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Extended Kalman Filter-Based Power Line Interference Canceller for Electrocardiogram Signal.

Suleman Tahir1, Muneeb Masood Raja1, Nauman Razzaq1

  • 1Mechatronics Engineering Department, College of Electrical and Mechanical Engineering, National University of Sciences and Technology, Islamabad, Pakistan.

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|July 15, 2021
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Summary
This summary is machine-generated.

This study introduces an extended Kalman filter (EKF)-based adaptive noise canceller (ANC) to effectively remove power line interference (PLI) from electrocardiogram (ECG) signals. The EKF-based ANC demonstrates superior performance in eliminating PLI, even with drifting frequencies, compared to existing methods.

Keywords:
ECGEKFPLISSRLSfrequency spectrum

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Area of Science:

  • Biomedical Engineering
  • Signal Processing
  • Cardiology

Background:

  • Cardiac diseases are a leading cause of mortality globally.
  • Electrocardiogram (ECG) is crucial for diagnosing heart conditions.
  • Power line interference (PLI) is a significant artifact in ECG signals, hindering accurate diagnosis.

Purpose of the Study:

  • To propose and evaluate an extended Kalman filter (EKF)-based adaptive noise canceller (ANC) for eliminating PLI from ECG signals.
  • To assess the EKF-ANC's ability to track PLI with drifting frequency.
  • To compare the performance of the proposed EKF-ANC with state-space recursive least squares (SSRLS) filter-based PLI cancellation.

Main Methods:

  • An EKF-based ANC was developed, incorporating PLI frequency as a distinct model parameter.
  • The system was evaluated using ECG data from the MIT-BIH arrhythmia database and real-time recordings.
  • Performance was assessed across four scenarios: known/unknown amplitude/frequency PLI, drifting PLI, and real-time PLI removal.
  • Key performance metrics included mean square error, frequency spectrum analysis, and noise reduction.

Main Results:

  • The EKF-based ANC effectively eliminated PLI from ECG signals in all tested scenarios.
  • The proposed EKF-ANC demonstrated superior performance compared to the SSRLS-based ANC.
  • Accurate tracking of PLI with drifting amplitude and frequency was achieved.

Conclusions:

  • The EKF-based ANC is a highly effective method for removing PLI from ECG signals.
  • This technique offers significant improvements over existing PLI cancellation methods, especially for dynamic interference.
  • The developed system has the potential to enhance the accuracy of ECG-based cardiac diagnostics.