Multichannel ECG compression using multichannel adaptive vector quantization.

Abstract

Adaptive vector quantization (AVQ) is a recently proposed approach for electrocardiogram (ECG) compression. The adaptability of the approach can be used to control the quality of reconstructed signals. However, like most of other ECG compression methods, AVQ only deals with the single-channel ECG, and for the multichannel (MC) ECG, coding ECG signals on a channel by channel basis is not efficient, because the correlation across channels is not exploited. To exploit this correlation, an MC version of AVQ is proposed. In the proposed approach, the AVQ index from each channel is collected to form a new input vector. The vector is then vector quantized adaptively using one additional codebook called index codebook. Both the MIT/BIH database and a clinical Holter database are tested. The experimental results show that, for exactly the same quality of reconstructed signals, the MC-AVQ performs better than single-channel AVQ in terms of bit rate. A theoretical analysis supporting this result is also demonstrated in this paper. For the same and relatively good visual quality, the average compressed data rate/channel is reduced from 293.5 b/s using the single-channel AVQ to 238.2 b/s using the MC-AVQ in the MIT/BIH case.