基于光电容积描记法的人体生理参数动态测量技术研究

发布时间：2018-02-20 00:04

本文关键词： 光电容积脉搏波 GM(1 1)模型脉搏波传导时间脉压差测量模型　出处：《中国科学技术大学》2017年博士论文　论文类型：学位论文

【摘要】：心血管疾病(Cardiovascular diseases,CVDs)通常由心脏、血管和血液运输系统发生异常导致,根据世界卫生组织(World Health Organization,WHO)2015年公布的数据显示,全球31%的人死于这类疾病,已经对人体健康造成严重威胁。实现动态监测心率、血压、血氧浓度和血液黏度等生理参数,对心血管类病症的诊治具有指导作用。目前传统的生理参数测量方法由于便携性差和测量舒适感低等限制,不能满足连续测量的需求。人体脉搏波是判断心血管系统健康与否的重要标准,生理参数测量模型的研究通常以脉搏波为研究对象。在众多脉搏波测量方法当中,光电测量法通过特定光谱获取人体容积脉搏波,测量过程重复性好,舒适度高,能够实现连续测量。本文重点对光电容积脉搏波(Photoplethysmography,PPG)和不同生理参数之间的关系进行深入研究,分别为心率、血压、血液黏度和血氧饱和度四种生理参数建立对应的测量模型,将测量结果以腕表的形式展现,具有很好的学术意义和市场应用价值。本文针对动态心率测量模型、舒张压测量模型和血液黏度测量模型的建模难度大,血氧饱和度测量模型定标环境复杂等问题,进行一系列的探索和研究。第一,选取523nm绿光、660nm红光和810nm红外的组合光谱作为探测光源,并在结构设计中引入"目"型槽结构消除环境光干扰,提高测量信号信噪比。将低功耗通信、微传感器技术,环境光学传感器、低功耗控制处理器和蓝牙模块集成在腕表上,实现硬件层面的信号放大和滤波,完成测量系统的电路设计与实现。第二,在传统广义形态学去除基线漂移算法的基础上进行改进,实现一种简化的基线漂移去除算法,以牺牲部分精度为代价实现快速、低功耗的信号处理过程,运算量降低了 4倍。第三,引入灰度预测GM(1,1)模型,对受到运动伪迹干扰导致失真的光电脉搏波信号进行补偿,结合加速度模型,建立动态心率测量模型,经过实验验证,94%以上的测量结果误差范围在+/-6之间;根据朗伯-比尔定律分析推导脉搏波形态特征和波形面积等参数与脉压差(收缩压-舒张压)之间的关系,成功推导得到脉压差的测量模型,间接实现舒张压的连续测量,通过实验得到测量误差在+/-10之间,符合美国医疗器械进步协会(The Association for the Advancement of Medical Instrumentation,AAMI)的规定;通过收缩压和舒张压计算得到关键参数K,带入经验公式完成血液黏度的测量,以开放型医学数据库MIMIC(Multiparameter IntelligentMonitoringinIntensiveCare)Ⅱ中的记录数据作为实验分析的对象,得到95%的测量值误差落在+/-0.5以内;根据修正的血氧饱和度测量公式,对未知系数进行定标,完成与定标环境相似条件下的血氧浓度的连续测量模型,经过实验验证得到测量结果的平均误差为0.076%。最后,通过手持设备与云服务平台建立联系,采集并存储多维度生理参数信息。不但实现生理参数的远程连续监测,而且为深度挖掘生理参数信息并实现健康趋势分析提供基础。
[Abstract]:Cardiovascular disease (Cardiovascular diseases, CVDs) is usually composed of heart, blood vessels and blood transport system abnormal cause, according to WHO (World Health Organization, WHO) data released in 2015, 31% of the world's people died from the disease, has been a serious threat to human health. To realize the dynamic monitoring of heart rate, blood pressure, blood oxygen and blood concentration the physiological parameters such as viscosity, diagnosis and treatment of cardiovascular diseases has a guiding role. The physiological parameters of the traditional measuring method due to poor portability and comfort and low measurement limit, can not meet the demand of continuous measurement. Human pulse wave is an important standard to judge whether a healthy cardiovascular system and the study of physiological parameters measurement models usually study in the pulse wave. In many measurement methods of pulse wave, the photoelectric measuring method to obtain the body volume pulse wave through specific spectrum measurement Good repeatability, high comfort, can realize continuous measurement. This paper focuses on the photoplethysmography (Photoplethysmography, PPG) was studied and the relationship between different physiological parameters, respectively. Heart rate, blood pressure, establish the corresponding measurement model of blood viscosity and oxygen saturation of four physiological parameters, the measurement results will be to watch show the form, has great academic significance and market value. In this paper the dynamic heart rate measurement model, the measurement model and the difficulty of modeling diastolic pressure and blood viscosity measurement model, oxygen saturation measurement problem of complex environment model, a series of exploration and research. First, select the 523nm green light spectrum combination 660nm red and 810nm infrared as the detection light source, and the introduction of "eye" type groove structure in the structural design to eliminate the interference of ambient light, increase the signal-to-noise ratio. The low power consumption. The letter, micro sensor technology, environmental optical sensors, low-power control processor and Bluetooth module integrated in watches, signal amplifying and filtering the hardware level, complete the circuit design and Realization of measurement system. In second, improvement in the traditional generalized morphology based algorithm to remove baseline drift, to achieve a simplified baseline drift the removal algorithm, to realize fast at the expense of accuracy, signal processing and low power consumption, the computation is decreased by 4 times. Third, the introduction of gray prediction GM (1,1) model, the motion artifacts caused by compensating the photoelectric pulse wave signal distortion, combined with the acceleration model, establish dynamic heart rate measurement model after experimental verification, measurement results more than 94% of the error in the range of +/-6; according to the Lambert Bill law analysis of pulse wave shape and wave area and the parameters such as pulse pressure (e.g. The systolic pressure and diastolic blood pressure) of the relationship between the pulse pressure measurement model is derived successfully obtained, indirect continuous measurement of diastolic blood pressure, measurement error between +/-10 through experiments, consistent with the United States Association of medical progress (The Association for the Advancement of Medical Instrumentation, AAMI) regulations; the systolic and diastolic blood pressure calculation get the key parameters of K, into the empirical formula of measurement of blood viscosity, with an open type medical database MIMIC (Multiparameter IntelligentMonitoringinIntensiveCare) in the recorded data as the object of experimental analysis, 95% measurement error falls within +/-0.5; according to the measurement of oxygen saturation formula, calibration of the unknown coefficient, continuous the measurement model and the calibration environment similar to the oxygen concentration conditions, the average error after experimental verification obtained measurement results For 0.076%., finally, through handheld devices and cloud service platform to establish links, collect and store multi-dimensional physiological parameter information. Not only achieve physiological parameters of remote continuous monitoring, but also provide a basis for deep excavation of physiological parameter information and health trend analysis.

【学位授予单位】：中国科学技术大学
【学位级别】：博士
【学位授予年份】：2017
【分类号】：R318;TP274

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