级别】：硕士
【学位授予年份】：2010
【分类号】：R766

【引证文献】