Multiresolutional distributed filtering: A novel technique that reduces the amount of data required in high resolution electrocardiography

High resolution ECG analysis is widely accepted as the best non-invasive te chnique for the assessment of ventricular tachycardia risk in post-myocardi al infarction patients. However, the standard analysis approaches involve a n extensive averaging procedure which requires long data records, accompani ed by the consequent efforts for storage and transmission. This paper outli nes an algorithm for multiresolutional distributed filtering, that can sign ificantly reduce the necessary amount of data. The proposed filtering metho d comprises three basic steps: the dyadic wavelet transform computation, th e shrinkage of the wavelet coefficients using adaptive Bayesian rules, and the reconstruction of the denoised signal through the inverse wavelet trans form. The performance evaluation using controlled simulation experiments re vealed that the present technique could accelerate the noise reduction, pre serving the diagnostic value of the signals. (C) 1999 Elsevier Science B.V. All rights reserved.