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用于心电信号的能量最大化模拟信息转换系统
引用本文:池博浩,江 浩,钱 慧,冯忱晖.用于心电信号的能量最大化模拟信息转换系统[J].仪器仪表学报,2021(3):213-220.
作者姓名:池博浩  江 浩  钱 慧  冯忱晖
作者单位:1.福州大学物理与信息工程学院
基金项目:福建省数字福建重点实验室专项(82917002)、中央引导地方科技发展专项福建省科技厅重点项目(82317241)资助
摘    要:现有便携式心电采集系统需要低功耗高分辨率的模拟数字转换模块,虽然基于脉冲宽度调制的模拟信息转换器(AIC)可以有效降低系统的采样速率,但是该系统量化部分的转化时钟与量化精度成正比,因此存在功耗过高的问题。依据心电信号的能量不均衡特性,提出一种基于功率熵的精度可调时间-数字转换模块(TDC)设计方法。以能量最大化作为设计准则的基本思想,通过分析ECG信号的功率谱熵,确定系统观测向量所需的最小量化精度,实现AIC时间编码系统的优化设计。测试结果表明,该设计方法能够在压缩比为4,重构信噪比为38.91 dB,重构精度为0.36%的情况下,在采样心电信号的同时减少了80%的TDC内部时钟动态翻转,从而有效降低功耗。

关 键 词:随机解调器  压缩感知  亚奈奎斯特采样  模拟信息转换器  脉冲宽度调制  时间-数字转换  功率谱熵

Energy maximization analog-to-information converter system for ECG signal
Chi Bohao,Jiang Hao,Qian Hui,Feng Chenhui.Energy maximization analog-to-information converter system for ECG signal[J].Chinese Journal of Scientific Instrument,2021(3):213-220.
Authors:Chi Bohao  Jiang Hao  Qian Hui  Feng Chenhui
Affiliation:1.College of Physics and Information Engineering, Fuzhou University
Abstract:The current portable ECG acquisition system needs analog to digital conversion module, which has low power consumption and high resolution. Although the analog to information converter (AIC) based on pulse width modulation can effectively reduce the sampling rate of the system, the quantization part of the conversion clock is proportional to the quantization accuracy. Therefore, there is a problem of high power consumption. In this study, a precision adjustable time to digital conversion (TDC) module based on the power entropy is proposed, which is based on the energy imbalance of ECG signal. The energy maximization is taken as the basic principle of design. The minimum quantization accuracy of system observation vector is determined by analyzing the power spectrum entropy of ECG signal. In this way, the optimal design of AIC time coding system is achieved. Experimental results show that this method can reduce 80% TDC clock dynamic reversal while sampling ECG signals under the conditions of compression ratio of 4, SNR of 38. 91 dB and reconstruction accuracy of 0. 36% . Therefore, the power consumption can be reduced effectively.
Keywords:random demodulation  compressed sensing  sub-Nyquist sampling  analog-to-information converter  pulse width modulation  time to digital conversion  power spectrum entropy
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