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Research on Denoising Methods for Magnetocardiography Signals in a Non-Magnetic Shielding Environment
by
Xing, Biao
, Feng, Xie
, Zhang, Binzhen
in
Accuracy
/ arithmetic optimization
/ Cardiac function
/ Cardiography
/ Cardiovascular disease
/ Comparative analysis
/ Contraindications
/ Control
/ Electrocardiography
/ Electromagnetic noise
/ Heart
/ Identification and classification
/ Localization
/ Magnetic fields
/ Magnetic properties
/ Magnetic resonance imaging
/ magnetocardiography (MCG)
/ Mathematical optimization
/ Measurement
/ Medical imaging
/ Methods
/ Morphology
/ Observations
/ Optimization algorithms
/ Physiological aspects
/ Radiation
/ signal denoising
/ Signal processing
/ Technology application
/ Ultrasonic imaging
/ un-magnetically shielded
/ variational mode decomposition (VMD)
/ wavelet threshold
2025
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Research on Denoising Methods for Magnetocardiography Signals in a Non-Magnetic Shielding Environment
by
Xing, Biao
, Feng, Xie
, Zhang, Binzhen
in
Accuracy
/ arithmetic optimization
/ Cardiac function
/ Cardiography
/ Cardiovascular disease
/ Comparative analysis
/ Contraindications
/ Control
/ Electrocardiography
/ Electromagnetic noise
/ Heart
/ Identification and classification
/ Localization
/ Magnetic fields
/ Magnetic properties
/ Magnetic resonance imaging
/ magnetocardiography (MCG)
/ Mathematical optimization
/ Measurement
/ Medical imaging
/ Methods
/ Morphology
/ Observations
/ Optimization algorithms
/ Physiological aspects
/ Radiation
/ signal denoising
/ Signal processing
/ Technology application
/ Ultrasonic imaging
/ un-magnetically shielded
/ variational mode decomposition (VMD)
/ wavelet threshold
2025
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Research on Denoising Methods for Magnetocardiography Signals in a Non-Magnetic Shielding Environment
by
Xing, Biao
, Feng, Xie
, Zhang, Binzhen
in
Accuracy
/ arithmetic optimization
/ Cardiac function
/ Cardiography
/ Cardiovascular disease
/ Comparative analysis
/ Contraindications
/ Control
/ Electrocardiography
/ Electromagnetic noise
/ Heart
/ Identification and classification
/ Localization
/ Magnetic fields
/ Magnetic properties
/ Magnetic resonance imaging
/ magnetocardiography (MCG)
/ Mathematical optimization
/ Measurement
/ Medical imaging
/ Methods
/ Morphology
/ Observations
/ Optimization algorithms
/ Physiological aspects
/ Radiation
/ signal denoising
/ Signal processing
/ Technology application
/ Ultrasonic imaging
/ un-magnetically shielded
/ variational mode decomposition (VMD)
/ wavelet threshold
2025
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Research on Denoising Methods for Magnetocardiography Signals in a Non-Magnetic Shielding Environment
Journal Article
Research on Denoising Methods for Magnetocardiography Signals in a Non-Magnetic Shielding Environment
2025
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Overview
Magnetocardiography (MCG) offers a noninvasive method for early screening and precise localization of cardiovascular diseases by measuring picotesla-level weak magnetic fields induced by cardiac electrical activity. However, in unshielded magnetic environments, geomagnetic disturbances, power-frequency electromagnetic interference, and physiological/motion artifacts can significantly overwhelm effective magnetocardiographic components. To address this challenge, this paper systematically constructs an integrated denoising framework, termed “AOA-VMD-WT”. In this approach, the Arithmetic Optimization Algorithm (AOA) adaptively optimizes the key parameters (decomposition level K and penalty factor α) of Variational Mode Decomposition (VMD). The decomposed components are then regularized based on their modal center frequencies: components with frequencies ≥50 Hz are directly suppressed; those with frequencies <50 Hz undergo wavelet threshold (WT) denoising; and those with frequencies <0.5 Hz undergo baseline correction. The purified signal is subsequently reconstructed. For quantitative evaluation, we designed performance indicators including QRS amplitude retention rate, high/low frequency suppression amount, and spectral entropy. Further comparisons are made with baseline methods such as FIR and wavelet soft/hard thresholds. Experimental results on multiple sets of measured MCG data demonstrate that the proposed method achieves an average improvement of approximately 8–15 dB in high-frequency suppression, 2–8 dB in low-frequency suppression, and a decrease in spectral entropy ranging from 0.1 to 0.6 without compromising QRS amplitude. Additionally, the parameter optimization exhibits high stability. These findings suggest that the proposed framework provides engineerable algorithmic support for stable MCG measurement in ordinary clinic scenarios.
Publisher
MDPI AG,Multidisciplinary Digital Publishing Institute (MDPI)
Subject
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