Analysis of esophageal atrial recordings through wavelet packets decomposition

In this paper the processing of esophageal atrial electrograms by means of wavelet packets (WP) decomposition is presented. WP is described as a flexible, signal-adaptive, tool, which can be easily tuned to enhance characteristics of esophageal signals. Two aspects are mainly investigated: (i) the possibility to obtain automatic, reliable detection of atrial activation in 24h Holter recordings and (ii) the development of an algorithm for discrimination between atrial flutter (AFLU) and atrial fibrillation (AF) episodes. WP decomposition was used as a framework for pre-processing the esophageal signal and to build a set of orthonormal sub-signals which can be selected and combined according to the signal processing task to be performed: (i) in the detection of atrial activation, sub-band signal characteristics were explored at different scales by using the modulus maxima criteria and (ii) in the discrimination between AFLU and AF the coarser approximation of the esophageal signal was studied by spectral analysis. A reliable detection of atrial activation was obtained (Sensitivity (SE): 99.08%; positive predictability (+P): 98.98%). In addition a quantitative index able to discriminate between AFLU (SE: 97.5%; +P: 98.7%) and AF (SE: 98.7%; +P: 97.5%) episodes was introduced.