An EMD-based ECG compression technique achieved an average compression ratio of 23.74:1 and a percent root mean square difference of 1.49, outperforming earlier methods.
Does an EMD-based compression technique improve compression ratio and PRD for ECG signals compared to earlier methods?
The proposed EMD-based ECG compression technique achieves a high compression ratio of 23.74:1 with a low PRD of 1.49, outperforming earlier methods.
Compression of bulky electrocardiogram (ECG) signal is a common requirement for most of the computerized applications. In this paper, a new compression and reconstruction technique based on Empirical Mode Decomposition (EMD) is proposed. The performance evaluation of the proposed technique is based on comparisons of Compression Ratio (CR) and Percent Root mean square Difference (PRD). The compression method consists of mainly five stages: EMD based signal decomposition, downsampling, discrete cosine transform (DCT), window filtering and Huffman encoding. The ECG signal reconstruction method follows the compression process in reverse order. The proposed algorithm is validated by testing on 48 ECG records available in MIT/BIH arrhythmia database. The compression efficiency is evaluated and the average values of CR and PRD are found to be 23.74:1 and 1.49, respectively. The experimental result shows that the proposed method achieves better compression ratio along with better PRD compared to earlier methods.
Sahoo et al. (Sun,) conducted a other in Arrhythmia (n=48). EMD-based compression and reconstruction technique vs. Earlier methods was evaluated on Compression Ratio (CR) and Percent Root mean square Difference (PRD). An EMD-based ECG compression technique achieved an average compression ratio of 23.74:1 and a percent root mean square difference of 1.49, outperforming earlier methods.