Reconstruction of Compressed VCG Signal Using Cubic Spline Interpolation

This paper presents a new technique based on Discrete Wavelet Transform (DWT) utilizing wavelet filter and spline interpolation for Vectorcardiogram (VCG) signal compression. In this method, the VCG signal is first smoothed by harnessing a Savitzky–Golay filter and then processed by a wavelet filter made with Daubechies-4 (Db-4). Thresholding of transformed coefficients is performed to further increase compression, followed by signal reconstruction applying Inverse Discrete Wavelet Transform (IDWT). Spline interpolation is used to enhance reconstruction quality. The simulation results obtained demonstrate the robustness of the proposed method in terms of several performance-measuring metrics, such as compression ratio (CR), percent root-mean-square difference (PRD), signal-to-noise ratio (SNR), peak signal-to-noise ratio (PSNR), retained samples (RS) and quality score (QS). A comparative study of the proposed approach is also made with Discrete Cosine Transform (DCT), Fast Fourier Transform (FFT) and different wavelet-filters such as Db-2, Db-10, Coiflet and Haar for VCG signal compression to evaluate their effectiveness in preserving diagnostic details while achieving a higher CR at lower PRD, and accurate signal reconstruction. It is evident from the performance metrics that the proposed method using Db-4 wavelet filter yields the best performance, obtaining a CR of 33.05, at a PRD of 2.8069% along with 32.73 SNR, PSNR of 38.00 with a similarity of 0.9979, a QS of 16.67 and a least RS of 310. Hence, the Db-4 wavelet is an ideal choice for high-precision medical diagnostics and long-term monitoring, where accuracy is paramount as compared to other wavelets, DCT and FFT, as it offers the best results over various performance metrics.