基于脉搏光谱分形算法的血氧测量研究

脉搏光谱测量方法被普遍用于临床的血氧饱和度的监测，由于检测时低血氧和血氧波动将改变血红蛋白的吸光系数，会造成脉搏光谱测量的误差。本文针对血氧波动、外界环境等产生的噪声干扰问题，采用脉搏光谱分形法去除光谱信号中的噪声干扰，利用自适应校正后的准理想光谱计算血氧饱和度，使得血氧饱和度的值更为精确，从而进一步保证其他生理参数的准确计算。实验结果表明，该方法有效提高了血氧饱和度的检测精度，为抗血氧干扰的无创肝储备功能的检测提供理论依据和实用方法。

Research on Oximetry Based on Pulse Spectrum Fractal Algorithm

The measurement method of pulse spectrum is widely used in clinical monitoring of oxygen saturation. The extinction coefficient of hemoglobin will be changed by the low blood oxygen or fluctuation during the detection,so the small variations would cause the measurement error. In this paper,the problems of noise interference arising from blood oxygen fluctuation or the external environment are mainly focused on,so the accurate measurement method of oxygen sat-uration based on pulse spectrum fractal algorithm is developed. The noise is removed from the spectrum signal,and the oxygen saturation is calculated by using the adaptive correction quasi-ideal spectrum. Thus, the oxygen saturation value is more precise and the accurate calculation of other physiological parameters is further ensured. The experimental results show that the method is effective to improve the detection accuracy of oxygen saturation. A theoretical basis and practical measurement method are provided for the noninvasive liver reserve function detection of anti-interference blood oxygen.