基于Android的心电监护系统设计

发布时间：2018-02-11 03:29

本文关键词： Android 心率失常小波变换主成分分析支持向量机　出处：《华中科技大学》2015年硕士论文　论文类型：学位论文

【摘要】：目前,人们越来越重视健康的生活习惯,更加关注自身的身体健康,因此经常会购买各种智能便携式的心电信号监测设备,比如便携式家用心电监护仪,能测量心率的智能手环等。然而,传统的心电信号监测设备不仅体积大,结构复杂,价格昂贵,而且不适合长时间实时动态监测。便携式的心电监护设备虽然能够长时间动态监测,并且具有采集,显示,存储等功能,但是通常不具备自动分析心电信号及报警功能,而且不便于随身携带,以及随时随地测量。目前流行的智能穿戴设备受其显示屏幕限制通常只能显示心率数据,不能对心电波形,尤其是心率失常波形进行直观的观察。根据这一特点,本文设计了一种基于Android系统的心电监护系统,包括心电电极,信号前端处理电路,心电信号采样及无线传输模块以及基于Android智能手机的心电应用程序等。本系统通过心电电极采集人体的心电信号,然后经过后级的放大,滤波处理电路,微控制器的AD控制器采样前端处理电路输出的心电信号,并经过一定的处理,然后通过串口蓝牙模块无线传输到Android智能手机上。Android智能手机接收到数据后,首先从接收到的数据帧中提取出心电数据,然后对心电信号进行预处理,最后绘制成心电波形显示出来,并且对其进行保存,以备以后使用。除此之外,本文还对接收到的心电数据进一步分析,进行了Q波,R波,S波(合称QRS波群)检测,特征提取,而后对提取的特征通过主成分分析的方法进行降维处理,最后通过支持向量机的方法进行分类,从而实现检测出异常波形,并对其进行记录,报警。本系统能够实现长时间的实时动态监测人体心电信号,同时能够对采集到的心电数据存储。同时,本系统还能实现对采集的心电数据进行自动检测,发现异常波形,立即报警,从而大大减轻了医务人员的负担。本系统具有便携性,低功耗,智能化等特点,对人体心电信号的长时间动态监测具有重大的实用价值。
[Abstract]:At present, people pay more and more attention to healthy living habits and pay more attention to their own health, so they often buy all kinds of intelligent portable ECG monitoring devices, such as portable domestic ECG monitor. Intelligent bracelet that can measure heart rate. However, traditional ECG monitoring equipment is not only large, complex structure, expensive, Although portable ECG monitoring equipment can monitor dynamically for a long time, and has the functions of collecting, displaying and storing, it usually does not have the function of automatic analysis of ECG signal and alarm. And it's not easy to carry around and measure anywhere and anytime. Current smart wearable devices are limited by their display screens to displaying heart rate data, not ECG waveforms. According to this characteristic, this paper designs a ECG monitoring system based on Android system, including ECG electrode, signal front-end processing circuit. ECG sampling and wireless transmission module and ECG application program based on Android smart phone. The AD controller of the microcontroller sampled the ECG signal output from the front-end circuit and processed it to a certain extent, then transmitted it wirelessly to the Android smartphone via the Bluetooth module of the serial port. After receiving the data, the AD controller received the data from the front-end circuit. First, the ECG data is extracted from the received data frame, then the ECG signal is preprocessed. Finally, the ECG waveform is displayed and stored for future use. In this paper, the received ECG data are further analyzed, the Q wave R wave S wave (QRS wave group) is detected, the feature is extracted, and the extracted feature is reduced by principal component analysis (PCA). Finally, the abnormal waveform can be detected, recorded and alerted by the method of support vector machine. This system can realize real-time and dynamic monitoring of human ECG signal for a long time. At the same time, it can store the collected ECG data. At the same time, the system can also realize the automatic detection of the collected ECG data, discover the abnormal waveform, and immediately alarm, thus greatly lightening the burden of the medical personnel. The characteristics of low power consumption and intelligence have great practical value for long time dynamic monitoring of human ECG signal.
【学位授予单位】：华中科技大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：TH776;R540.4

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