Journal of electrocardiology · 2024
Enhancing ECG readability in LVAD patients: A comparative analysis of Denoising techniques with an emphasis on discrete wavelet transform.
СтатьяСравнительное исследованиеНазвание и аннотация: Перевод пока не подготовлен
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Khalil Jalkh, Kayla Shahbazian, Phong Nguyen, Wael AlJaroudi, Evan Hiner, Adnan AlJaroudi, Haitham Hreibe
Аннотация
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.
CONCLUSION: 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.
CONCLUSION: 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.