ECG data compression by multiscale peak analysis

The paper presents an ECG data compression technique using multiscale peak analysis. The authors define multiscale peak analysis as the wavelet maxima representation of which the basic wavelet is the second derivative of a symmetric smoothing function. The wavelet transform of an ECG shows maxima at the start, peak and stop points of five transient waves P through T. The number of wavelet maxima is expected to be less than the number of original data samples. The wavelet maxima can be enough to reconstruct original signals precisely. The wavelet maxima representation can lead to ECG data compression and analysis. The compressed data still keep the peaks of QRS waves, and abnormal behavior search will be feasible in practice. The result of the compression shows that a normal ECG data is compressed by a factor 10