Electrocardiography signal compression using non-decimated stationary wavelet transform-based technique

Abstract

Abstract Background. In telecardiology, the bio-signal acquisition processing and communication for clinical purposes occupies larger storage and significant bandwidth over a communication channel. Electrocardiograph (ECG) compression with effective reproductivity is highly desired. In the present work, a compression technique for ECG signals with less distortion by using a non-decimated stationary wavelet with a run-length encoding scheme has been proposed. Method. In the present work non-decimated stationary wavelet transform (NSWT) method has been developed to compress the ECG signals. The signal is subdivided into N levels with different thresholding values. The wavelet coefficients having values larger than the threshold are evaluated and the remaining are suppressed. In the presented technique, the biorthogonal (bior) wavelet is employed as it improves the compression ratio as well percentage root means square ratio (PRD) when compared to the existing method and exhibits improved results. After pre-processing, the coefficients are subjected to the Savitzky-Golay filter to remove corrupted signals. The wavelet coefficients are then quantized using dead-zone quantization, which eliminates values that are close to zero. To encode these values, a run-length encoding (RLE) scheme is applied, resulting in compressed ECG signals. Results. The presented methodology has been evaluated on the MITDB arrhythmias database which contains 4800 ECG fragments from forty-eight clinical records. The proposed technique has achieved an average compression ratio of 33.12, PRD of 1.99, NPRD of 2.53, and QS of 16.57, making it a promising approach for various applications. Conclusion. The proposed technique exhibits a high compression ratio and reduces distortion compared to the existing method.