ECG signal processing: Lossless compression, transmission via GSM network and feature extraction using Hilbert transform

Abstract

Software based new, efficient and reliable lossless ECG data compression, transmission and feature extraction scheme is proposed here. The compression and reconstruction algorithm is implemented on C-platform. The compression scheme is such that the compressed file contains only ASCII characters. These characters are transmitted using internet based Short Message Service (SMS) system and at the receiving end, original ECG signal is brought back using just the reverse logic of compression. Reconstructed ECG signal is de-noised and R peaks are detected using Lagrange Five Point Interpolation formula and Hilbert transform. ECG baseline modulation correction is done and Q, S, QRS onset-offset points are identified. The whole module has been applied to various ECG data of all the 12 leads taken from PTB diagnostic ECG database (PTB-DB). It is observed that the compression module gives a moderate to high compression ratio (CR=7.18), an excellent Quality Score (QS=312.17) and the difference between original and reconstructed ECG signal is negligible (PRD=0.023%). Also the feature extraction module offers a good level of Sensitivity and Positive Predictivity (99.91%) of R peak detection. Measurement errors in extracted ECG features are also calculated.