The Forward Problem of Electrocardiography: Theoretical Underpinnings and Applications

Gulrajani, R.M.

doi:10.1007/978-0-387-49963-5_2

Cited by 5 publications

(5 citation statements)

References 77 publications

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“…The analysis of ECG forward problems can be found in [ 27 ] while general considerations are described in [ 28 ]. According to the above-mentioned papers, the electric potential distribution,

, shortly assigned as

in the thorax, can be calculated using the partial differential equation [ 22 , 29 ]:

where:

and

denotes the cardiac source (so-called active currents). The current density that is normal to the thorax surface, S, also has to fulfill a boundary condition:

where n is a unit vector normal to S.…”

Section: Materials and Methodsmentioning

confidence: 99%

Non-Contact Monitoring of ECG in the Home Environment—Selecting Optimal Electrode Configuration

Bujnowski

Osinski

Przystup

et al. 2022

Sensors

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Capacitive electrocardiography (cECG) is most often used in wearable or embedded measurement systems. The latter is considered in the paper. An optimal electrocardiographic lead, as an individual feature, was determined based on model studies. It was defined as the possibly highest value of the R-wave amplitude measured on the back of the examined person. The lead configuration was also analyzed in terms of minimizing its susceptibility to creating motion artifacts. It was found that the direction of the optimal lead coincides with the electrical axis of the heart. Moreover, the electrodes should be placed in the areas preserving the greatest voltage and at the same time characterized by the lowest gradient of the potential. Experimental studies were conducted using the developed measurement system on a group of 14 people. The ratio of the R-wave amplitude (as measured on the back and chest, using optimal leads) was less than 1 while the SNR reached at least 20 dB. These parameters allowed for high-quality QRS complex detection with a PPV of 97%. For the “worst” configurations of the leads, the signals measured were practically uninterpretable.

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“…The analysis of ECG forward problems can be found in [ 27 ] while general considerations are described in [ 28 ]. According to the above-mentioned papers, the electric potential distribution,

, shortly assigned as

in the thorax, can be calculated using the partial differential equation [ 22 , 29 ]:

where:

and

denotes the cardiac source (so-called active currents). The current density that is normal to the thorax surface, S, also has to fulfill a boundary condition:

where n is a unit vector normal to S.…”

Section: Materials and Methodsmentioning

confidence: 99%

Non-Contact Monitoring of ECG in the Home Environment—Selecting Optimal Electrode Configuration

Bujnowski

Osinski

Przystup

et al. 2022

Sensors

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“…At myocardial location r and time instant t , equivalent current density J eq on each myocardial site can be defined as [30]…”

Section: Methodsmentioning

confidence: 99%

Temporal Sparse Promoting Three Dimensional Imaging of Cardiac Activation

Zhou

2015

IEEE Trans. Med. Imaging

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A new Cardiac Electrical Sparse Imaging (CESI) technique is proposed to image cardiac activation throughout the three-dimensional myocardium from body surface electrocardiogram (ECG) with the aid of individualized heart-torso geometry. The sparse property of cardiac electrical activity in the time domain is utilized in the temporal sparse promoting inverse solution, one formulated to achieve higher spatial-temporal resolution, stronger robustness and thus enhanced capability in imaging cardiac electrical activity. Computer simulations were carried out to evaluate the performance of this imaging method under various circumstances. A total of 12 single site pacing and 7 dual sites pacing simulations with artificial and the hospital recorded sensor noise were used to evaluate the accuracy and stability of the proposed method. Simulations with modeling error on heart-torso geometry and electrode-torso registration were also performed to evaluate the robustness of the technique. In addition to the computer simulations, the CESI algorithm was further evaluated using experimental data in an animal model where the noninvasively imaged activation sequences were compared with those measured with simultaneous intracardiac mapping. All of the CESI results were compared with conventional weighted minimum norm solutions. The present results show that CESI can image with better accuracy, stability and stronger robustness in both simulated and experimental circumstances. In sum, we have proposed a novel method for cardiac activation imaging, and our results suggest that the CESI has enhanced performance, and offers the potential to image the cardiac activation and to assist in the clinical management of ventricular arrhythmias.

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“…The analysis of forward ECG problem can be found in [26] while general considerations are described in [37]. According to above mentioned papers and [35] an electric potential field in the thorax could be calculated using the partial differential equation…”

Section: B Numerical Simulationsmentioning

confidence: 99%

“…The bioelectric phenomena are modeled as a quasi-static and linear problem and investigated using, for example, the Finite Element Method (FEM). As a result, it is possible to determine the potential distribution resulting from the electrical activity of the heart, both within and on the surface of the chest [26]- [28]. The accuracy of various approaches is discussed in [29] while the influence of material properties and geometry on the results of the ECG forward simulations is discussed in [30].…”

Section: Introductionmentioning

confidence: 99%

QRS Morphology-Based EDR Signal—Factors Determining its Properties

Przystup

Poliński²,

Wtorek³

2022

IEEE Access

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Respiration-induced signals contain a clinically significant information. It could be obtained utilizing both direct and indirect methods. ECG-Derived Respiration (EDR) method is the latter one. However, in this case, two approaches could be distinguished. First one is based on determining changes in the morphology of QRS complexes while the second one is based on the Respiratory Sinus Arrhythmia (RSA) mechanism. The former approach is discussed in the paper. The basic properties of QRS morphology-based EDR signal were evaluated by means of simulations performed using a developed FEM model and appropriate experiments. In effect, basing on changes of the leads' voltages induced by a heart translation or rotation, or by both mechanisms undergoing simultaneously, the sensitivity-like surfaces and the synthetic EDR signals were obtained. A very good agreement of the experimental and simulation results was achieved. The QRS morphology-based signal's properties strongly depend on geometrical relation of the used lead to dominating direction of the heart translation, its rotation, and on personal relation between these two mechanisms. The conclusions presented should be taken into account especially when developing or using QRS morphology-based approach in respiratory monitoring systems.INDEX TERMS Electrocardiography (ECG), ECG-derived respiration (EDR), respiration monitoring.

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The Forward Problem of Electrocardiography: Theoretical Underpinnings and Applications

Cited by 5 publications

References 77 publications

Non-Contact Monitoring of ECG in the Home Environment—Selecting Optimal Electrode Configuration

Non-Contact Monitoring of ECG in the Home Environment—Selecting Optimal Electrode Configuration

Temporal Sparse Promoting Three Dimensional Imaging of Cardiac Activation

QRS Morphology-Based EDR Signal—Factors Determining its Properties

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