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.
Insights
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.
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.
Abstract:
Cardiac diseases constitute a major root of global mortality and they are likely to persist. Electrocardiogram (ECG) is widely opted in clinics to detect countless heart illnesses. Numerous artifacts interfere with the ECG signal, and their elimination is vital to allow medical specialists to acquire valuable statistics from the ECG. The utmost artifact that is added to the ECG signal is power line interference (PLI). Numerous filtering methods have been employed in the literature to eliminate PLI from noisy ECG. This article proposes an extended Kalman filter (EKF)-based adaptive noise canceller (ANC) that comprises PLI frequency as a distinct model parameter. Thus, it is capable of tracking PLI with drifting frequency. The proposed canceller's performance is compared with state-space recursive least squares (SSRLSs) filter-based PLI canceling. The evaluation is carried out for four cases of PLI, that is, PLI with known amplitude and frequency, PLI with unknown amplitude and frequency, PLI with drifting amplitude and frequency, and PLI removal from a real-time ECG recording. The samples of the Massachusetts Institude of Technology (MIT)-Boston's Beth Israel Hospital (BIH) arrhythmia database are considered for the first three cases, whereas, for the fourth case, real ECG signal is taken from armed forces institude of cardiology, the national institude of heart diseases (AFIC/NIHD), Pakistan. Mean square error, frequency spectrum, and noise reduction are selected as performance metrics for comparison. Simulation results depict that the presented EKF-based ANC system outperforms the SSRLS-based ANC system and effectively eliminates PLI from ECG under all four investigated scenarios.
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