基于SiPLS-BP模型的血红蛋白定量分析研究  

Quantitative Analysis of Hemoglobin Based on SiPLS⁃BP Model

作　　者：张朱珊莹 朱思聪 张献文 付保荣 李智 曹汇敏[1,2,3] 刘繄 Zhang Zhushanying;Zhu Sicong;Zhang Xianwen;Fu Baorong;Li Zhi;Cao Huimin;Liu Yi(College of Biomedical Engineering,South-Central Minzu University,Wuhan 430074,Hubei,China;Key Laboratory of Cognitive Science,State Ethnic Affairs Commission,Wuhan 430074,Hubei,China;Hubei Key Laboratory of Medical Information Analysis and Tumor Diagnosis&Treatment,Wuhan 430074,Hubei,China;Linyi GREPO Garden Machinery Co.,Ltd.,Linyi 276700,Shandong,China;Wuhan Great Sea Hi-Tech Co.,Ltd.,Wuhan 430223,Hubei,China;School of Mechanical and Electronic Engineering,Wuhan University of Technology,Wuhan 430070,Hubei,China)

机构地区：[1]中南民族大学生物医学工程学院,湖北武汉430074 [2]认知科学国家民委重点实验室,湖北武汉430074 [3]医学信息分析及肿瘤诊疗湖北省重点实验室,湖北武汉430074 [4]临沂格莱普园林机械有限公司,山东临沂276700 [5]武汉长海高新技术有限公司,湖北武汉430223 [6]武汉理工大学机电工程学院,湖北武汉430070

出　　处：《中国激光》2023年第21期166-172,共7页Chinese Journal of Lasers

基　　金：国家自然科学基金(61501526,61178087,32200560);湖北省重点研发计划(BZZ22002);中南民族大学中央高校基本科研业务费专项资金(CZQ22006)。

摘　　要：基于反向传播(BP)神经网络模型结合联合区间等间隔偏最小二乘法(SiPLS),设计了SiPLS-BP模型定量分析复杂背景下血红蛋白含量。以186个不同浓度血红蛋白的血液样本和39个不同浓度的血红蛋白仿体溶液样本的近红外光谱数据为研究对象,优选出最佳的数据集划分方法、最佳划分比例和最佳预处理方法,利用SiPLS优选波段,构建SiPLS、SiPLS-BP、全谱偏最小二乘法(PLS)和全谱BP四种定量分析模型,并进行分析对比。实验结果表明:两种样本的最佳定量分析模型均为SiPLS-BP。即使采用相同的特征波长优选方法,每个模型优选的波段也并不完全相同。对于背景复杂、样本差异性较大的混合溶液和血液,SiPLS-BP模型具有更好的预测效果,能更准确地定量分析血红蛋白浓度。研究结果为复杂背景下的血红蛋白定量分析提供了参考。Objective Hemoglobin is a special protein responsible for transporting oxygen in red blood cells.Hemoglobin concentration is an important parameter in routine blood tests and an important index for the diagnosis of anemia and other blood diseases in clinical medicine.Changes in hemoglobin concentration can directly reflect changes in human health;therefore,it is important to detect the hemoglobin concentration in the human body accurately for the diagnosis of many blood diseases.Current clinical medical treatments mainly rely on chemical reagents to detect hemoglobin concentrations,resulting in high detection costs,long analysis time,complicated operations,and trauma to the human body.Infrared spectroscopy can detect hemoglobin concentrations without reagents efficiently and noninvasively.However,the blood composition is complex,and the spectral overlap is serious.This complex background information makes it difficult to construct a high-precision quantitative hemoglobin analysis model.The model developed in this study is based on a backpropagation(BP)neural-network model combined with synergy interval partial least squares(SiPLS).This model uses SiPLS to eliminate most of the interference information,accelerates the modeling speed,and can achieve high-precision quantification of hemoglobin concentration in a complex background.It is believed that the proposed model can be helpful in promoting noninvasive detection of hemoglobin.Methods In this study,the near-infrared spectral data of 186 blood samples with different concentrations of hemoglobin and 39 nearinfrared spectral data of hemoglobin imitation solution samples with different concentrations under a complex background are used as the research objects.The best dataset division method,best division ratio,and best pretreatment method are selected.Four quantitative analysis models[SiPLS,SiPLS-BP,full-spectrum partial least squares(PLS),and full-spectrum BP]are constructed using SiPLS preferred bands,analyzed,and compared.Results and Discussions The best quanti

关 键 词：光谱学 近红外光谱 特征波长优选 血红蛋白 反向传播神经网络 

分 类 号：O657.31[理学—分析化学] X832[理学—化学]