Intraindividual variability in electrocardiograms

An in-silico analysis of the effect of heart position and orientation on the ECG morphology and vectorcardiogram parameters in patients with heart failure and intraventricular conduction defects

“…We chose to shift the electrodes up to 3 cm, as it was found in clinical practice that the average distance from the actual electrode position to the prescribed location was 2.9 cm [7]. However, VCG parameter alterations after shifting the electrodes by such small amounts were minimal in our results (− 17% and + 8%).…”

“…The influence of geometrical factors on ECG parameters has been extensively investigated in the past [5][6][7]19], but the influence of geometry on QRS morphology and VCG parameters has not been studied before in patients with wide QRS complexes. Our results, based on an in-silico approach using patient-specific geometries, demonstrate that morphological features of the ECG (in particular notching/slurring and ID-time) and voltage-dependent VCG parameters (QRS amplitude, QRS area, T-wave amplitude, and T-wave area) are severely affected by geometry modifications, influencing the diagnosis of LBBB.…”

“…Moreover, ventricular enlargement, as noted in heart-failure (HF) patients, may rotate the heart around the anteroposterior axis to a more horizontal orientation [7]. All these factors may affect the interpretation of the ECG and the diagnosis of cardiac pathologies, and possibly influence indication to device therapy [8].…”

Fast, accurate and easy-to-teach QT interval assessment: The triplicate concatenation method

“…Three main sources of variability of QT assessment have been identified: inter-reader variability, intra-reader variability and intrinsic beat-to-beat QT variability. Triplicate ECGs and median beat were introduced to reduce the intrinsic beat-tobeat variability [16,17] and ECG signal to noise ratio [18]. Finally, semi-automated computerassisted methods using the generation of a superimposed median beat have shown good reproducibility in terms of intra and inter-reader variability [19].…”

Electrocardiogram Signal Compression with Reconstruction via Radial Basis Function Interpolation Based on the Vertex

“…A high performance processor with mass storage is necessary to precisely digitize the ECG data, which leads to the difficulty in developing portable ECG devices because of limited resources. In addition, the ECG data must be managed with efficiency for long-term monitoring of the patient's heart condition [1][2][3]. Therefore, data compression needs to be employed for efficient storage, processing and transmission.…”