Hardware/Software Co-design of an ECG- PPG Preprocessor: A Qualitative & Quantitative Analysis

Aditta Chowdhury, Diba Das, R. Cheung, M. Chowdhury
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引用次数: 1

Abstract

This paper aims to design a digital system to pre-process electrocardiogram (ECG) and photoplethysmogram (PPG) signal for the purpose of hardware implementation. Muscle signal, motion artifacts, power line interference affect the biomedical signal during data acquisition. The proposed system focuses at removing the noises by designing infinite impulse response filter to remove power line noise and finite impulse response filter to eliminate other high and low frequency noises. At first the preprocessor is designed in Matlab to validate the simulation performance. Then the hardware is designed in xilinx system generator targeting Zedboard Zynq xc7z020-1clg484. Finally, we verified the hardware software codesign by comparing both outputs. For quantity based analysis different filtering techniques have been applied to determine the most optimized system in terms of resource utilization and power consumption. Pearson correlation coefficient of 0.9993 and 0.9982 have been found for ECG and PPG, respectively using Hamming filter technique for High and low pass filter. Root squared error for both signal has been also in the range of 10−2• These data validate the accuracy of the designed system providing quality assurance. Frequency spectrum also has been analyzed to ensure denoising of undesired signals. The designed preprocessor can be utilized for further analysis of the signals and designing digital systems & wearable devices for the detection of heart rate, cardiac diseases etc.
一种ECG- PPG预处理器的软硬件协同设计:定性与定量分析
本文旨在设计一个数字系统,对心电图(ECG)和光容积描记图(PPG)信号进行预处理,以实现硬件实现。在数据采集过程中,肌肉信号、运动伪影、电源线干扰会影响生物医学信号。该系统主要通过设计无限脉冲响应滤波器来消除电力线噪声,设计有限脉冲响应滤波器来消除其他高低频噪声。首先在Matlab中设计预处理器,验证其仿真性能。然后以Zedboard Zynq xc7z020-1clg484为目标,在xilinx系统生成器中进行硬件设计。最后,通过对比两种输出,验证了软硬件协同设计的正确性。对于基于数量的分析,已经应用了不同的过滤技术来确定在资源利用率和功耗方面最优化的系统。采用汉明滤波技术进行高通和低通滤波,心电图和PPG的Pearson相关系数分别为0.9993和0.9982。两个信号的均方根误差也在10−2•的范围内,这些数据验证了所设计系统的准确性,提供了质量保证。对频谱也进行了分析,以确保不需要的信号去噪。所设计的预处理器可用于进一步分析信号,设计用于检测心率、心脏病等的数字系统和可穿戴设备。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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