【摘要】：光譜法無(wú)創(chuàng)檢測(cè)多成分介質(zhì)特定成分含量是檢測(cè)領(lǐng)域一直以來(lái)的研究熱點(diǎn),光在組織介質(zhì)中的傳輸和血液成分含量等組織成分檢測(cè)是生物醫(yī)學(xué)檢測(cè)領(lǐng)域的前沿?zé)狳c(diǎn)課題。對(duì)于組織中的光傳輸模型有待繼續(xù)完善,同時(shí)由于測(cè)量信號(hào)微弱、測(cè)量條件和個(gè)體差異等影響,近紅外光譜檢測(cè)進(jìn)入臨床實(shí)用具有很大的難度。本課題改進(jìn)的光在多成分介質(zhì)中的傳輸仿真模型以及相關(guān)的光譜測(cè)量數(shù)據(jù)處理的新方法有助于推進(jìn)光譜無(wú)創(chuàng)檢測(cè)技術(shù)的發(fā)展。本文綜述了光在組織中的傳輸?shù)难芯砍晒肮庾V測(cè)量各個(gè)環(huán)節(jié)中數(shù)據(jù)處理的相關(guān)方法,說(shuō)明了生物醫(yī)學(xué)光子學(xué)測(cè)量中需要解決的問(wèn)題:如組織光傳輸模型的精確構(gòu)建;組織吸收光譜的重疊性;測(cè)量環(huán)境的影響;光譜分析的模型的建立等。本文針對(duì)這些問(wèn)題的解決,做出的主要工作和創(chuàng)新點(diǎn)有:從蒙特卡羅模型及其光在組織中傳輸?shù)姆抡婺Ｐ统霭l(fā),針對(duì)傳統(tǒng)蒙特卡羅模型的應(yīng)用局限性,改進(jìn)了模型,進(jìn)行了光在多成分組織中傳輸?shù)难芯?并做了實(shí)際仿真實(shí)驗(yàn)驗(yàn)證和應(yīng)用舉例。這個(gè)模型后期可用于血液成分檢測(cè)的精確理論仿真。將經(jīng)驗(yàn)?zāi)B(tài)分解應(yīng)用于光譜測(cè)量數(shù)據(jù)預(yù)處理中,用于提高光譜測(cè)量的精度。通過(guò)介紹了動(dòng)態(tài)光譜血液成分消除個(gè)體差異的檢測(cè)原理和經(jīng)驗(yàn)?zāi)B(tài)分解(EMD)用于濾波的基本原理,將EMD引入光譜數(shù)據(jù)預(yù)處理過(guò)程中,用來(lái)提高光譜數(shù)據(jù)的性噪比;以動(dòng)態(tài)光譜無(wú)創(chuàng)測(cè)量血紅蛋白濃度中的應(yīng)用說(shuō)明了EMD在光譜測(cè)量數(shù)據(jù)處理中的可行性和有效性,為光譜數(shù)據(jù)處理及其產(chǎn)品化的設(shè)計(jì)應(yīng)用提供了新方法。將方差分析應(yīng)用于在光譜測(cè)量數(shù)據(jù)處理中,用來(lái)判定光譜數(shù)據(jù)及其模型建立的有效性。介紹了試驗(yàn)方差分析(ANOVA)的基本概念以及應(yīng)用于光譜數(shù)據(jù)中進(jìn)行有效性判定的原理和依據(jù),并以ANOVA的F值和p值作為評(píng)價(jià)指標(biāo),在不同噪聲水平下分析了光譜數(shù)據(jù)的仿真模型。以血氧測(cè)量作為一個(gè)應(yīng)用舉例,說(shuō)明了ANOVA應(yīng)用于血氧光譜無(wú)創(chuàng)測(cè)量中雙波長(zhǎng)選取的原理,并做了內(nèi)部機(jī)理分析。通過(guò)方差分析的方法可以判定噪聲水平及評(píng)價(jià)光譜數(shù)據(jù)處理分析方法的有效性,進(jìn)而能提高物質(zhì)成分定量分析的可靠性。
[Abstract]:Non-invasive detection of specific components in multi-component media by spectral method has been a hot research topic in the field of detection. The transmission of light in tissue media and the detection of tissue components such as blood content are hot topics in the field of biomedical detection. It is necessary to improve the optical transmission model in tissue. At the same time, it is very difficult for near infrared spectroscopy to be used in clinical practice because of the weak signal, measurement conditions and individual differences. The improved simulation model of optical transmission in multi-component medium and the new method of spectral measurement data processing are helpful to promote the development of spectral non-invasive detection technology. In this paper, the research results of optical transmission in tissue and the related methods of data processing in various links of spectral measurement are reviewed. The problems that need to be solved in biomedical photonics measurement are described, such as the accurate construction of tissue optical transmission model; Overlapping of tissue absorption spectrum; influence of measuring environment; establishment of spectral analysis model. In order to solve these problems, the main work and innovation of this paper are as follows: starting from Monte Carlo model and its simulation model of light transmission in organization, aiming at the limitation of application of traditional Monte Carlo model, this paper improves the model. The transmission of light in multi-component tissue is studied, and the simulation results and application examples are given. This model can be used for accurate theoretical simulation of blood component detection in later stage. The empirical mode decomposition (EMD) is applied to the pretreatment of spectral measurement data to improve the precision of spectral measurement. This paper introduces the detection principle of eliminating individual differences in dynamic spectral blood components and the basic principle of empirical mode decomposition (EMD) for filtering. EMD is introduced into the process of spectral data preprocessing to improve the ratio of spectral data to noise. The feasibility and effectiveness of EMD in spectral data processing are illustrated by the application of dynamic spectrum noninvasive measurement of hemoglobin concentration, which provides a new method for the design and application of spectral data processing and its production. Variance analysis is applied to spectral data processing to determine the validity of spectral data and its modeling. This paper introduces the basic concept of test variance analysis (ANOVA) and the principle and basis of validity evaluation applied in spectral data. The F value and p value of ANOVA are taken as evaluation indexes. The simulation model of spectral data is analyzed under different noise levels. Taking the measurement of oxygen in blood as an example, the principle of selecting two wavelengths in non-invasive measurement of blood oxygen spectrum by ANOVA is explained, and the internal mechanism is analyzed. The method of variance analysis can be used to judge the noise level and evaluate the validity of the spectral data processing and analysis method, thus improving the reliability of the quantitative analysis of material composition.
【學(xué)位授予單位】：天津大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類(lèi)號(hào)】：R318.51

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