基于LabVIEW的脉搏数据处理系统的设计与实现

发布时间：2018-05-31 16:10

本文选题：脉搏信号 + 可穿戴计算　；参考：《北京工业大学》2014年硕士论文

【摘要】：心脑血管是危害当今人类健康的主要疾病之一，随着我国人民生活水平的不断提高以及老龄化加深，其发病率和死亡率逐年增加。因此，需要一种方便快捷的检测方法来随时了解自身的健康状况。脉搏信号是一种非线性、非平稳的生理信号，其中含有大量的生理、病理信息，通过对其信号的检测并研究分析结果，可以对早期的心脑血管疾病有预防并能够及时对患者进行治疗。本课题应采用可穿戴计算技术开发脉搏数据采集系统，并基于LabVIEW开发脉搏分析处理软件。本文确定以ATmegal6单片机为核心的Arduino开发为基础，对脉搏信号进行采集和存储，并集成蓝牙模块将数据传输到上位机。其中上位机以LabVIEW为平台，采用多分页的方式和多模块化设计理念开发一套脉搏信号采集、分析系统软件。该软件主要包括数据库管理模块、脉搏数据采集模块、脉搏信号处理模块等。由于脉搏信号幅值较低，在数据采集的过程中，信号可能会包含摩擦、干扰等噪声信号，对脉搏数据、信号等的提取容易造成误判，需要进行去噪处理。论文将采集到的脉搏信号进行小波去噪，，通过分析得到适合的小波去噪方法，并将脉搏数据进行小波特征值提取，进而将正常人的脉搏数据与患者的脉搏数据进行区分，以此来判断老年人是否发病，达到监测老年人身体健康的目的，为老年人心血管疾病早期预防和治疗提供决策支持。
[Abstract]:The cardiovascular and cerebral blood vessels are one of the main diseases that harm the health of human being. With the continuous improvement of the living standards and the deepening of the aging of the people in China, the incidence and mortality of the blood are increasing year by year. Therefore, a convenient and quick method is needed to understand the health of the people at any time. The pulse signal is a nonlinear, non-stationary physiology. The signal, which contains a lot of physiological and pathological information, can prevent the early cardiovascular and cerebrovascular diseases and can treat the patients in time by detecting the signals and studying the analysis results. This topic should develop the pulse data collection system by wearable computing technology, and develop the pulse analysis software based on LabVIEW.
Based on the development of Arduino with ATmegal6 as the core, this paper is to collect and store the pulse signal, and integrate the Bluetooth module to the upper computer. The upper computer uses LabVIEW as the platform to develop a pulse signal acquisition and analysis system software by multi paging and multi modular design idea. Mainly including database management module, pulse data acquisition module, pulse signal processing module and so on. Due to the low pulse signal amplitude, in the process of data acquisition, the signal may contain friction, interference and other noise signals, the extraction of pulse data, signal and so on is easy to be misjudged and need to be de-noised.
The pulse signal of the collected pulse is de-noised by wavelet, and the suitable wavelet denoising method is obtained, and the pulse data is extracted from the wavelet characteristic value. Then the pulse data of the normal person is distinguished from the pulse data of the patient, in order to judge whether the elderly are sick or not, so as to monitor the health of the elderly. The early prevention and treatment of cardiovascular disease in the elderly provide decision support.
【学位授予单位】：北京工业大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TN911.6

【参考文献】