ArticleBiomedical engineering letters2022
The evaluation of seismocardiogram signal pre-processing using hybridized variational mode decomposition method.
Article in Biomedical engineering letters, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 1 paper.
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1 citing paper in PubMed.
- A triaxial accelerometer-based approach for motion noise resilient segmentation of seismocardiogram signal.Physical and engineering sciences in medicine · 2026Article
Corrections and comments
- Erratum issued
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5 authors.
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Abstract
This study aims to determine the performance of variational mode decomposition (VMD) combined with detrended fluctuation analysis (DFA) as a hybrid framework for extracting seismocardiogram and respiration signals from simulated single-channel accelerometry data and removing its contained noise. The method consists of two consecutive layers of VMD that each contribute to extracting respiration and SCG signal respectively. DFA is utilized to determine the number of modes produced by VMD and select the most appropriate modes to be the constituents of the reconstructed signal based on the Hurst exponent value thresholding. This hybridized VMD successfully extracted respiration and SCG signal with minimal mean absolute error value (0.516 and 0.849, respectively) and boosted the SNR to 2 dB and 4 dB, respectively in heavily noise-interfered conditions. This method also outperformed other empirical mode decomposition strategies and exhibits short computational time. Two main drawbacks exist in this framework, i.e. the determination of balancing parameter (
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