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双语推荐：心电信号采集系统

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设计了一种基于智能终端的人体心电信号监测的系统,通过该系统可以实时连续地检测到被监护者的心电信号。该系统主要包括前端心电信号采集模块和后端心电信号无线发送模块。其中前端采集模块对心电信号进行了预处理;后端心电信号发送模块采用蓝牙无线通信方式,从而实现心电数据短距离无线传输且方便与PDA或Android智能手机等手持终端通信,保证了对被监护者的连续实时监测。
This article designed of human ECG monitoring system based on an intelligent terminal, through the monitoring system ECG can be real-time continuously detected. The system includes front-end ECG signal acquisition module and back-end ECG wireless transmitter module. The front-end ECG signal acquisition module to pretreatment ECG signal;the back-end ECG signal transmission module using Bluetooth wireless communication mode,in order to achieve short-distance wireless ECG data transmission and convenient with the PDA or Android smart phones and other hand-held terminal communication,to ensure the guardian for the continuous real-time monitoring.

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目的设计一种低成本的便携式心电信号数据采集系统，实现长时间对心电信号进行采集与存储。方法对采集的心电信号进行放大、滤波、电平提升和模数转换后存储于Flash存储器，再通过液晶显示器显示实时心电波形。结果本系统可实现对心电信号进行长时间的数据采集和记录。结论本系统对于临床和患者应用都具有一定的实用价值。
Objective To design a portable and low cost system which can collect and store dynamic data of electrocardio-signal for a long time. Methods The electrocardio-signal will be magniifed, ifltered, elevated and converted to digital signals, and then be registered in Flash memories. Also the real-time cardiograph can be displayed by LCD. Results This system can collect and register dynamic data of electrocardio-signal for a long time. Conclusion This design has practical value for clinic and patients.

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设计了一种能采集人体微弱心电信号的检测系统,此系统使用前端电路实现对心电信号的采集,通过滤波、陷波电路过滤掉人体及器件产生的干扰信号,后级放大及电平抬高电路为模拟信号进行模数转换做准备,最后使用MPS430单片机进行A/D转换,从而实现心率的读取。测试结果表明,此系统达到了良好的检测效果。
In this paper,a measurement system for weak electrocardiograph(ECG)signal is proposed.The system employs an analog front-end for ECG signal acquisition,which integrates bandpass and notch iflters to remove interference signal from human body and environment.A second ampliifer stage provides gain and level shifting to signal for analog-to-digital(A/D) conversion.Final y,the A/D conversion is realized by MPS430 micro-control er,which completes the ECG signal measurement.Experiment results show that the system achieves good measuring performance.

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心电图是人体最重要的生物电信息之一,传统的心电图采集系统和装置使用了分立的元器件对心电信号进行采集;但是由于集成电路、电阻和电容元器件等个体之间存在诸多的差异性,造成了心电图各个导联的参数和指标具有差异性,引起不必要的失真。本文针对现有心电采集装置存在的问题,提出了一种集成化的心电图采集方法,该方法采用集成化的ASIC芯片取代传统的分体式电路,避免了由于电阻和电容差异造成滤波特性不一致,引起心电信号的失真,很大程度上提高了心电采集系统的精度以及信噪比。
Electrocardiograph (ECG) is one of the most important relfections of bioelectrical information. The traditional ECG col ection system and device use discrete components to col ect ECG;however, due to the many differences among each individual integrated circuit (IC), resistance and capacitor, each lead of ECG has different parameters and indicators. This is what we cal unnecessary distortion. Aiming at solving the existing problems in ECG col ection device, this article puts forward an integrated ECG col ection method. This method uses integrated ASIC (Application Speciifc Integrated Circuit) chip to replace the traditional split circuit in order to avoid ECG distortion resulting from inconsistent iflter characteristics due to resistance and capacitor differences, which greatly improves the precision of ECG col ection system and SNR (Signal to Noise Ratio).

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设计完成了一种多生物电信号采集能力并能完成生物电信号模式识别和辅助诊断的复合式生物电信号检测系统。系统通过具备双通道的低噪声高共模抑制比的前置采集放大电路,可实现心电信号和表面肌电信号两种体表生物电信号的检测。通过FPGA硬件化实现的小波分解模块和在NiosⅡ软核中实现的FFT和BP神经网络算法,可以完成对采集到的心电信号心率监测、QRS波群的检测和ST段形态识别反馈监护者的健康信息;并通过提取表面肌电信号活跃段数据和时频域参数为运动性肌肉疲劳评估提供参考。系统通过LCD屏、音频输出和SD卡存储能够完成对信号实时波形和监护参数显示、报警输出和长时间监护数据的存储。
A composite bio-signal monitoring system is designed,which is characterized with multi-signal acquisition capabilities and can complete biological signals pattern recognition and aide diagnosis. Clear surface EMG and surface ECG waveform can be detected via different channels of the pre-acquisition amplifier circuit with low noise and high common mode rejection ratio. The wavelet decomposition module integrated in FPGA are used for heart rate and QRS complex detection,and the BP neural network on NiosIIsoft core has realized the identification of ST segment morphology. The extracted time-frequency domain parameters of surface EMG active segment can provide assessment of muscle fatigue. The system can complete display of the signal waveform and real-time monitoring parameter on the LCD screen,and alarm people by audio speaker,and store prolonged monitoring data on SD card.

