【作者】 周青；

【导师】 林勇；

【作者基本信息】 山东大学 ， 生物医学工程， 2011， 硕士

【摘要】 氧气供给是否正常关系到人体能否进行正常的新陈代谢,而血氧饱和度是反映供氧状态的一个重要指标。脉搏血氧饱和度检测仪可以实现血氧饱和度的无创检测,在临床和家庭保健中广泛使用。本论文针对这类检测仪器目前存在的模拟电路复杂,稳定性差,运动伪差干扰难以去除的缺陷,提出主要采用软件方法实现脉搏波信号的预处理和特征参数的提取,综合引入形态学方法,平移不变量提升小波阂值法和经验模态分解方法实现了强噪声背景下脉搏波信号的提取,提高了血氧饱和度检测的准确性。论文主要包含了以下几个方面：(1)设计并完成了以ATmega8单片机作为核心的双波长指端透射光硬件检测电路。这款单片机I/O口可以输出、吸收20mA的电流,能够直接驱动双波长LED,同时其内部集成的10-bit ADC也使模拟电路的设计大为简化。(2)提出将信号传送到上位机用软件方法实现强噪声干扰下脉搏波信号的提取。首次采用形态学方法和平移不变量提升小波阈值法级联的综合滤波算法实现脉搏波信号的基线矫正和高频干扰去除。综合方法将形态学滤波器在滤除基线漂移方面运算量小,速度快的优点和平移不变量提升小波阈值去噪法优良的高频消噪性能结合起来,在低信噪比环境下有效提取了脉搏波信号。(3)采用经验模态分解方法在很大程度上去除了脉搏血氧饱和度检测中难以去除的运动伪差,矫正了运动伪差导致的波形畸变。用提升小波模极大值法代替传统的差分法提取预处理后脉搏波信号的特征点,即使在含有噪声干扰的情况下也能实现特征点的准确提取,并且提升小波的引入使得传统的模极大值法分解更为简单快速。(4)利用血氧饱和度的定义和提取出的脉搏波信号的特征参数计算出脉搏血氧饱和度,实现了对人体脉搏血氧饱和度的实时测量和连续监测。论文最后对全文的工作和存在的不足进行了总结,并对下一步的研究工作进行了展望。更多还原

【Abstract】 The oxygen supply affects the metabolism in human body, and oxygen saturation is an important index of evaluating oxygen supply condition. Transmission pulse oximeter has been used widely in clinical and family health care which can realize non-invasive oxygen saturation detection. Traditional oximeter applies complex analogue electric circuits to realize signal processing, this leading to poor stability. Moreover, it is hard to eliminate the motion artifact. To solve these problems, this thesis proposes using software method to process pulse signal and extract its characteristic parameters. By implying morphology method, translation invariant lifting wavelet method, and empirical mode decomposition method, weak pulse signal submerged in noise is extracted. This improves detection accuracy. The main content on the paper is summarized as follows:Firstly, the hardware platform is designed and completed to detect dual-wavelength finger transmitted light. This platform is based on the ATmega8 MCU. The I/O ports of this MCU have nearly 20mA current driving capability which can activate the dual-wavelength light source directly. The internal integrated 10-bit analog-to-digital converter (ADC) in MCU also simplifies the circuit design.Secondly, we transmit the signal to computer in order to process pulse signal with software method. This paper combines the morphological filter with the translation invariant lifting wavelet method to remove baseline drift and high frequency noise in pulse wave. The comprehensive method combines their good merits. Morphological filter has small computational work and a high processing speed. Its performance in removing baseline drift is nearly perfect. Translation invariant lifting wavelet method has excellent performance in high-frequency noise removing. Comprehensive method can extract pulse wave signals excellently when the signal-to-noise ratio is quite low.Thirdly, the empirical mode decomposition method is used to eliminate the motion artifact and correct waveform distortion. Then the lifting wavelet modulus maxima method is used to realize feature point detection of the pretreated pulse signal. Compared to the traditional wavelet modulus maxima method, it achieves similar examination precision with less computation and high efficiency. Finally, pulse oxygen saturation is calculated on the basis of its definition and pulse signal’s characteristic parameters. The result shows this system has achieved real time pulse oxygen saturation measurement and continuous monitoring of human body.A summation is made to generalize the work and deficiency in this paper. Suggestions are proposed for the further research and improvements.更多还原