FPGA实现的实时ECG R波检测系统与性能验证

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本文主要探讨了"基于FPGA的实时R波检测"这一关键领域的研究。在现代心脏病学和自动心电图分析系统中，R波检测起着至关重要的作用，因为它能准确地识别心脏电信号中的R波，这对于诊断和监测心脏健康具有重要意义。研究者们针对这一需求，设计了一款便携式自动心电图分析系统，采用的是Altera DE2-70开发板上的FPGA技术。该系统的设计分为四个核心模块： 1. 数据输入：通过高效的数据采集接口，系统能够实时接收来自各种传感器的心电信号，包括MIT/BIH心律失常数据库中的数据，这些数据是进行后续处理的基础。 2. ECG denoising (心电图去噪)：为了提高信号质量，研究者采用了CDF9/7小波滤波器，这种滤波器特别适合于去除高频噪声，使得后续分析更为精确。小波分析因其对信号特性有良好的保留能力而被广泛用于心电图信号处理。 3. ECG analysis and R-wave detection（心电信号分析与R波检测）：这是整个系统的焦点，通过对去噪后的信号进行深入分析，利用阈值方法来精确识别R波的发生时刻。阈值法是一种常见的非参数方法，通过设定特定的阈值来区分正常的心电信号和异常事件，如R波。 4. 结果显示：系统将处理后的结果以直观的方式展示出来，便于医生或研究人员快速理解和评估心脏健康状况。在 Quartus II 9.0 开发环境中，研究团队完成了系统的模拟和综合验证。实验结果显示，他们提出的FPGA架构能够实现对R波的准确检测，并且其资源利用率达到了较高的效率。这意味着这个系统不仅功能强大，而且能够在实时条件下提供可靠的结果，对于医疗设备和实时健康监测应用具有很高的实用价值。这篇研究论文展示了如何利用FPGA技术优化心电图分析系统，提高了R波检测的精度和实时性，为心脏病患者提供了更便捷、精准的诊断手段，同时也推动了电子健康领域的发展。

The Real-Time R-wave Detection

Based on FPGA

Tongqing Li, Yide Ma Member IEEE, Yurun Ma, Xiangyu Lu

School of Information Science and Engineering

Lanzhou University

Lanzhou, China

litq12@lzu.edu.cn,

yidema@gmail.com, yurunma@gmail.com, luxy2012@lzu.edu.cn

Abstract—R-wave detection is one of the most significant parts in

Electrocardiogram (ECG) signal studies and plays an important

role in the automatic ECG analysis system. In this research, we

design a prototype of portable automatic ECG analysis system

based on field programmable gate array (FPGA) using Altera

DE2-70 development board. The system includes four parts:

1)Data input, 2)ECG denoising, 3)ECG analysis and R-wave

detection, 4) Results display. In this paper, we use the data from

the well-known MIT/BIH arrhythmia database. CDF9/7 wavelet

filter is used to remove the high-frequency noise and the

threshold method is used to detect the R-wave. In addition, In the

Quartus II 9.0 development environment, we complete the

simulation and synthesis. Experimental results based on the

system show that proposed architecture can detect R-wave

accurately and the utilization percent of resource is low, just 6%.

Keywords-ECG, R-wave detection, CDF9/7 wavelet filter,

Threshold, FPGA.

I. INTRODUCTION

Electrocardiogram (ECG) signal is one of the earliest

biological signals studied and applied to clinical medicine. At

present, ECG analysis is still one of the simplest noninvasive

diagnostic methods for heart and cardiovascular disease. With

the rapid development of electronic science technology and

family medicine, the computer aided diagnosis system and

portable ECG monitoring devices are developed, which make

the ECG automatic analysis become a research focus in the

field of Biomedical Engineering. However, automated analysis

of ECG beats is a challenging problem because the

morphological and temporal characteristics of ECG signals

show significant variation for different patients under different

physical conditions [1].

It is important that the reliable and accurate detection

algorithm of the basic characteristic features of the signal for

the automatic ECG analysis system. QRS wave is the most

important part in ECG signal and used as the reference point

for beat alignment. In recent years, there have been a lot of

R-wave detection algorithms proposed, such as difference

threshold value algorithm [2] [3], wavelet transform algorithm

[4] [5] [6], template matching algorithm [7], neural network

algorithm [8] [9], and others that combine the basic algorithms

above [10] [11]. However, most of these algorithms are in the

stage of theoretical research and processed offline. The studies

of the hardware implementation of the algorithm are relatively

small.

Nowadays, Field Programmable Gate Array (FPGA) is at

the forefront of digital signal processing technology. We

generally use the hardware description language, VerilogHDL

or VHDL, to configure the FPGA. FPGA allows designers to

add some new circuits, or reconfigure the hardware resources

for the special functions even after the program has been

downloaded into chips. The fast growing speed and circuit

density of FPGAs have made them a significant player in

domains earlier dominated by Application Specific Integrated

Circuits (ASIC). Besides being used for general purpose logic

design, modern FPGAs are equipped with building blocks for

specialized applications such as DSP and embedded system

design [12]. In recent years, FPGA has also been widely used

in the field of ECG signal processing, such as ECG denoising

system [13] [18], QRS wave detection [12] [14] and feature

extraction. In [15], an accurate FPGA based ECG Analysis

system is described. That design is based on popular software

based QRS detection.

Our previous research [16] succeeded making lots of

simulations for the real-time R-wave detection using CDF9/7

wavelet filter and difference method. In this paper, we try to

implement them on a prototype of portable automatic ECG

analysis system based on FPGA using Altera DE2-70

development board. FPGA system has high speed and the

plentiful leaving resources, which make other more circuits can

be easily join this design to form a larger system that has more

functions. Moreover, at present, the researches for portable

ECG device tend to be small size, low power and real-time data

processing. So the portable ECG devices based on FPGA have

a great advantage.

This paper is organized as follows. In section II, we

describe the algorithm used in this system. This algorithm is

our previous research, so we introduce the algorithm

implementation process briefly and some improved places for

more suitable for FPGA implementation. Section III introduces

the design and implementation of ECG analysis system on

FPGA. It is the most important part of our paper. We use

MIT/BIH Arrhythmia Database to test system and give the data

analysis and comparison in Section IV. Finally, the conclusions

are made in section V.

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FPGA实现的实时ECG R波检测系统与性能验证

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