提高DS法无创血液成分检测信噪比的方法与分析  被引量:2

The Analysis for Improving the SNR of Blood Components Noninvasive Measurement with DS Method

在线阅读下载全文

作  者:李刚[1] 王慧泉[1] 赵喆[1] 林凌[1] 张宝菊[2] 吴晓荣 

机构地区:[1]天津大学精密测试技术及仪器国家重点实验室,天津300072 [2]天津师范大学物理与电子信息学院,天津300387

出  处:《光谱学与光谱分析》2012年第8期2290-2294,共5页Spectroscopy and Spectral Analysis

基  金:国家自然科学基金项目(30973964);天津市应用基础及前沿技术研究计划项目(11JCZDJC17100);天津市科技计划项目:科技型中小企业创新基金项目(10ZXCXSY10400)资助

摘  要:为了提高血液成分无创检测精度,增加预测模型稳定性,对基于动态光谱(dynamic spectrum,DS)的血液成分无创检测仪器和预处理方法进行了定量信噪比分析与实验验证。在DS数据提取时加入boxcar积分器、降低波长分辨率、均衡DS信噪比和剔除粗大误差等预处理方法,使得各个波段上的DS数据信噪比得以均衡,提高了DS的总体信噪比。利用DS数据采集平台对两名志愿者连续多次测试,同一个体的DS数据相关度分别从0.934和0.953分布提高到了0.991和0.987,而不同个体间DS数据相关度与同一个体DS数据相关度差距也显著增加,结果表明这些方法可以提高DS数据信噪比。无创血液成分检测信噪比定量分析可有效指导预处理方法的选择,为无创血液成分检测的临床应用创造了条件。In order to increase the accuracy of blood components measurement and enhance the stability of prediction model, the quantitative signal-noise-ratio (SNR) analysis of measuring instruments based on dynamic spectrum (DS) and preprocessing method was conducted. The SNR of DS is increased after adding boxcar integrator, decreasing wavelength revolution, balancing the DS's SNR and excluding gross errors in preprocessing according to experiment results. Two volunteers were tested continu- ously for many times using the DS data acquiring system. The correlation coefficients of the each volunteer's DS data was in- creased from 0. 934 and 0. 953 to 0. 991 and 0. 987, respectively. Moreover, the gap between the correlation coefficient of the same volunteer's DS and different volunteers' DS is increased too, which shows that the SNR can be improved by these methods. The quantitative SNR analysis can guide the way of choosing preprocessing method efficiently, which will create the condition for clinical application of the blood components noninvasive measurement.

关 键 词:无创 血液成分 信噪比 

分 类 号:O657.3[理学—分析化学]

 

参考文献:

正在载入数据...

 

二级参考文献:

正在载入数据...

 

耦合文献:

正在载入数据...

 

引证文献:

正在载入数据...

 

二级引证文献:

正在载入数据...

 

同被引文献:

正在载入数据...

 

相关期刊文献:

正在载入数据...

相关的主题
相关的作者对象
相关的机构对象