A new VCG signal compression technique based on discrete Karhunen-Loeve expansion and tunable quality wavelet transform

Abstract

This paper presents a novel two-stage compression technique for vectorcardiogram (VCG) signals, combining Discrete Karhunen-Loeve (K-L) Expansion and Tunable Q-Factor Wavelet Transform (TQWT). In the first stage, VCG signals undergo discrete K-L expansion and a secondary rotation to reduce variance caused by physiological factors, such as respiration and varying heart orientations among patients. This process effectively simplifies the dataset by leveraging eigenvector-based transformation, while standardizing the data across different VCG records. In the second stage, the standardized data is processed using TQWT, with finely tuned parameters (Q-factor of 4, redundancy factor of 1.2, and 6 stages), followed by quantization and Run-Length Encoding (RLE). The RLE method efficiently compresses the long sequences of zeros generated during the process, further enhancing the data reduction. The proposed method was rigorously evaluated using the PTB Diagnostic ECG Database, demonstrating remarkable compression efficiency. When compared with standard approaches like Discrete K-L Transform and Discrete Cosine Transform (DCT), the method achieved a superior average compression ratio of 15.43. Key evaluation metrics further highlight its efficacy, including an average Percent Root Difference (PRD) of 7.39 %, Fidelity of 99.72 %, Peak Signal-to-Noise Ratio (PSNR) of 37.38 dB, and a Quality Score (QS) of 2.13 %. Moreover, the method's rapid processing speed of 0.076 s per record makes it well-suited for real-time applications. This innovative approach provides an effective solution for VCG signal compression, enhancing the storage and transmission efficiency, while preserving high signal fidelity for clinical use.