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AUTHOR(S): L. S. Jayashree, M. Sherlin Jenifer
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ABSTRACT This paper examines how the diagnosis of heart conditions is enhanced at the conjunction of modern computational methods and Seismocardiography (SCG), Without the requirement of invasive methods, SCG detects minute vibrations on the chest wall brought on by the heart's movements providing vital information on the heart function noninvasively. However, because of the complexity of the signal and the variety from person to person, the task of interpreting the signal accurately is challenging. To get beyond these obstacles, this work employs advanced signal processing techniques. In order To isolate significant frequency components from the signal the Discrete Wavelet Transform (DWT) is used. It further lowers noise in SCG signals and enhances better feature extraction. R-peaks in ECG signals are identified by The Pan-Tompkins algorithm identifies. They are then synchronized with SCG data, which allows to achieve a thorough segmentation and analysis of each heartbeat. To further refine the SCG signals interpolation techniques like Akima Interpolation and Piecewise Cubic Hermite Interpolation (PCHIP) are used to produce a continuous dataset, guaranteeing smooth and consistent signals for analysis. The SCG signals are then broken into Intrinsic Mode Functions (IMFs) by Hilbert-Huang Transform(HHT), which yields a more precise time-frequency analysis that is tailored to each individual signal. This study shows that seismocardiography (SCG) can provide accurate and non-invasive measurements of heart function by combining SCG and (ECG) data using advanced computational techniques. SCG has great potential as a reliable diagnostic tool in clinical settings, offering an easy and dependable way to assess cardiac health. |
KEYWORDS Seismocardiography,non-invasive, Hilbert-Huang Transform, Signal Processing, Discrete Wavelet Transform |
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Cite this paper L. S. Jayashree, M. Sherlin Jenifer. (2024) Optimising Seismocardiography for Precision Cardiac Diagnosis with Advanced Signal Processing Algorithms. International Journal of Biology and Biomedicine, 9, 24-30 |
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