摘要
为了提高动态光谱法信号的信噪比,从信号和噪声能量的角度分析了动态光谱法以往采用的频域数据处理方法优点和缺陷,研究了了典型动态光谱系统噪声来源、频谱特点及其对动态光谱法信噪比的影响;并由此提出了增加多次谐波分量计入动态光谱的方法,并通过实验方法研究了实验中不同对照组的动态光谱相关系数与谐波次数逐渐增加时的变化趋势、确定了计入动态光谱的最佳谐波次数。实验证明,伴随频域处理中引入的谐波次数的增加,源自两个不同个体的动态光谱数据的相关系数会先减小后增加;而源自同一个体不同部位的动态光谱数据则一直增大。当引入的谐波次数为5时,可以得到最佳信噪比。所得到的动态光谱可以更加准确地反应血液成分信息,从而使动态光谱法的信噪比最大。
The sources of noise in dynamic spectrum (DS) method and their corresponding frequency characteristic wereanalyzed in order to improve the signal to noise ratio (SNR) of DS method. The processes of DS data in frequency domain were reviewed by means of energy, then the harmonic waves of DS data were taken into account in the DS signal and some experiments were done to test whether the modified method works well. In addition, corresponding experiments were carried out to seek the relationship between the SNR and the number of harmonic waves, and to determine how many harmonic waves should be involved in order to get the best SNR in DS method. Results showed when harmonic waves were used in the method properly, the modified method can distinguish DS more precisely. And it was also showed that as the number of harmonic waves increased, the correlation coefficient of DS data from different volunteers became smaller at first and then bigger later, while the correlation coefficient of DS data from different sampling site of the same volunteer kept increasing all the time. When the number of harmonic waves was set to 5, the correlation coefficient of DS data from different volunteers goes from 0. 737 52 to 0. 736 76, while the one from the same volunteer goes from 0. 994 16 to 0. 995 33, which means the modified method can reflect the information about blood component more precisely than the old ones, and thus the SNR of DS reaches the highest.
出处
《光谱学与光谱分析》
SCIE
EI
CAS
CSCD
北大核心
2009年第10期2769-2772,共4页
Spectroscopy and Spectral Analysis
基金
国家自然科学基金项目(60174032
60674111)
辽宁省教育厅高等学校科学研究项目(20060379)资助
关键词
血液成分
无创检测
动态光谱法
频域处理
信噪比
Blood component
Non-invasive measurement
Dynamic spectrum method
Processing in frequency domain
SNR