For an ECG signal {x1, x2,…, xN} consisting of N timestamps, we create K state vectors. Each state vector \({\overrightarrow{s}}_{i}\) is an M-dimensional vector defined by: $${\overrightarrow{s}}_{i}=({v}_{i},{v}_{i+\tau },{v}_{i+2\tau },\ldots ,{v}_{...
These vectors represent \(m\) consecutive \(x\) values, starting with the \(i\) th point. The distance between \(X\left(i\right)\) and \(X\left(j\right)\), \(d\left[X\left(i\right),X\left(j\right)\right]\), is defined as the maximum absolute difference between their ...
Although often ignored, assessment of the electrical axis is an integral part of ECG interpretation. The electrical axis reflects the average direction of ventricular depolarization during ventricular contraction. The direction of the depolarization (and thus the electrical axis) is generally alongside the...
There are two ways to learn ECG interpretation—pattern recognition (the most common) and understanding the exact electrical vectors recorded by an ECG as they relate to cardiac electrophysiology — and most people learn a combination of both. This tutorial pairs the approaches, as basing ECG inter...
Since the exploring electrode and the reference is placed in the horizontal plane, these leads primarily observe vectors moving in that plane. Placement of chest (precordial) electrodes V1: fourth intercostal space, to the right of the sternum. V2: fourth intercostal space, to the left of the...
In the scenario of accurate detection of the QRS complex, after the R peak detection by the formation of the feature vectors under usage the amplitude of the significant frequency components of the DFT frequency spectrum [58]. By using the knowledge from the literature, categorized the ...
Another success story of the artificial neural network (ANN) as in Fig.8is to detect the most significant part of the ECG waveform (QRS complex detection). In the scenario of accurate detection of the QRS complex, after the R peak detection by the formation of the feature vectors under usa...
[12] used feature selection to select the most relevant features, where feature vectors were prepared by using wavelet transform coefficients and discrete Fourier transform spectrum extracted from the ECG signals. Swain et al. [37] used ECG signals to identify the presence of myocardial infarction ...
The parameters describing T wave shape (also utilized in the Feature Vectors), are obtained with regard to the local extremes time position (See FIG. 4 and also x1, x2, x3 in FIG. 7).T1, T2 and T3 points are calculated in the following way:...
Despite the wide literature on R-wave detection algorithms for ECG Holter recordings, the long-term monitoring applications are bringing new requirements, and it is not clear that the existing methods can be straightforwardly used in those scenarios. Our