摘要
血氧饱和度是人体一项重要的生理参数 ,它的准确测量对于生理研究及医学应用都具有很重要的意义。对血氧饱和度的无创伤检验通常采用双波长法 ,在该方法中 ,血氧饱和度的计算是以识别脉搏波并提取其特征值为基础进行的。由于采用双波长法得到的脉搏波信噪比较低 ,且脉搏波又不具有明显的特征 (例如心电信号中有QRS波群 ) ,因此常用的脉搏波波形识别方法正确检出率不高 ,经常出现漏检或误检。本文提出利用时间序列建模的方法 ,建立心搏间期的自适应 AR模型 ,用微分阈值法的输出值同模型的估计值作比较 ,甄别出漏检或误检的脉搏波 ,从而大大提高了脉搏波的正确检出率。
Blood oxygen saturation is an important physiological parameter of human body. The accurate measurement of it is important to both physiological research and medical application. Dual wavelength method is widely adopted in noninvasive detection of blood oxygen saturation. In this method, the calculation of blood oxygen saturation is based on the identification of pulse waveform and the extraction of peak characteristic values. But the pulse waveform obtained from this method merely has distinctive features such as the QRS complexes in ECG, so the ratio of correct detection of pulse waveform is always low. An autoregressive model of heart beat intervals is developed. The output of the differential method is compared with that of the AR model so as to distinguish the false or missing detection. The ratio of correct detection is improved by the use of this method.
出处
《生物医学工程学杂志》
EI
CAS
CSCD
北大核心
2000年第3期285-287,共3页
Journal of Biomedical Engineering
关键词
血氧饱和度
脉搏波
自适应AR模型
脉搏血氧计
Blood oxygen saturation\ \ Pulse waveform\ \ Autoregressive model\ \ Oximetry
