Automated ECG analysis during esophageal pacing stress

Present computer methods for automated processing of the exercise electrocardiogram (ECG) are inadequate in analyzing the surface ECG during cardiac stress induced by transesophageal atrial pacing. This is due to the presence of large pacing artifacts which confound the commonly used R-wave detection logic. The authors have devised a signal processing algorithm which deploys separate schemes for detection of pace artifacts and R waves and hence rectifies this difficulty. The algorithm is able to distinguish between pace artifacts and R waves even in difficult situations where the pace artifact is very close to or superimposed on the QRS complex. The algorithm calculates beat-by-beat and averaged ST segment level and slope, R wave amplitude, instantaneous heart rate, RR and pace-R intervals, as well as sinus node recovery time on loss os sustained capture. The authors have demonstrated the inadequacy of the current computer methods in processing the ECG during esophageal pacing stress and the dramatically improved performance of the algorithm on real ECG data.<
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