Abstract：
BACKGROUND: Electrocardiograms (ECGs) are vital for diagnosing cardiac conditions but obtaining clean signals in Left Ventricular Assist Device (LVAD) patients is hindered by electromagnetic interference (EMI). Traditional filters have limited efficacy. There is a current need for an easy and effective method.
METHODS: Raw ECG data obtained from 5 patients with LVADs. LVAD types included HeartMate II, III at multiple impeller speeds, and a case with HeartMate III and a ProtekDuo. ECG spectral profiles were examined ensuring the presence of diverse types of EMI in the study. ECGs were then processed with four denoising techniques: Moving Average Filter, Finite Impulse Response Filter, Fast Fourier Transform, and Discrete Wavelet Transform.
RESULTS: Discrete Wavelet Transform proved as the most promising method. It offered a one solution fits all, enabling automatic processing with minimal user input while preserving crucial high-frequency components and reducing LVAD EMI artifacts.
CONCLUSIONS: Our study demonstrates the practicality and efficiency of Discrete Wavelet Transform in obtaining high-fidelity ECGs in LVAD patients. This method could enhance clinical diagnosis and monitoring.
METHODS: Raw ECG data obtained from 5 patients with LVADs. LVAD types included HeartMate II, III at multiple impeller speeds, and a case with HeartMate III and a ProtekDuo. ECG spectral profiles were examined ensuring the presence of diverse types of EMI in the study. ECGs were then processed with four denoising techniques: Moving Average Filter, Finite Impulse Response Filter, Fast Fourier Transform, and Discrete Wavelet Transform.
RESULTS: Discrete Wavelet Transform proved as the most promising method. It offered a one solution fits all, enabling automatic processing with minimal user input while preserving crucial high-frequency components and reducing LVAD EMI artifacts.
CONCLUSIONS: Our study demonstrates the practicality and efficiency of Discrete Wavelet Transform in obtaining high-fidelity ECGs in LVAD patients. This method could enhance clinical diagnosis and monitoring.
摘要：
背景：心电图（ECG）对于诊断心脏病至关重要，但是在左心室辅助装置（LVAD）患者中获得清洁信号会受到电磁干扰（EMI）的阻碍。传统的过滤器具有有限的功效。目前需要一种简单有效的方法。
方法：从5例LVAD患者获得的原始ECG数据。LVAD类型包括HeartMateII,III在多个叶轮速度下，还有HeartMateIII和ProtekDuo的案子.检查ECG频谱图，以确保研究中存在各种类型的EMI。然后用四种去噪技术处理ECG：移动平均滤波器，有限脉冲响应滤波器，快速傅里叶变换,和离散小波变换。
结果：离散小波变换被证明是最有前途的方法。它提供了一个适合所有人的解决方案，以最少的用户输入实现自动处理，同时保留关键的高频组件并减少LVADEMI伪影。
结论：我们的研究证明了离散小波变换在LVAD患者中获得高保真ECG的实用性和有效性。该方法可以增强临床诊断和监测。
方法：从5例LVAD患者获得的原始ECG数据。LVAD类型包括HeartMateII,III在多个叶轮速度下，还有HeartMateIII和ProtekDuo的案子.检查ECG频谱图，以确保研究中存在各种类型的EMI。然后用四种去噪技术处理ECG：移动平均滤波器，有限脉冲响应滤波器，快速傅里叶变换,和离散小波变换。
结果：离散小波变换被证明是最有前途的方法。它提供了一个适合所有人的解决方案，以最少的用户输入实现自动处理，同时保留关键的高频组件并减少LVADEMI伪影。
结论：我们的研究证明了离散小波变换在LVAD患者中获得高保真ECG的实用性和有效性。该方法可以增强临床诊断和监测。
