Multi-Channel Esophageal ECG Signal Classification

Overview

This study is designed to prove new methods to enable the automated analysis of esophageal electrocardiography (eECG) signals in long-term measurements as well as the detection of atrial fibrillation. The investigators hypothesis is that eECG signals allow the reliable atrial and ventricular ECG signal distinction and the detection of atrial fibrillation. Therefore 14 patients with arrhythmias and 6 cardiac healthy subjects are asked to take part in this study. On each subject an esophageal ECG and a simultaneous standard surface ECG will be taken for about half an hour. Patient undergoing a cardiac catheter ablation during their current hospitalization will be further asked to allow access to the invasively obtained measurements (i.e. atrial potential map) to further improve the understanding of the eECG signals.

Background The fast and correct diagnosis of heart rhythm disorders is very important to reduce morbidity and mortality in cardiovascular patients. Atrial fibrillation is of special interest, because it is an important cause of devastating brain strokes. A significant number of strokes have a cardioembolic genesis due to paroxysmal atrial fibrillation which was not diagnosed early enough. Therefore, it is very important to detect atrial fibrillation as soon as possible. With oral anticoagulation an effective therapeutic option in available to prevent cardioembolisms. In the clinical routine, mostly 24-hour or 7-day ECGs are made to look for cardiac arrhythmias. The use of such devices is well established. Nevertheless, they have some side effects/limitations. Skin electrodes used for derivation of the ECG often cause skin irritation, sometimes leading to premature termination of the recording. Because of dryout of the contact gel (causes artifacts), small p-waves and especially also motion artifacts, triggered recording or semi-automatic analysis of the recording is problematic, but for longer recording times such a semi-automatic analysis would be helpful. As an alternative esophageal electrocardiography can be performed. Signal quality of the ECG recording (especially of the left atrium) is better than in the standard surface ECG because of the vicinity of the esophagus and the left atrium. The esophagus tolerates well foreign bodies as the investigators know from long-term nasogastric intubation. Therefore use of the esophageal technique for long-term rhythm monitoring is an interesting and promising alternative to conventional surface Holter ECGs. Earlier studies have already shown the improved p-wave in eECG signals, but the automatic or semi-automatic wave analysis algorithms were not satisfactory. By increasing the number of measuring channels on the esophageal catheter, new classes of algorithm can be applied in order to increase the detection reliability. Using multiple channels to increase the quality of the result is an intuitive and widely used method e.g. in 12 lead ECG or EECG, etc. Objective Primary Objective: Differentiation of electrical atrial and ventricular cardiac activity (A/V classification) Secondary Objective: Detection of atrial fibrillation sequences (AFib Detection) Methods 20 subjects are included in this pilot study to verify enhanced multi-channel detection algorithm. In order to cover a wide variety of arrhythmias to test the algorithm with, the subjects are selected according to 4 categories: 1) 4 patients with intermitting or persisting atrial fibrillation. 2) 4 patients with atrial flutter 3) 6 patients with frequent atrial or ventricular extra-systoles. 4) 6 cardiac healthy subjects. In total around 50'000 heart beats are recorded. The surface ECG signal is used as the reference (manually analyzed). Sensitivity and specificity of the correctly detected atrial and ventricular activities compared to this manual reference including the 95% confidence intervals are calculated (A/V Classification). Additionally the sensitivity and specificity of the detected of atrial fibrillation sequences including the 95% confidence intervals are calculated (AFib Detection).