首页> 外文会议>2016 Annual Connecticut Conference on Industrial Electronics, Technology and Automation >Hardware-based FIR filter implementations for ECG signal denoising: A monitoring framework from industrial electronics perspective
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Hardware-based FIR filter implementations for ECG signal denoising: A monitoring framework from industrial electronics perspective

机译:用于ECG信号降噪的基于硬件的FIR滤波器实现:工业电子角度的监控框架

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This work represents the design and verification of three different finite impulse response (FIR) filter implementations for removing the noise of electrocardiogram (ECG) signals. Generally, ECG signals may be contaminated with different noise sources such as body movement and respiration, electromyography (EMG) interference, power line interference and the baseline wander noise. The FIR filter coefficients are calculated to attenuate the 60 Hz frequencies. The advanced filter design tool available with MATLAB is used to first determine the FIR filter coefficients. These coefficients are then used in three different FIR filter implementations: regular implementation, pipelined implementation and pipelined multiply-accumulate (MAC) implementation. The three implementations are designed using VHDL and the Quartus II design toolset. A test bench is also designed to verify the operation of each filter implementation, and the Modelsim simulator available with Quartus is used to run the tests. The synthesized reports for the three different implementations show the resource utilization and the maximum operating frequency. As a result, the regular (direct) design produces the simplest design but consumes more resources and operates at lower frequencies. The pipelined architecture consumes more resources but it enhances the operating frequency. The pipelined MAC implementation requires the least resources and operates at extremely higher performance, however, the main drawback is its complexity. The hardware implementations can be further viewed as an industrial ECG monitoring framework where system dynamics modeling can be applied to minimize the risks associated with the framework using any of the three implementations.
机译:这项工作代表了用于消除心电图(ECG)信号噪声的三种不同的有限冲激响应(FIR)滤波器实现的设计和验证。通常,ECG信号可能会被不同的噪声源污染,例如人体运动和呼吸,肌电图(EMG)干扰,电源线干扰和基线漂移噪声。计算FIR滤波器系数以衰减60 Hz频率。 MATLAB附带的高级滤波器设计工具用于首先确定FIR滤波器系数。然后,将这些系数用于三种不同的FIR滤波器实现中:常规实现,流水线实现和流水线乘法累加(MAC)实现。这三种实现是使用VHDL和Quartus II设计工具集设计的。还设计了一个测试台,以验证每个过滤器实现的操作,并使用Quartus附带的Modelsim模拟器来运行测试。三种不同实现的综合报告显示了资源利用率和最大工作频率。结果,常规(直接)设计产生了最简单的设计,但是消耗了更多的资源并以较低的频率工作。流水线架构消耗更多资源,但会提高工作频率。流水线MAC实施需要最少的资源并以极高的性能运行,但是,主要缺点是其复杂性。硬件实现可以进一步视为工业ECG监视框架,其中可以使用三种实现中的任何一种,应用系统动力学建模以最小化与框架相关的风险。

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