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صفحه اصلی
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هفتمین کنفرانس بین المللی میکروالکترونیک ایران
Hybrid ECG Signal Denoising Using Wavelet Transform and Adaptive Notch Filtering
نویسندگان :
Hossein Kodoori
1
Mehrnaz Monajati
2
1- دانشگاه تحصیلات تکمیلی صنعتی و فناوری پیشرفته کرمان
2- دانشگاه تحصیلات تکمیلی صنعتی و فناوری پیشرفته کرمان
کلمات کلیدی :
ECG denoising،adaptive notch filter،wavelet transform،biomedical signal processing،power-line interference
چکیده :
This research introduces a hybrid ECG signal denoising method that integrates discrete wavelet transform (DWT) with adaptive notch filtering to effectively remove both transient and narrowband noise while preserving critical waveform morphology. The Symlet-4 wavelet and Bayesian thresholding were used to suppress high-frequency and non-stationary noise, followed by a dynamically tuned IIR notch filter to eliminate power-line interference in the 50–60 Hz range. The method was evaluated using ECG signals from the MIT-BIH Arrhythmia Database and assessed through Signal-to-Noise Ratio (SNR), Peak Signal-to-Noise Ratio (PSNR), and Root Mean Square Error (RMSE). Experimental results showed consistent improvements across all five test signals, with average SNR enhancement of 10.36 dB, PSNR exceeding 24.58 dB, and RMSE reduced to an average of 11.32. Compared to standalone wavelet denoising, the hybrid approach demonstrated significantly better noise suppression and morphological fidelity. These findings support its suitability for real-time monitoring systems and clinical applications.
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بیشتر
ثمین همایش، سامانه مدیریت کنفرانس ها و جشنواره ها - نگارش 43.9.1