Hybrid Algorithm for Denoising of Vibrocardiographic Signals Using Savitzky Golay Filter and Hilbert-Huang Transform
Vibrocardiography is an important diagnostic tool used to fetch out the cardiac vibration at the chest surface simply by attaching the electrodes. But these vibration signals can contaminated by artifacts and to get exact outcomes for better and restorative diagnosis of heart problems, denoising of VCG signal is used. In Vibrocardiographic (VCG) signals, several filter methodologies are accessible for expulsion of noise artifacts. In this work the adaptive Savitzky Golay filter and Hilbert-Huang Transformation (HHT) is used for denoising of noise interference from VCG signals. In this paper better search results are obtained by adaptive hybrid optimization Algorithms. Intrinsic Mode Functions (IMFs) are decomposed in a limited number using the Empirical Mode Decomposition (EMD) to Vibrocardiographic signals. To examine the VCG signal dominated IMFs and noise dominated IMFs boundary, energy investigation is led on the IMFs.The next contribution is to implement the denoising of VCG signal using Hybrid Bat Optimization (HBO) algorithm. The proposed technique centers around the remarkable noise decrease execution for VCG signals, and the noise removed signal is reasonable for clinical finding. The proposed techniques were tried utilizing the MIT-BIH dataset.