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ERG is a biopotential response of various retinal cells formed by visual stimulation with a bright flashlight. The retina produces an appropriate response which is depending on the visual stimulation conditions. To ensure uniform flash intensity throughout the patient's field of view, the patient's chin is placed on a special ganzfeld platform. This installation realizes the uniformity of light stimulation distribution. During the examination, the patient looks at one point indicated in the ganzfeld. Flash intensity replacements are routinely regulated by the ISCEV standard, however, this study used standard EP-1000 (Tomey GmbH) protocols. Filtering is a key part of signal analysis. In accordance with the requirements of the standard, the filtration of (ERG) signals should be implemented using a posteriori methods. The source of this recommendation is the complex waveform and the presence of frequency components of different private ranges. Thus, this study described the selection of the optimal filtering method for the Maximum 2.0 ERG Response signal based on the posteriori method. The study used the original biomedical signals of adult patients previously published on the IEEE DataPort.

ERG is a biopotential response of various retinal cells formed by visual stimulation with a bright flashlight. The retina produces an appropriate response which is depending on the visual stimulation conditions. To ensure uniform flash intensity throughout the patient's field of view, the patient's chin is placed on a special ganzfeld platform. This installation realizes the uniformity of light stimulation distribution. During the examination, the patient looks at one point indicated in the ganzfeld. Flash intensity replacements are routinely regulated by the ISCEV standard, however, this study used standard EP-1000 (Tomey GmbH) protocols. Filtering is a key part of signal analysis. In accordance with the requirements of the standard, the filtration of (ERG) signals should be implemented using posteriori methods. The source of this recommendation is the complex waveform and the presence of frequency components of different private ranges. Thus, this study described the selection of the optimal filtering method for the Maximum 2.0 ERG Response signal based on the posteriori method. The study used the original biomedical signals of adult patients previously published on the IEEE DataPort.

In this paper, we discuss accelerometry: an approach to human activity recognition and functional state assessment based on the usage of inertial sensors. Our discussion summarizes the pivotal aspects of accelerometric research, intending to provide an overview for the beginner practitioners in the field. Covered topics include signal processing techniques and machine learning algorithms, as well as general pointers to relevant literature.

To date, electrophysiological research (EPR) remains an important source of objective assessment of the visual analyzer functional state. The ability to exclude the EPR subject subjectivity is no doubt an attractive advantage of EPR. In particular, an essential advantage is the functional topographic assessment of the malfunction of the visual analyzer systems. Localized electrophysiology of the vision organ is submitted by a variety of methods for recording the biomedical signals. High complexity and many confounder factors during signal receiving may be complicated by the final result analyzing given by ranging from stimulation parameters to the state of the patient himself. Differential diagnosis, preclinical toxicology, and scientific and experimental models are the main emphasis of EPR. Potential prospects of EPR provide new opportunities for effective implementation of multifocal electroretinography. Classical EPR does not provide detailed and quantitative information about the state of the visual analyzer. This implies the need to optimize and algorithmize assessment data of ophthalmic pathology, even more than before, environmental concerns differentiated criteria inherent into a particular ocular pathology. This article presents literature review of electrophysiological methods in ophthalmology and the processing of electroretinograms using wavelet transform. To efficient processing of electroretinograms, it is necessary to separate the high-frequency and low-frequency components from the experimental signal. The low-frequency component is an oscillatory response or oscillatory potentials generated by the cells of the inner layers of the retina. This article notes the need to vary the basis functions of the wavelet transform and the methods of time-frequency analysis based on the results of electroretinograms processing.

Photoplethysmogram is an image of blood flow changes in the human body. It isn’t a simple shape signal rather it has at least six principle parameters form who derivate another useful. In the last decade, the PPG was exploited in order to extract more useful information about physiologic parameters. The current paper will focus on the blood flow velocity where this feature has a major implication in the blood mixer device. It needs to constantly monitor the transfused blood volume with the most accurate level. In transfusiological practice, special attention is paid to the accuracy of donation. The accuracy of donation means the correlation of a given volume and the resulting volume of the blood bag. Therefore, implementing the PPG principle to this device it can offer a good advantage at measuring the blood flow. This article is part of the work devoted to the modernization and development of new equipment for transfusion therapy based on LLC Lidkor production.

