Electrodynamic Model of the Heart to Detect Necrotic Areas in a Human Heart

To diagnose the conditions and diseases of the cardiovascular system is the main task of electrocardiology. The problem of the cardiovascular system diagnostics is caused by a complex multi-level mechanism of its functioning, and only experienced specialists are able to establish a correct diagnosis. Since the working heart is inaccessible to direct observations in real life, diagnostics of diseases is based on noninvasive methods such as electrocardiography. By assumption, weak "bursts" (micropotentials) of electrocardiographic signals in different areas are the precursors of dangerous arrhythmias. The amplitude of these signals on the body surface is insignificant and tends to be commensurate with the noise level of the measuring system. Advances in electrocardiography make it possible to generate a high resolution ECG signal and to detect the heart micropotentials. The method of modeling helps to understand causes of micropotentials in the ECG signal by selecting the model parameters. The model of the heart should allow generating a signal close to the high resolution ECG signal. The research aims to find a numerical model that allows solving the inverse problem of the heart tissue characteristics recovery using a high resolution ECG signal and CT data on the heart geometry. The proposed computer model and highly sensitive methods for the ECG measurement are the part of the hardware-software complex to detect dangerous precursors of cardiac arrhythmias

Advantages of Nanosensors in the Development of Interfaces for Bioelectric Prostheses

The present research aims to explore the bioelectric activity of muscles using a high-resolution electromyograph and to analyze the prospects of the electromyograph to develop bioelectric patterns for the prosthesis control method based on the data recognition system. The activity of the healthy forearm muscles was investigated during the cyclic activity of fingers in different modes. In addition, the impact of filters on the quality and informativity of myoelectric signals, as well as on the development of bioelectric activity patterns was analyzed. The virtually developed bandpass filters were utilized as experimental filters. The filter impact analysis included the comparison of the signal recorded in the frequency band from 0 to 10000 Hz with the signal filtered in the frequency band from 20 to 500 Hz. The research revealed the advantages of a high-resolution electromyogram for the pattern recognition-based myocontrol

Advantages of Nanosensors in the Development of Interfaces for Bioelectric Prostheses

The present research aims to explore the bioelectric activity of muscles using a high-resolution electromyograph and to analyze the prospects of the electromyograph to develop bioelectric patterns for the prosthesis control method based on the data recognition system. The activity of the healthy forearm muscles was investigated during the cyclic activity of fingers in different modes. In addition, the impact of filters on the quality and informativity of myoelectric signals, as well as on the development of bioelectric activity patterns was analyzed. The virtually developed bandpass filters were utilized as experimental filters. The filter impact analysis included the comparison of the signal recorded in the frequency band from 0 to 10000 Hz with the signal filtered in the frequency band from 20 to 500 Hz. The research revealed the advantages of a high-resolution electromyogram for the pattern recognition-based myocontrol

Effect of averaging of high-resolution cardiac signals in medical diagnostics using Simson's method

Simson's method employed in cardiological diagnostics detects the presence or absence of late ventricular potentials to indicate cardiac pathologies. It has been a long time since the development of Simson's method, but it is still used in clinics and is often mentioned in studies related to high-resolution ECGs and averaging of ECG signals. An optimal algorithm of high-resolution ECG averaging was chosen and implemented in this study. Efficiency of Simson's method was assessed on the cardiac signal recorded using a modern hardware and software complex. The result of the study showed no relationship between late ventricular potentials and localized micropotentials on the ST interval in individual cardiac pulses

Computer Spatially Oriented Reconstruction of A 3D Heart Shape Based on Its Tomographic Imaging

Diagnostics of cardiovascular system conditions and diseases is considered the most important task of electrocardiology. The aim of the study is to define geometric parameters of the patient heart and the synthesis of a realistic three-dimensional heart image based on a series of two-dimensional images obtained by computer tomography. The preparation and further processing of medical image data is an important initial step for further study of the heart electrodynamic activity. The problem is solved with the help of computer tomography method by preparing a series of images of the patient heart. The technique of volumetric rendering is applied to represent certain anatomical structures in a three-dimensional (3D) graphical form. It is concluded that the character of the obtained three-dimensional model of the patient heart is determined by the quality of the input data, the resolution of the tomograph, the tomographic slice thickness, the accuracy of the object boundaries determining the segmentation process and the peculiarities of medical image processing by the software applied

Wearable nanosensor-based hardware and software complex for dynamic cardiac monitoring

To date, continuous dynamic monitoring of the cardiovascular system is relevant for improvement of the quality of diagnosis of cardiac diseases. The equipment available for continuous cardiac monitoring operates in the standard frequency range, has a low resolution, and contains filters that limit signals in low and high frequencies. The development of wearable devices and high-resolution methods for dynamic cardiac monitoring to record signals in the range from 0 to 3500 Hz without filtering and averaging is of high priority. In addition, this will allow us to obtain new data on the atria and ventricles of the heart and to detect cardiovascular diseases at an early stage. A wearable hardware and software complex based on nanosensors was developed, and preliminary technical tests of the complex were carried out. An algorithm and a program were developed to detect micropotentials over the entire duration of the ECG signal except for the waves of cardiac pulses and sharp peaks in signal processing. Histograms were built for quantitative evaluation of micropotentials, and the total energy of micropotentials was calculated. Preliminary medical studies were carried out on volunteers

Advanced features of ECG mapping

Cardiovascular diseases are the leading cause of death worldwide. A great number of methods have been developed to monitor the state of the heart, each of which has its own advantages and limitations. One of the most promising method is surface mapping. To improve reliability and informativity of this method, researchers of Medical Engineering Laboratory of TPU developed nanosensors with unique metrological characteristics for non-invasive measurement of ECG signals of microvolt and nanovolt levels. The results of previous studies showed that metrological characteristics of the developed nanosensors significantly exceed those of conventional electrodes. Based on this, nanosensors used for surface ECG mapping will enable qualitative improvement of data obtained and diagnostic capabilities of this method