Principal component analysis of atrial fibrillation: Inclusion of posterior ECG leads does not improve correlation with left atrial activity

Background Lead V? is routinely analysed due to its large amplitude AF waveform. V? correlates strongly with right atrial activity but only moderately with left atrial activity. Posterior lead V? correlates strongest with left atrial activity. Aims (1) To establish whether surface dominant AF frequency (DAF) calculated using principal component analysis (PCA) of a modified 12-lead ECG (including posterior leads) has a stronger correlation with left atrial activity compared to the standard ECG. (2) To assess the contribution of individual ECG leads to the AF principal component in both ECG configurations. Methods Patients were assigned to modified or standard ECG groups. In the modified ECG, posterior leads V? and V? replaced V? and V?. AF waveform was extracted from one-minute surface ECG recordings using PCA. Surface DAF was correlated with intracardiac DAF from the high right atrium (HRA), coronary sinus (CS) and pulmonary veins (PVs). Results 96 patients were studied. Surface DAF from the modified ECG did not have a stronger correlation with left atrial activity compared to the standard ECG. Both ECG configurations correlated strongly with HRA, CS and right PVs but only moderately with left PVs. V? contributed most to the AF principal component in both ECG configurations

Non-invasive acquisition of fetal ECG from the maternal xyphoid process: a feasibility study in pregnant sheep and a call for open data sets

Objective: The utility of fetal heart rate (FHR) monitoring can only be achieved with an acquisition sampling rate that preserves the underlying physiological information on the millisecond time scale (1000 Hz rather than 4 Hz). For such acquisition, fetal ECG (fECG) is required, rather than the ultrasound to derive FHR. We tested one recently developed algorithm, SAVER, and two widely applied algorithms to extract fECG from a single channel maternal ECG signal recorded over the xyphoid process rather than the routine abdominal signal. Approach: At 126dG, ECG was attached to near-term ewe and fetal shoulders, manubrium and xyphoid processes (n=12). FECG served as the ground-truth to which the fetal ECG signal extracted from the simultaneously-acquired maternal ECG was compared. All fetuses were in good health during surgery (pH 7.29+/-0.03, pO2 33.2+/-8.4, pCO2 56.0+/-7.8, O2Sat 78.3+/-7.6, lactate 2.8+/-0.6, BE -0.3+/-2.4). Main result: In all animals, single lead fECG extraction algorithm could not extract fECG from the maternal ECG signal over the xyphoid process with the F1 less than 50%. Significance: The applied fECG extraction algorithms might be unsuitable for the maternal ECG signal over the xyphoid process, or the latter does not contain strong enough fECG signal, although the lead is near the mother's abdomen. Fetal sheep model is widely used to mimic various fetal conditions, yet ECG recordings in a public data set form are not available to test the predictive ability of fECG and FHR. We are making this data set openly available to other researchers to foster non-invasive fECG acquisition in this animal model

Electrocardiography in horses, part 2: how to read the equine ECG

The equine practitioner is faced with a wide variety of dysrhythmias, of which some are physiological. The recording of an exercise electrocardiogram (ECG) can help distinguish between physiological and pathological dysrhythmias, underlining the importance of exercise recordings. The evaluation of an ECG recording should be performed in a highly methodical manner in order to avoid errors. Each P wave should be followed by a QRS complex, and each QRS complex should be preceded by a P wave. The classification of dysrhythmias according to their origin helps to understand the associated changes on the ECG. In this respect, sinoatrial nodal (SA nodal), atrial myocardial, atrioventricular nodal (AV nodal) and ventricular myocardial dysrhythmias can be distinguished. Artefacts on the ECG can lead to misinterpretations. Recording an ECG of good quality is a prerequisite to prevent misinterpretations, but artefacts are almost impossible to avoid when recording during exercise. Changes in P or T waves during exercise also often lead to misinterpretations, however they have no clinical significance