| 摘要 |
This is a method and apparatus for the automated discrimination of cardiac events of interest, including P-waves, R-waves, T-waves, and specific arrhythmic sequences, in EGM signals for data storage in an implantable monitor or to control operations of an implantable cardiac stimulator through the use of Hidden Markov Modeling techniques and a reduced set of observations. The number of computations and computation time during a heart cycle is reduced by timing the frames of A-EGM samples to the detection of A-SENSE events by the atrial sense amplifier. The A-EGM sample frame is defined in a window preceding and following each A-SENSE event. The A-EGM sample frames are wavelet transformed, and a number of selected W.T. coefficients for each sample frame are saved in a buffer. Each set of saved W.T. coefficients therefore represents either a P-wave or an intrinsic or paced far field R-wave (including fusion beats) unless noise continuously causes A-SENSE events to occur. When the V-SENSE event occurs, an R-trigger is generated, and each set of saved W.T. coefficients is subjected to the HMM algorithm for a determination as to whether the preceding (and any concurrent) A-SENSE events from which the saved W.T. coefficients were derived are P-waves or R-waves. In addition, when the V-SENSE occurs, the HMM algorithm determines stochastically whether or not the successive sets of saved W.T. coefficients represent P-P sequences, far field R-R sequences or P-R sequences or the like.
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