Heart rate variability (HRV) from recorded electrocardiograms (ECG) is a well-known diagnostic method for the assessment of autonomic nervous function of the heart, which is widely used to predict clinically relevant outcomes in the critical care setting, to risk stratify patients, and predict outcomes such as mortality. The morphological variations in the ECG waveform and the high degree of heterogeneity in the QRS complex often make it difficult to identify R waves, which may preclude the accurate analysis for HRV. Photoplethysmographic (PPG) signal can provide information about both the cardiovascular and respiratory systems and have extremely high degree of correlation with ECG during cardiac cycle. In this paper, we developed robust algorithm for high-resolution inter-beat waveform extraction using combined ECG and PPG analysis, which is highly needed for accurate HRV estimation. The simulation results showed high performance for inter-beat waveform detection in different cases that identifies missing/extra peaks in the QRS detection algorithm.
Введение. На современном этапе развития медицинских технологий произошли кардинальные изменения в области диагностической визуализации внутренних органов и тканей человека. Сегодня в Российской Федерации более половины всех диагнозов устанавливаются на основании результатов применения методов неинвазивной лучевой медицинской диагностики (НЛМД) [1].В настоящее время в клинической практике используются следующие методы НЛМД, каждый из которых обладает своими преимуществами и недостатками [2]: рентгенодиагностика; ультразвуковое исследование; компьютерная томография; магнитно-резонансная томография; радионуклидная визуализация.Предлагаемый новый метод НЛМД функционального состояния органов и тканей человека на основе применения неинвазивных методов микроволнового зондирования и визуализации (НММЗВ) в неионизирующей области электромагнитного спектра, реализуемых на практике с помощью использования адаптивной цифровой антенной
Requirements for perspective medical system for non-invasive radiation diagnostics of functional state of biological organs and tissues, based on application of microwave sensing techniques, practically implemented in a smart antenna array, are synthesized. Estimates of characteristics of beam pattern and gain factor for the simulated smart antenna array meet the requirements for microwave medical imaging applications. A perspective diagnostic microwave imaging system is supposed to have high functional characteristics, enabling the possibility of precise imaging of biological organs and tissues without using contrast agents, and at a lower cost, compared with existing X-ray, magnetic resonance and positron emission tomography systems on the market.
An important practical problem is a personalized selection of characteristics and parameters of intravascular frame to reduce traumatism of inner lining artery - the intima, which, in turn, reduces the instent restenosis. The solution of this problem is due to the phase calculation biomechanical model of the vessel with its stenosed area and implantable stent in accordance with the mechanical and geometric parameters of the pathophysiological characteristics and conditionally normal plots of the artery. The article presents the techniques and methods selection of the geometric characteristics of the stent, the pressure in the balloon used for intravascular angioplasty, taking into account the individual characteristics of the patient´s coronary artery. The selection me-thods are based on biomechanical models of intact areas of the coronary arteries, the parameters were taken from the available references. As the study results are data obtained in simulation of balloon dilation and stenting of the coronary arteries.
The presented calculations require biomechanical computer models of axisymmetric and non-axisymmetric stenosed intact aras of the coronary arteries, as well as biomechanical models commonly used stents and dilatation balloon catheters for interventional procedures on coronary arteries.
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