Partial potentials of selected cardiac muscle regions and heart activity model based on single fibres

Janicki, Jerzy Stanisław; Leoński, W.; Jagielski, J

doi:10.1016/j.medengphy.2009.08.007

Cited by 2 publications

(6 citation statements)

References 17 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Moreover, the SSS is of significant prognostic importance: the correct result of the exercise perfusion test (very low SSS value) defines low-risk patients (death or infarction occurs in <1% of patients annually in several years of follow-up); the greater the stress test perfusion impairment, the greater the risk of cardiovascular events. To compare the effectiveness of SATRO ECG in the diagnosis of significant HM perfusion disorders, the SPECT (TOT2) study used 4 anatomical areas (interventricular septum and anterior, interior, lateral walls), each of which consisted of 4 segments [ 3 , 16 ].…”

Section: Methodsmentioning

confidence: 99%

“…In the formulas the values

) were calculated according to the Formulas (4)–(6):

where

and

denote the beginning and end of the appearing potentials with a cut-off point of

. Each of the part potentials is defined by two functions:

corresponding to the depolarization of a specific area of the left ventricular muscle, as shown in Figure 2 ., where

are the parameters calculated for part potentials treated as the norm with normal electrical activity [ 3 , 16 ].…”

Section: Methodsmentioning

confidence: 99%

“…The duration of part potentials

was calculated according to the following formulas:

and the value of the normalized duration was calculated from the relationship:

where:

determine the duration of each of the five potentials that appear during the depolarization of individual areas. In order to be able to assess the dynamics of depolarization, the J i coefficients (12) were introduced, which is the ratio of the value of the potential occurring in the final depolarization phase (U 2, i ) to the initial value (U 1, i ) in each of the analyzed areas, where i = (IS, AW, IW, LW, PW) [ 3 , 16 ].

…”

Section: Methodsmentioning

confidence: 99%

“…The method of imaging the variability of the electric potential generated by the heart is widely used in cardiological diagnostics as a functional test, e.g., to diagnose ischemic heart disease (IHD), the most common cause of which involves haemodynamic disorders caused mainly by obstructive coronary artery disease (CAD) [ 1 , 2 ]. However, the diagnostic efficiency of the ECG is unsatisfactory, because the current method of analyzing the measured potential does not allow one to recognize both the process of discrete stimulation of individual areas of the heart muscle (HM) and the potential occurring during the depolarization of individual parts of the effective HM fiber representing a specific area of HM [ 3 ]. In the current ECG studies, it is also difficult to determine the effect on the parameters of the potential of factors related to, for example, permanent loss of HM cell potential, disturbances in the intraventricular conduction system (ICS), or HM inflammation [ 4 , 5 ], which significantly reduces the effectiveness of IHD diagnosis using this tool.…”

Section: Introductionmentioning

confidence: 99%

“…The emerging problem of the efficiency of ECG (R) was the motivation to develop a new model of the electrical activity of the heart, using the idea of the effective working fibers SFHAM described in [ 3 ]. The practical implementation of this model was carried out using SATRO ECG software, which is a medical device [ 15 ], and the algorithms used in it enable the automatic calculation of the parameters of each of the five partial potentials that appear during the depolarization of left ventricular HM cells: the interventricular septum (IS) and the anterior (AW), inferior (IW), lateral (LW), and posterior (PW) walls [ 3 , 16 ]. The method of analyzing the resultant ECG (R) potentials with the use of SFHAM has already been described in detail in the patent application [ 17 ].…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Comparative Analysis of the Diagnostic Effectiveness of SATRO ECG in the Diagnosis of Ischemia Diagnosed in Myocardial Perfusion Scintigraphy Performed Using the SPECT Method

