摘要
为了实现血液成分的无创检测,利用动态光谱指端透射法进行了人体血红蛋白浓度无创测量的研究。对34名健康志愿者进行了在体测量动态光谱和抽血分析血红蛋白含量,在验证了动态光谱的可靠性的基础上,选用BP神经网络对获取的动态光谱数据和血红蛋白浓度实测值进行建模分析,从34个样本中抽取19个作为校正集,另外15个作为预测集,得到校正集和预测集的相关系数分别为0.983 1和0.936 5,预测集的相对误差最大为7.5%,平均相对误差为3.04%,满足临床应用对血红蛋白测量精度的要求。结果表明:动态光谱法可以有效的克服测量位置等测量条件对光谱测量的影响,较准确地进行人体血红蛋白浓度的测量,是一种比较好的血液成分无创测量方法。
For non-invasively measurement of the components of human blood, dynamic spectrum method was used to measure hemoglobin concentration of volunteers for the first time. In-vivo measurements were carried out on 34 healthy volunteers, and their dynamic spectra were collected. To ensure the dynamic spectrum data to be valid, a number of experiments were carried out on the dynamic spectrum data. BP artificial neural network was used to establish the calibration model of subjects＇ hemoglobin concentration values against dynamic spectrum data. Among 34 swatches, 19 swatches were taken as calibration set and the other 15 as prediction set. For calibration set and prediction set, the correlation coefficient was 0. 983 1 and 0. 936 5 respectively. The biggest relative error of prediction is 7.5 %, and the average relative error is 3. 04%. The accuracy of measurement results can satisfy the demand for clinical application. Measurement results show that the influences of measuring conditions on spectra can be decreased effectively by dynamic spectrum method and this method can be applied to accurate non-invasive measurement of human hemoglobin concentration. It can be a good method for non-invasive blood analysis.
出处
《光谱学与光谱分析》
SCIE
EI
CAS
CSCD
北大核心
2010年第1期150-153,共4页
Spectroscopy and Spectral Analysis
基金
国家自然科学基金项目(60174032,60674111)资助
关键词
动态光谱
血红蛋白浓度
无创测量
人工神经网络
Dynamic spectrum~ Hemoglobin concentration Non-invasive measurement
Artificial neural network