The photoplethysmography technique take advantage of the pulsatile phenomena inside the cardiovascular system. In addition, the blood volume can be discriminated from the sourounding tissues because of its optical reflectance property under a certain wavelengh of light source. In medical systems that used blood for donation the setup of apparatus can made the optimum environment to apply the photopletysmography tecnique. Therefore, in the presented paper the estimation of blood flow rate is determined by applying the described technique. This measurement can increase the redundance of electronical part that monitor the blood flow during the transfusion operation. The actual method that calculate the previous parameter is based on the mass sensor however, in the event of the inoperability of the force sensor, the mass of the blood packet may be greater or less than a predetermined volume. The article discusses possible options for the passage of blood flow through the tube, as well as modeling the real process of donation. It is part of the work devoted to the modernization and development of new equipment for transfusion therapy based on LLC Lidkor production.

In this paper design of competencies ontology for the analysis of educational programs are presented. An analytical review of papers on the subject are shown. The methodology of the process of collecting and analyzing professional and personal qualities is proposed. Processes collection, processing and analysis of data of professional and personal qualities are given. The development of a methodology for mapping the curriculum of a higher education into an ontological model are presented. Data on the requirements for a degree programmer are collected. An ontology of required competencies in this specialty is created. Example an ontology of key-skills for the profession ”Programmer” is depicted. Options for the compositions of all the qualities collected are represented. Practical implementation of the transition and the combination of research dealing with market analysis and research dealing with dynamic changes in education are described. Next, the resulting lists of professional qualities and personal qualities will be classified into generalized groups.

In existing systems for blood donation, flow rate estimation is implemented using various force sensors. However, in the event of the inoperability of the force sensor, the mass of the blood packet may be greater or less than a predetermined volume. This fact leads to the improper storage of blood and its components, which means that blood products can be spoiled. Thus, it is necessary to develop duplicate systems to control blood flow velocity. This article presents a PPG-based blood flow rate estimation method. Photoplethymogram, known as abbreviated PPG, is an image of blood flow changes in the human body. It isn’t a simple shape signal rather it has at least six principle parameters form who derivate another useful. In the last decade, the PPG was exploited in order to extract more useful information about physiologic parameters. The article discusses possible options for the passage of blood flow through the tube, as well as modeling the real process of donation. This article is part of the work devoted to the modernization and development of new equipment for transfusion therapy based on LLC Lidkor production.

The aim of the article is to evaluate the applicability of multifractal methods to the analysis of biomedical signals. Among the known methods of multi- and monofractal formalism for the evaluation of short-term biomedical signals, the multifractal fluctuation (MFDFA) and cross-correlation (MFCCA) analysis approaches are of the greatest interest. In the article, we have evaluated the accuracy of the MFDFA and MFCCA approaches with the use of model time series of fractal Brown motion for certain Hurst exponent values. Next, model studies on stability assessment of the multifractal estimates in case of noise addition for investigation of the evaluation dependency on the different features of the modeled time series are considered. Peculiarities of application of multifractal analysis to simultaneously recorded biomedical signals are shown. Analysis of MFDFA and MFCCA approaches by the model signals have shown that such approaches can be applied to the assessment of short-term biomedical signals of the multichannel Radiophysical complex MRTHR.

In this paper, we review the state of biofeedback methodology 50 years after its inception, with the objective to facilitate well-informed, scientific discourses around the topic. The scope of our review is limited to quantitative analysis of body of work published over the last decade, from which it is evident that biofeedback experiences a major methodological shift - away from strictly confined medical and research facilities, and towards personal, consumer-level use, thanks to wireless gadgets, wearables and smart devices available en masse. With such change come new opportunities and challenges, in the form of technological aspects, such as data processing trade-offs, efficiency of sensor placement, modalities and architectures, as well as general effectiveness of biofeedback in novel application areas, surrounded by privacy concerns and implications of e-health mobile technologies, which already available, but not yet ready for the prime-time. It is our intent to reflect on this liminal state of affairs.

Student trajectory - the main stages of training related to the choice: from admission to deduction. Student expulsion can be caused by various reasons. The main reasons are expulsion due to graduation from the university and academic failure. There are works that use various data to predict student expulsion: Demographic, Academic, Social and Behavioural in social networks. The peculiarity of this study is the use of data on the choice of a student in the formation of his individual trajectory. In paper the data model of the student and use-cases of the information system for students track prediction were considered. Impersonal data of 5000 bachelors from Ural Federal University formed a features space, including data on education, data on student track formation behavior and data on the social context. A model for predicting the trajectory of a student was developed. The proposed system can be adapted to the processing of data to form a competence portrait of student. On basic level, the system can be used to predict probability of a student being expelled from a University

This paper presents the modeling of an information system for collecting and processing data for the implementation and support of modular educational programs in the University. Features using modern educational technologies, including a personalized approach are described. The proposed system is called the “Digital Tutor” System. Use cases, functionality and service integration scheme are shown. The paper shows that this will allow informing students and receiving feedback from students about the learning conditions in the educational program.

