Wavelet transform based algorithms for EGM morphology discrimination for implantable ICDs

New wavelet transform based EGM morphology discrimination algorithms for implantable ICDs are presented. The algorithms are similar to correlation waveform analysis (CWA) and area of difference (AD) but computations are performed in the wavelet domain. The use of the wavelet transform allows more efficient signal processing due to its information compression and filtration properties. Also, wavelet coefficients corresponding to different time scales are weighted to reflect the relative importance of corresponding time scales for EGM morphology discrimination and to facilitate the computation. The algorithms have been implemented in ICD firmware and are capable of processing morphology at up to 250 beats per minute. Holter data analysis showed that morphology measurements were stable over 48 hours of electrogram recording