Computer analysis of the electrocardiogram during esophageal pacing cardiac stress
| Autor: | Hossein Jadvar, M. Schwaiger, J.M. Jenkins, Robert Arzbaecher, R.E. Stewart |
|---|---|
| Rok vydání: | 1991 |
| Předmět: |
Adult
Male medicine.medical_specialty RR interval Biomedical Engineering Electrocardiography QRS complex Esophagus Computer analysis Internal medicine Heart rate medicine Humans ST segment cardiovascular diseases Signal processing Atrium (architecture) medicine.diagnostic_test business.industry Cardiac Pacing Artificial Signal Processing Computer-Assisted Middle Aged cardiovascular system Cardiology Female business |
| Zdroj: | IEEE Transactions on Biomedical Engineering. 38:1089-1099 |
| ISSN: | 0018-9294 |
| DOI: | 10.1109/10.99072 |
| Popis: | It has been estimated that 15 to 30% of patients with suspected or known coronary artery disease are unable to perform an adequate exercise stress test due to a variety of reasons such as obesity, poor physical condition, claudication, etc. Transesophageal atrial pacing has been proposed as a noninvasive alternative for inducing cardiac stress in patients who cannot exercise. Although computer analysis is commonly employed to analyze the electrocardiogram (ECG) during the conventional exercise stress test, the surface ECG recorded during transesophageal atrial pacing is contaminated with large pacing artifacts which confound beat identification by standard computer software. We report the development of a robust signal processing algorithm for interpretation of the surface ECG during transesophageal atrial pacing stress. The algorithm employs novel schemes using both linear and nonlinear transformations to detect and differentiate between the pacing artifact and QRS complex even in difficult situations where the pacing artifact is in proximity to or superimposed on the QRS complex. The algorithm uses sophisticated logic for automatic recognition of sustained capture. It subsequently calculates beat-by-beat and average (over five beats) ST segment amplitude and slope. The algorithm also reports the instantaneous heart rate, RR interval, pace-to-R interval, R-wave amplitude, and estimated sinus node recovery time upon loss of sustained capture. The limitations of present exercise ECG computer methods in processing the ECG during transesophageal atrial pacing stress are evaluated and significantly improved performance by our algorithm is demonstrated. |
| Databáze: | OpenAIRE |
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