Janicki¹,

Leoński

Janicki³

et al. 2022

Diagnostics

View full text Add to dashboard Cite

There is a great need for early diagnosis of ischemic heart disease (IHD), the most common cause of which is haemodynamic disorders caused mainly by obstructive atherosclerosis of the coronary arteries. The diagnosis of IHD is usually made with the use of functional tests, which include resting ECG (R) or examination of significant perfusion disorders during exercise using the SPECT method. Despite the fact that the ECG (R) test is commonly used in cardiological diagnostics, it has a limited diagnostic value, especially in people with a low probability of coronary artery disease (CAD). In order to increase the effectiveness of the ECG (R) examination, SATRO ECG software, based on the single fibres heart activity model (SFHAM), was used to evaluate the electrocardiograms. The introduction of new classifiers from the available medical data to the analysis made it possible to evaluate the diagnostic efficacy of SATRO ECG (TOT) in predicting significant perfusion disorders in the exercise SPECT (TOT 2). These disorders are most often caused by obstructive atherosclerosis of the coronary arteries, which is the main cause of CAD. The database of 316 patients (219 men and 97 women, aged 57 ± 10 years) was analyzed using resting and stress ECG, perfusion scintigraphy performed using the SPECT method, and SATRO ECG analysis. The diagnostic efficacy parameters of SATRO ECG (TOT) in predicting significant perfusion abnormalities in the exercise-induced SPECT (TOT 2) study were: sensitivity, 99%; specificity, 91%; concordance, 96%; and positive, 96%, and negative, 97%, predictive values. The Kappa–Cohen coefficient was 0.92, and the statistical significance coefficient was p < 0.001. These results indicate a statistically significant agreement in the diagnosis of IHD in both diagnostic methods used.

show abstract

Section: Methodsmentioning

confidence: 99%

“…In the formulas the values

) were calculated according to the Formulas (4)–(6):

where

and

denote the beginning and end of the appearing potentials with a cut-off point of

. Each of the part potentials is defined by two functions:

corresponding to the depolarization of a specific area of the left ventricular muscle, as shown in Figure 2 ., where

are the parameters calculated for part potentials treated as the norm with normal electrical activity [ 3 , 16 ].…”

Section: Methodsmentioning

confidence: 99%

“…The duration of part potentials

was calculated according to the following formulas:

and the value of the normalized duration was calculated from the relationship:

where:

…”

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Comparative Analysis of the Diagnostic Effectiveness of SATRO ECG in the Diagnosis of Ischemia Diagnosed in Myocardial Perfusion Scintigraphy Performed Using the SPECT Method

Janicki¹,

Leoński

Janicki³

et al. 2022

Diagnostics

View full text Add to dashboard Cite

show abstract

Gk Based Fuzzy Clustering for the Diagnosis of Cardiac Arrhythmia

Mehdi

Zayegh

Begg

et al. 2010

Int. J. Comp. Intel. Appl.

View full text Add to dashboard Cite

Abstract-Cardiac arrhythmia is one of the major causes of human death, and most of the time it cannot be predicted well in advance at the right time. Computational intelligence algorithms can help in extracting the hidden patterns of biological datasets. This paper explores the use of advanced and intelligent computational algorithms for automated detection, classification and clustering of cardiac arrhythmia (CA). Application of Fuzzy C-Mean and Extended Fuzzy C-Mean method to the arrhythmia dataset (165 normal healthy and 138 with CA) demonstrated their good CA classification capabilities. Fuzzy C Mean algorithm was able to classify the two group of data set with an overall accuracy of 97.2% [sensitivity 96.4%, specificity 98.12% and area under the receiver operating curve (AUC-ROC = 0.963)]. The classification accuracy improved significantly when GK-based extended Fuzzy was employed, and an overall accuracy of 99.14% was achieved (sensitivity 97.11%, specificity 99.18% and AUC-ROC = 0.995). These accuracy results were respectively, 19.02%, 7%, 9.14% and 11.06% higher when compared to multi-input single layer perceptron (SLP), feed forward back propagation (FFBP), self organizing maps (SOM) and support vector machine (SVM). The performance measures of fuzzy techniques were found to be better if a Principal Component Analysis (PCA) technique was used to preprocess the arrhythmia datasets.

show abstract

Partial potentials of selected cardiac muscle regions and heart activity model based on single fibres

Cited by 2 publications

References 17 publications

Comparative Analysis of the Diagnostic Effectiveness of SATRO ECG in the Diagnosis of Ischemia Diagnosed in Myocardial Perfusion Scintigraphy Performed Using the SPECT Method

Comparative Analysis of the Diagnostic Effectiveness of SATRO ECG in the Diagnosis of Ischemia Diagnosed in Myocardial Perfusion Scintigraphy Performed Using the SPECT Method

Gk Based Fuzzy Clustering for the Diagnosis of Cardiac Arrhythmia

Contact Info

Product

Resources

About