基于智能终端的血氧饱和度测量方法与系统研究

发布时间：2018-05-19 04:14

本文选题：血氧饱和度 + 智能终端　；参考：《湘潭大学》2017年硕士论文

【摘要】：血氧饱和度是人体的重要生命体征指标,其反应了人体的呼吸循环、心血管系统等生理状况,在临床救护中有着的重要地位。随着老龄化加剧和电子信息技术的快速发展,越来越多的人选择便携式的可穿戴设备供老年人检测血氧饱和度。然而普及这些可穿戴设备还存在一些问题,成本高,普通家庭难以支付;操作繁琐,不便于老年人使用;存在感较强,不利于携带。针对这些问题,本文研究了基于YUV光谱法的血氧饱和度测量方法,提出了基于亮度信号能量谱的血氧饱和度测量方法,实现了基于智能终端的血氧饱和度测量方法。主要成果如下:(1)对在混合光下测量血氧饱和度进行了理论分析。以含氧血红蛋白浓度和还原血红蛋白浓度为变化量,使用YUV视频中的U、V通道信号,推导出基于U、V通道信号映射氧合血红蛋白和还原血红蛋白的变化的理论方法。(2)根据(1)的理论结论,提出了基于YUV光谱的血氧饱和度测量方法,使用U、V通道的波谷及峰峰值为特征点,获得光强的变化,进而求得血氧饱和度。该方法测量数据与专业设备测量数据进行对比,结果显示准确性高,基本达到97%以上,验证了该方法的有效性。(3)根据亮度信号曲线与血液中含氧量的强相关关系,本文提出了基于亮度信号能量谱的血氧饱和度参数回归方法。根据心动周期中含氧血红蛋白和血流容积之间的关系,与含氧变化量和血液色差变化的关系,本文采用当前心动周期的血流视频中亮度信号的能量和亮度变化曲线的峰峰值为特征点,实时的计算出血氧饱和度。将该方法测量数据与专业设备测量数据进行对比,结果显示该方法稳定可靠。(4)结合基于YUV光谱法的血氧饱和度测量方法、基于亮度信号能量谱的血氧饱和度测量方法与智能手机,设计并实现了血氧饱和度检测系统,使得智能手机能够实时连续的测量出人体血氧饱和度值。另外血氧饱和度检测引擎中的核心算法能够跨平台使用,目前已在Android平台和iOS平台调用。此系统模块划分明确,并且把血氧饱和度检测引擎进行封装,可供第三方调用,并已经通过大量测试验证了该系统的实用性及准确度。
[Abstract]:Oxygen saturation is an important index of vital signs of human body, which reflects the physiological conditions of human body, such as respiration and circulation, cardiovascular system and so on, and plays an important role in clinical rescue. With the aggravation of aging and the rapid development of electronic information technology, more and more people choose portable wearable devices to detect oxygen saturation in the elderly. However, there are still some problems in popularizing these wearable devices, such as high cost, difficult for ordinary families to pay, cumbersome operation, inconvenient for the elderly to use, and strong sense of existence, which is not conducive to carrying. In order to solve these problems, this paper studies the measurement method of blood oxygen saturation based on YUV spectrum, proposes a method of measuring oxygen saturation based on luminance signal energy spectrum, and realizes the measurement method of blood oxygen saturation based on intelligent terminal. The main results are as follows: 1) the measurement of oxygen saturation in mixed light is theoretically analyzed. With the concentration of oxygenated hemoglobin and the concentration of reductive hemoglobin as the variable, the UGV channel signal in YUV video was used. The theoretical method of mapping the changes of oxygenated hemoglobin and reductive hemoglobin based on UGV channel signal is derived. According to the theoretical conclusion, a method of measuring oxygen saturation based on YUV spectrum is proposed. The variation of light intensity is obtained by using the peak and trough of the UGV channel as the characteristic points, and the saturation of oxygen is obtained. Compared with the measured data of professional equipment, the method has a high accuracy of over 97%. The validity of the method is verified by the strong correlation between the luminance signal curve and the oxygen content in the blood. In this paper, a regression method of oxygen saturation parameters based on luminance signal energy spectrum is proposed. According to the relationship between oxygenated hemoglobin and blood flow volume in cardiac cycle, and the change of oxygen content and color difference of blood, In this paper, the peak and peak of the luminance signal energy and luminance change curve in the blood flow video of the current cardiac cycle are used as the characteristic points to calculate the oxygen saturation of the bleeding in real time. The results show that the method is stable and reliable. It is combined with the method of measuring oxygen saturation based on YUV spectroscopy. The measurement method of blood oxygen saturation based on luminance signal energy spectrum and the smart phone are designed and implemented, which enables the smart phone to measure the human blood oxygen saturation in real time and continuously. In addition, the core algorithms in the oxygen saturation detection engine can be used across platforms, which have been called on Android and iOS platforms. The system module is clearly partitioned and encapsulated by the oxygen saturation detection engine, which can be called by a third party, and the practicability and accuracy of the system have been verified by a large number of tests.
【学位授予单位】：湘潭大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：R443;TN911.6

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