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Noise Elimination of Electrocardiogram Signals Using the Evolutionary Bispectrum

机译：使用进化BISPectrum的心电图信号消除噪声消除

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The electrocardiogram (ECG) signal provides a valuable basis for the clinical diagnosis and treatment of several diseases. However, its reference significance is based on the effective acquisition and correct recognition of ECG signals. In fact, this mV-level weak signal can be easily affected by various interferences caused by the power of magnetic field, patient respiratory motion or contraction, and so on from the sampling terminal to the receiving and display end. The overlapping interference affects the quality of the ECG waveform, leading to a false detection and recognition of wave groups, and thus causing misdiagnosis or faulty treatment. Therefore, the elimination of the interference of the ECG signal and the subsequent wave group identification technology has been a hot research topic, and their study has important significance. Since when the signal is non-stationary, like the ECG signal, neither the regular power spectrum nor the bispectrum can handle this problem because they do not reflect the time variation of the process characteristics. With the recent introduction of the evolutionary bispectrum (EB) in digital signal processing, a new approach to the analysis problem has been devised. The work in this paper is focusing on the reduction of the noise interferences by introducing a new algorithm based on the EB. This approach exploits the fact that the EB contains information regarding both the phase and the magnitude of the system. Also, we will show that if the ECG signal is corrupted by stationary/non-stationary noise with symmetric distribution, the noise can be removed using the EB. To show the effectiveness of the proposed method, some simulation is declared.
机译：心电图（ECG）信号为几种疾病的临床诊断和治疗提供了有价值的基础。然而，其参考意义基于对ECG信号的有效采集和正确识别。事实上，这种MV电平弱信号可以容易地受到由磁场，患者呼吸运动或收缩的功率引起的各种干扰的影响，等等从采样终端到接收和显示端。重叠干扰影响了ECG波形的质量，导致波组的假检测和识别，从而导致误诊或缺陷治疗。因此，消除了ECG信号的干扰和随后的波组识别技术一直是热门研究课题，他们的研究具有重要意义。由于当信号是非静止的，如ECG信号，常规功率频谱和BISPectrum都不能处理这个问题，因为它们不反映过程特性的时间变化。随着最近在数字信号处理中的进化BISPectrum（EB）的引入，已经设计了一种新的分析问题的方法。本文的工作专注于通过引入基于EB的新算法来减少噪声干扰。这种方法利用EB包含关于系统的相位和幅度的信息。此外，我们将表明，如果ECG信号通过具有对称分布的静止/非静止噪声损坏，则可以使用EB拆下噪声。为了显示所提出的方法的有效性，声明了一些模拟。

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