Vector quantization for compression of multichannel ECG.

Abstract

We propose a scheme based on vector quantization (VQ) for the data-compression of multichannel ECG waveforms. N-channel ECG is first coded using m-AZTEC, a new, multichannel extension of the AZTEC algorithm. As in AZTEC, the waveform is approximated using only lines and slopes; however, in m-AZTEC, the N-channels are coded simultaneously into a sequence of N + 1 dimensional vectors, thus exploiting the correlation that exists across channels in the AZTEC duration-parameter. Classified vector quantization (CVQ) of the m-AZTEC output is next performed to exploit the correlation in the other AZTEC parameter, namely, the value-parameter. CVQ preserves the waveform morphology by treating the lines and slopes as two perceptually-distinct classes. Both m-AZTEC and CVQ provide data-compression and their performance improves as the number of channels increases. Moreover, the final output differs little from the AZTEC output and hence ought to enjoy the same acceptability.