A new electrocardiogram (ECG) data compression method (CUSAPA) is pres
ented 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 at
tribute grammar is developed to locate the best initial spline knot lo
cations which will represent the S-Q segment. With an overall compress
ion ratio greater than four, the quality of the reconstructed signal i
s well suited for morphological studies when compared to some other te
chniques (FFT, FOI and SAPA). The proposed algorithm has shown a signi
ficant 50 Hz baseline noise reduction. Extensive computer results obta
ined with an ECG database have demonstrated the efficiency of the prop
osed algorithm.