基于智能手机的LSPR生化传感检测系统研究与实现

发布时间：2018-03-07 19:03

本文选题：智能手机　切入点：LSPR　出处：《中央民族大学》2016年硕士论文　论文类型：学位论文

【摘要】：面对癌症患者早期诊断的困境时,LSPR检测技术凭借其界面效应、无标记、实时和无污染检测的优势,得到了广泛关注。与此同时,随着在线医疗、家庭诊断和快速检测等移动医疗理念的兴起,智能手机逐渐发展成LSPR生化传感检测的一个有效平台。近期,印度科研工作者首次推出了一款基于智能手机的LSPR生化传感检测系统,即通过智能手机图像传感器获取LSPR检测数据。虽然,该系统能满足癌症早期检测与移动性的基本需求;但是处理比较耗时,并且检测精度不高。于是,本文提出了一套智能手机便携式LSPR生化传感检测方案。首先利用专业光谱仪获取高精度的检测数据,然后再通过智能手机USB接口迅速采集光谱数据,最后及时准确地展示LSPR检测结果。本方案在保证LSPR生化检测的准确性与便捷性前提下,不仅较好地解决了上述问题,而且提供了一个良好的Android应用平台。本文贡献如下：(1)检测系统硬件平台的构建与实现根据生化传感检测系统的硬件平台设计,光谱仪在检测系统与智能手机之间发挥纽带作用。本文在不修改光谱仪内核驱动前提下,先开发出一款光谱仪USB免驱动静态库,再通过NDK技术将该库编译成Arm平台的动态库。最后实现智能手机通过该动态库及时地采集光谱数据。(2)检测系统软件的设计与实现。为满足检测系统良好的交互使用特性,设计并实现一款操作简单、功能完备和界面友好的Android应用。该程序按照软件项目管理流程实现。首先从功能、界面和性能需求角度进行软件需求分析。再通过用户界面设计、数据库设计和程序模块设计达到程序设计的目的。最后实现软件功能模块,包含用户界面、实时数据、本地数据和数据存储转发四个模块。(3)光谱数据的采集与曲线拟合。获取到的光谱数据,是以二维坐标点(波长,光谱强度)的形式保存。绘制LSPR生化检测曲线时,以一条平滑的曲线展示给用户。本文从最小二乘法曲线、基于RBF曲线和三次样条曲线拟合算法中分析对比发现,三次样条曲线拟合算法更适合处理光谱离散点。并能通过拟合函数,求解指定范围内的极值点。该点为LSPR生化检测消光峰波长位置。(4) LSPR检测系统软件测试和应用研究。系统软件开发完毕后,进行了详细的软件测试。主要利用黑盒测试对软件界面、交互功能和软件性能进行全方位测试。通过测试发现,该软件符合应用需求。同时,LSPR检测系统应用于纳米粒子消光谱和肝病毒生化检测。系统检测精度非常高。总之,本文的创新点在于,根据LSPR生化检测的现状,提出了一套完整的基于Android智能手机的LSPR生化传感检测方案。首先,设计与实现了该系统的软硬件平台；其次,通过了全面的软件测试。最后,将该系统成功应用于纳米粒子和肝病毒的LSPR检测,其检测精度和灵敏度符合预期。
[Abstract]:In the face of the dilemma of early diagnosis of cancer patients, LSPR detection technology has gained wide attention because of its advantages of interface effect, non-marking, real-time and pollution-free detection. With the rise of mobile medical concepts such as home diagnosis and rapid detection, smart phones have gradually developed into an effective platform for LSPR biochemical sensing. For the first time, Indian researchers have developed a smartphone based LSPR biochemical sensing system, which uses smart phone image sensors to obtain LSPR detection data, although the system can meet the basic needs of early detection and mobility of cancer. However, the processing is time-consuming and the detection accuracy is not high. Therefore, this paper proposes a set of portable LSPR biochemical sensing detection scheme for smart phones. Firstly, a professional spectrometer is used to obtain high precision detection data. Then the spectral data are collected quickly through the USB interface of smart phone, and the results of LSPR detection are displayed in time and accurately. This scheme not only solves the above problems well, but also ensures the accuracy and convenience of LSPR biochemical detection. In addition, a good Android application platform is provided. This paper contributes as follows: 1) the construction and implementation of the hardware platform of the detection system according to the design of the hardware platform of the biochemical sensing system. The spectrometer plays a role as a link between the detection system and the smart phone. In this paper, we develop a spectrometer USB driver free static library without modifying the drive of the spectrometer kernel. Then the library is compiled into the dynamic library of Arm platform by NDK technology. Finally, the design and implementation of the software of smart phone detecting system, which can collect spectrum data in time by this dynamic library, is realized. In order to satisfy the good interactive characteristics of the detection system, the software is designed and implemented. Design and implement a Android application with simple operation, complete function and friendly interface. The program is implemented according to the software project management flow. Firstly, the software requirement analysis is carried out from the aspects of function, interface and performance requirements. Database design and program module design to achieve the purpose of programming. Finally, the realization of the software functional module, including the user interface, real-time data, Acquisition and curve fitting of local data and data storage and forwarding four modules. The acquired spectral data are preserved in the form of two-dimensional coordinate points (wavelength, spectral intensity). When drawing the LSPR biochemical detection curve, This paper presents a smooth curve to the user. This paper analyzes and compares the least square curve, based on RBF curve and cubic spline curve fitting algorithm. The cubic spline curve fitting algorithm is more suitable to deal with spectral discrete points. To solve the extreme point in the specified range. This point is the wavelength position of LSPR biochemical detection extinction peak. 4) the software test and application research of LSPR detection system. After the system software development, The software interface, interaction function and software performance are tested with black box test. The software meets the requirements of application. At the same time, the LSPR detection system is applied to the detection of nano-particle elimination spectrum and liver virus biochemistry. The accuracy of the system is very high. In a word, the innovation of this paper lies in the fact that according to the present situation of LSPR biochemical detection, A complete LSPR biochemical sensing detection scheme based on Android smart phone is proposed. Firstly, the hardware and software platform of the system is designed and implemented. The system has been successfully applied to the LSPR detection of nanoparticles and liver viruses, and its detection accuracy and sensitivity are in line with expectations.
【学位授予单位】：中央民族大学
【学位级别】：硕士
【学位授予年份】：2016
【分类号】：TP274;R730.4

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