This paper discusses the option of hardware-software integration, according to the assessment of human cognitive potential. The presented complex is based on an assessment of the integrative activity of the brain that allows one to get an idea of the current state of relations between the different areas of the brain structures (i.e., allows numerically estimate the number of structures involved in the activity). Evaluation of the integrative activity performed by a coherent analysis of the patient's EEG. The analysis is performed in real time using module coherent analysis developed in OpenVibe software.

In this research, we hypothesize that head-mounted accelerometric sensors can be effectively utilized in the tasks of motion activity classification and balance control evaluation, on a par with conventional methods based on stabilometric platforms. Following this hypothesis, we carried out a series of short experiments with stabilometric system "Stabilan-01-2" and consumer-grade tri-axial accelerometer. Collected motion signals were batch-processed and passed through feature extraction pipeline. After that, characteristic spaces were formed and classified using statistical machine learning methods. Results of the classification indicated that feature space of accelerometric data is informative enough to accurately classify motion activity associated with balance control, thus confirming our initial hypothesis. These results demonstrate that accelerometers can be used as a low-costly and portable alternative to stabilometric systems, and suggest a promising and novel approach to balance control assessment. © 2019 Author(s).

The Brain-Computer Interface (BCI) can be used for evaluation of the state of individuals during everyday routines. As shown in previous works, there is a relationship between the BCI multimodal metric with functional states of human. We have used power of Theta, Alpha, Beta low and Beta high electroencephalography rhythms and head motion data signals for multimodal metric. Heart Rate Variability (HRV) is common medical method for functional state assessment. In this paper the results of interrelation estimation between multimodal metric and HRV are shown. We used Pearson correlation coefficient (PCC) for estimates of interrelation between multimodal metric and HRV. It was found, the best results for estimates of parasympathetic part of the autonomic nervous system and suprasegmental regulation HRV have value of PCC more then critical value for Pearson correlation. © 2019 by SCITEPRESS - Science and Technology Publications, Lda. All rights reserved. The work was supported by Act 211 Government of the Russian Federation, contract № 02.A03.21.0006.

This paper discusses the possibility of development and testing a special methodology for the formation of a dynamic competence space. The main object of study is a student. The proposed methodology can take into account the risks of an erroneous assessment of the competences of an object, and it is also quickly adaptable and scalable. This paper presents a synthesis of methodology. Seven hypothetical ways of assessing and constructing skills space are considered.

In paper different standards for intelligent medical systems and multimodal architecture interfaces are under review. Application of Fast Healthcare Interoperability Resource (FHIR) standard for data model of intelligent multimodal interface are proposed. Intelligent multimodal interface for EEG and accelerometer bio-signals based on FHIR are shown. Use case diagrams, resource diagrams and class diagrams for production and research mode of this interface are described.

The estimation in real time of the functional and mental state level for the athlete during the loads is essential for management of the training process. New multimodal metric, obtained by means of the brain-computer interface (BCI), is proposed. The paper discusses the results of the joint usage of data from Emotiv EPOC+ mobile wireless headset. It includes motion sensors (accelerometer) and EEG channels. The features of the Emotiv EPOC+ interface allow to record the deviation of the head from the body axis, which provides an additional channel of information about the physical and mental (psycho-emotional) state of the athlete. Based on this data a new multimodal metric is calculated. Approbation of the metric was performed for functional stress studies on group of 10 volunteer subjects, including evaluations of the TOVA-test and the hyperventilation load. The joint application of different signals modalities allows to obtain estimates level of attention for these functional studies.

In the paper possibilities of functional research complex for mental status evaluation are shown. The complex consists of neuroheadset Emotiv Epoc+, including 14 channel wireless EEG-system with accelerometer, and ECG-recorder for acquisition of the heart rate variability signals (HRV). The record of biomedical signals was obtained in several functional states for 10 healthy subjects: Background (functional rest), TOVA-test (mental load), Hyperventilation (physical load) and Aftereffect (after test state). It was found that the power of the very low-frequency component of the HRV spectrum was significantly changed, which is caused by infiuence of the suprasegmentally regulation level on the heart rhythm. Also, the decrease in the control effect of the cerebral cortex (α-rhythm activity) is registered. At the same time, the amplitude of the average accelerometer values increases as result of uncontrolled movements in order to find the most stable position of the head relative to the gravitational vector.