ECG data compression via cubic-splines and scan-along polygonal approximation

Abstract

Abstract A new electrocardiogram (ECG) data compression method (CUSAPA) is presented in this paper. It applies the scan-along polygonal approximation (SAPA) algorithm on the QRS complex of the ECG waveform and the cubic-splines approximation to the S&−Q segment. This method requires a QRS detector as preprocessor to filter out the QRS complex portions. An attribute grammar is developed to locate the best initial spline knot locations which will represent the S−Q segment. With an overall compression ratio greater than four, the quality of the reconstructed signal is well suited for morphological studies when compared to some other techniques (FFT, FOI and SAPA). The proposed algorithm has shown a significant 50 Hz baseline noise reduction. Extensive computer results obtained with an ECG database have demonstrated the efficiency of the proposed algorithm.