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远程无线心电实时监护系统的心电采集终端基于嵌入式设备开发,系统资源和网络带宽都收到限制,这要求系统设计具有低功耗和数据实时压缩的功能,因此引入压缩感知算法对心电信号进行处理。压缩感知算法具有编码计算简单快速,解码计算相对复杂的特点。对于心电信号,需要对压缩感知算法在实时心电压缩系统中的可行性进行研究。
The acquisition terminal of the remote wireless real time ECG monitoring system is developed based on the embedded device ,so system resources and network bandwidth are limited ,which requires a system design with the low power and the real-time data compression function .Therefore the compressed sensing algorithm for processing the ECG signal was introduced . Compressed sensing algorithm is a new signal processing method with the features of simple coding and complex decoding .The feasibility of compressed sensing algorithms in real-time ECG compression system needs to be analyzed .

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随着中国老龄化和家庭空巢化的加剧,患有慢性疾病的老人在医院外的健康监护问题变得日益突出。这就需要人们能够设计出有别于传统医疗仪器的新系统,这样的新系统称为体域网系统。论述了体域网无线心电监护系统的设计方案,重点介绍了患者系统以及预警系统的构成。患者系统采用便携式心电检测模块来采集患者的心电信号;蓝牙短距无线通信技术用于将实时心电信号传输到智能手机;预警系统能接收患者系统发送的心电信号。最后给出了在医院环境中对系统进行的三项测试结果。
With the rapid increase of older people in China,the problem of elder people''s chronic diseases and their health monitoring requirement outside hospital become more and more important. To face such challenge,the body area network sys-tem,a new kind of health care monitor,is needed to build up. This system is a small network based on IOT and sensor technol-ogies. A design scheme of body area network wireless electrocardiogram monitoring system is described in this paper. The patient system and pre-warning system are introduced emphatically. The portable electrocardiogram detecting blockis adopted in the pa-tient block to collect patient''s electrocardiogram signal. The bluetooth short distance wireless communication technology is em-ployed to transmit the real-time electric signal to smartphone. The results of three iterms tested in the hospital environment are given in this paper.

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体表心电图设备，包括常规心电图机、床边心电监护仪、动态心电记录仪、负荷运动心电系统等，是目前最广泛应用的心脏功能诊断／监护设备。这类设备的核心部分是心电信号采集放大器和模数转换器。本文综述了国内外心电信号采集技术的研究现状，分析了其主要技术参数，最后提出低增益直流放大器和高分辨率模数转换器是未来的发展趋势。
Electrocardiographic devices, including common electrocardiogram ( ECG ) machines, bedside ECG monitors,ambulatory ECG recorders,stress exercise ECG systems,and others,are the most widely used tools for cardiac function diagnostic/monitoring currently .The core parts of such equipment are electrocardiographic signals amplifier and analog to digital converter(ADC).The methods of ECG readout circuits and current development are reviewed in the manuscript , and main technical parameters are discussed here.Finally,the low gain DC amplifier and the high resolution analog to digital converter are the main trends in the future .

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目前的心电监护平台使用传感器在设备与病人之间直接进行数据采集,复杂的线路连接使病人心电信号采集时产生压力,数据采集的准确率较低;提出基于ZigBee的心电监护网络平台构建方法,设计了网络中的功能部件与结构方案,采用ARM芯片构造监控平台的核心处理器与外围的数据调理电路,在嵌入式系统中装载了心电信号分析处理算法,实验结果证明,在病人随机走动的情况下,病人的定位误差与数据的采集误差都能保持在相对误差为0.003附近,距离增加也不会出现大幅波动,平台的数据采集准确率高达98.6%,具有很强的实用性。
Based on the ZigBee propos ecg monitoring network platform construction methods,design the function of the network com-ponents and structure plan,the ARM chip is used to construct monitoring platform core processor and peripheral data conditioning circuit,in embedded systems loading the ecg signal processing algorithm,the actual test,the platform of the data acquisition accuracy reaches as high as 98.6%,have very strong practicability.

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针对人体生物医学信号的特点,以ARM处理器LPC2138为核心,结合嵌入式操作系统研究了一种实用的便携式心电信号检测系统。设计了硬件检测电路,将微弱的心电信号进行采集、放大及滤波后提取出来传至ARM处理器进行处理与分析,并将心电波形显示在LCD显示屏上。实验测试表明,该系统能全面实现对心电信号的检测,具有较高的实际应用价值。
Combined with the embedded operating system ,this paper studies a practical portable ECG signal de-tection system,according to the characteristics of human body biomedical signals ,employing the ARM processor LPC2138 as the core. We designed the circuit of hardware detection, and acquired, amplified and filtered the weak ECG signals,then transmitted them to the ARM processor for processing and analyzing. And the ECG waveforms were displayed on the LCD monitor. Experimental results show that this system can fully detect ECG signals and has strong practical application value.

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