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Thе paper presents the inclusion of new innovative methods in medical education in Bulgaria. Recently, schools around the world have had to move to distance learning for their students. The use of modern technologies in the virtual classroom today is the most important part of the educational process. Effective modern devices, user-friendly platforms and appropriate educational pedagogical methods prove to be the key to excellent training. The inclusion of virtual teaching methods and serious educational games contributes to the conduct of high-level training and the formation of future medics of knowledge, skills and experience necessary for the formation of their professional qualities. The paper presents the results of a survey conducted among trainers and trainees at medical universities in Bulgaria. The analysis of the results shows the readiness of teachers and students to apply the methods of virtual learning and serious games in the educational process.

This article introduces an integrated photoplethysmographic (PPG) based cardiovascular monitoring system that consists of an individually portable PPG device for recording photoplethysmographic signals and a software system with a serverless architecture for processing, storing, and analyzing the obtained signals. The portable device uses the optical plethysmography technique for measuring blood volume in blood vessels. The device was tested and validated by a comparative analysis of three photoplethysmographic signals and one Electrocardiographic signal registered simultaneously in the target subject. The comparative analysis of these signals shows insignificant deviations in the obtained results, with the mean squared error between the studied signals being less than 21 ms. This deviation cannot affect the results that were obtained from the analysis of the interval series tested. Based on this result, we assume that the detected signals with the proposed device are realistic. The designed software system processes the registered data, performs preprocessing, determines the pulse rate variability, and performs mathematical analysis of PP intervals. Two groups of subjects were studied: 42 patients with arrhythmia and 40 healthy controls. Mathematical methods for data analysis in time and frequency domain and nonlinear methods (Poincaré plots, Rescaled Range Plot, Detrended Fluctuation Analysis, and MultiFractal Detrended Fluctuation Analysis) are applied. The obtained results are presented in tabular form and some of them in graphical form. The parameters studied in the time and frequency domain, as well as with the nonlinear methods, have statistical significance (p < 0.05) and they can distinguish between the two studied groups. Visual analysis of PP intervals, based on Poincare’s nonlinear method, provides important information on the physiological status of patients, allowing for one to see at a glance the entire PP interval series and quickly detect cardiovascular disorders, if any. The photoplethysmographic data of healthy individuals and patients diagnosed with arrhythmia were recorded, processed, and examined through the system under the guidance of a cardiologist. The results were analyzed and it was concluded that this system could serve to monitor patients with cardiovascular diseases and, when the condition worsens, a signal could be generated and sent to the hospital for undertaking immediate measures to stabilize patient’s health.

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The physiological signals that are recorded from different parts of the human body have a non-stationary nature and the tracking of their dynamics is an interesting research problem. This report examines Heart Rate Variability through the use of statistical methods of analysis that are traditionally used to study the functionality of the heart and via Detrended Fluctuation Analysis. The use of the technique of Detrended Fluctuation Analysis allows the investigation of short-term and long-term correlations in non-stationary Heart Rate Variability series. A study has been made of the changes in the functioning of the human heart, depending on the age. The study encompasses healthy individuals in three different age groups. The analysis of the obtained results shows a change in the correlated behavior of the investigated signals with an increase in age. UDC Classification: 612,

The paper presents frequency methods for estimating the variability of intervals between individual heart beats in Electrocardiogram. This parameter is known in the scientific literature as the Heart Rate Variability and with this method it is possible to make predictions about human health. Three frequency ranges have been studied: Very Low Frequency, Low Frequency, and High Frequency. The study in this paper was based on real cardiological data obtained from 33 patients suffering from heart fibrillations and 29 healthy individuals. The investigated records are obtained through a Holter monitoring of studied individuals in real life conditions. The obtained results show significantly lower values ​​of the tested spectral parameters in the diseased individuals compared to the healthy controls. The accomplished study shows the effective applicability of the spectral methods of Heart Rate Variability analysis and the possibility of differentiation by the spectral parameters of the patients from healthy individuals.

The article presents a methodology to support the process of correct cardiodiagnostics based on cardio signals recorded with modern optical photoplethysmographic (PPG) sensor devices. An algorithm for preprocessing registered PPG signals and the formation of a time series for the analysis of heart rate variability is presented, which is an important information indicator in the diagnosis of cardiovascular diseases. In order to validate the proposed algorithm, an experimental scheme for synchronous recordings of PPG and electrocardiographic (ECG) signals and the study of the accuracy of the registered signals was created. The obtained results show high accuracy of the studied signals in terms of the following parameters: number of QRS complexes/pulse waves and mean RR intervals/PP intervals and the finding that the proposed algorithm is suitable for preprocessing PPG signals, as well as the possibility of interchangeable use of PPG and ECG. The results of the mathematical analysis of heart rate variability by applying linear methods (Time-Domain and Frequency-Domain) to two groups of people are presented: healthy controls and patients with cardiovascular disease (syncope). After determining the values of the parameters of the methods used, in order to distinguish healthy subjects from sick ones, statistical analysis was applied using t-test and Receiver Operating Characteristics (ROC) analysis. The obtained results show that the linear methods used are suitable for analysing the dynamics of PP interval series and for distinguishing healthy subjects from those with pathological diseases. The presented research and analyses can find applications in guaranteeing correctness and accuracy of conducting cardiodiagnostics in clinical practice.

Heart rate variability (HRV) is a non-invasive marker for monitoring the physiological condition of patients and assisting in the diagnosis of cardiovascular disease. The aim of this study was to investigate the consistency between HRV parameters based on photoplethysmographic (PPG) and electrocardiographic (ECG) signals. Parameters from the linear analysis in the time domain were studied. The time domain indices are standardized and widely used to calculate HRV. These indices are statistical and geometric measurements. The statistical calculations of the successive heart rate intervals (RR interval series) are strictly interrelated (SDNN, SDANN, RMSSD, pNN50), while geometric measurements are based on TINN and HRVTi parameters. The ECG and PPG signals of a healthy individual were examined. The obtained results show a very good agreement between the HRV parameters obtained from the two types of signals. In view of this finding, it can be concluded that the PPG offers an alternative ECG option for HRV analysis without compromising accuracy. The correspondence between the studied parameters applied to the two types of signals provides potential support for the idea of using PPG instead of ECG in the extraction and analysis of HRV in outpatient cardiac monitoring of healthy individuals and patients with cardiovascular disease. A study of two groups of individuals: healthy and with cardiovascular disease based on PPG signals by applying the method: analysis in the time domain. The obtained results show that with the used method the two studied groups of subjects can be distinguished.