Development of a compression algorithm suitable for exercise ECG data

Huge amount of data recorded during exercise electrocardiography may be stored for further analysis or be transferred to a remote physician through telephone lines. Due to channel limitations, data must be compressed prior to the transfer, In this study, an algorithm suitable for compression of exercise electrocardiography data is proposed. 2-D discrete cosine transformation is applied in the algorithm to make use of the pseudo periodic behavior of the data. To increase the correlation, data is aligned from the R peaks. QRS detection is performed using a fast dyadic wavelet transform. The success rate of the detection algorithm is found to be 99.78%. Uniform scalar quantization is used with a zonal coding method in the coding of 2-D discrete cosine transform coefficients. The performance of the compression algorithm is evaluated in terms of compression ratio, reconstruction error and by comparing the reports of the ST segment depression test applied before the compression and after the reconstruction to inspect whether vital information is preserved.