Computation of Time Series Scaling Exponent for Electricity Prices Forecasting

Popovska, Ekaterina; Gospodinov, Mitko

doi:10.1145/3345252.3345267

Cited by 3 publications

(2 citation statements)

References 7 publications

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“…Линейните методи са стандартизирани и се използват в клиничната практика, докато нелинейните методи са в процес на активни изследвания. Характерно за тези математически методи е, че те са универсални и се прилагат за анализ на данни и в други научни области [23,24].…”

Section: методи за определяне на всчunclassified

Analysis of Methods and Approaches for Evaluation of Heart Rate Variability

Lebamovski¹

2022

STEM

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This article analyses methods and approaches for assessing heart rate variability (HRV). One of the approaches is to study the impact of sports, in particular running athletics on HRV. As a result of the research, it was found that sports increase HRV by increasing the sympathetic share. The HRV method is influenced by various factors: diseases, external factors, physiological and lifestyle factors. Those that influence the athletic achievements of athletes are also considered. The impact of stress on HRV can be studied by creating 3D serious games to simulate various stressful situations and to study their impact on HRV. The article presents virtual reality systems, which are of two types: with immersion and without immersion and their application in the study of HRV. It follows from the analysis that the level of sympathetic tone in the analysis of HRV using virtual reality depends on the degree of immersion. Another approach to assessing HRV is to monitor patients at night to determine parasympathetic tone of the autonomic nervous system. For the accurate analysis of HRV, the mathematical methods used are important, which are mainly divided into linear and nonlinear. Spectral analysis is an example of linear, and Poincarè plot is nonlinear.

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Section: методи за определяне на всчunclassified

Analysis of Methods and Approaches for Evaluation of Heart Rate Variability

Lebamovski¹

2022

STEM

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“…Редица изследвания, проведени през последните години, показват че много системи в природата генерират времеви редове със сложно поведение. Примери за такива времеви редове са: времената на пристигане на пакетите данни в Интернет [17], сериите от времевите интервали между последователните удари на сърцето [1,2,4], цените на електроенергията [15,16], геофизични данни [3] и др. Сложното, непредсказуемо поведение на такива системи се дължи на случайни промени в техните параметри, случайни външни влияния, както и на развитието на различни нестабилности в системите.…”

Section: въведениеunclassified

Methods of Nonlinear Dynamics for Heart Rate Variability Analysis

Georgieva-Tsaneva¹

2022

STEM

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The heart rate variability (HRV) analysis, based on the methods of nonlinear dynamics, can provide important information for the physiological interpretation of the functioning of the cardiovascular system and assess the risk of its pathology. The article presents methods for nonlinear analysis of HRV, united in the following groups: fractal, multifractal, graphical and informational. The application of the methods of nonlinear dynamics in the study of the information characteristics of HRV in order to distinguish healthy subjects from sick ones is an important topic from the point of view of the application of the information technologies in the field of non-invasive cardiology. After determining the values of the studied parameters with the developed software and for the distinction of the two studied groups of subjects (healthy controls and patients with arrhythmia) statistical analysis was applied. The statistical analysis was performed by t-test and receiver operating characteristic (ROC) analysis. ROC curves are constructed and the area under the curves is calculated, on the basis of which the quality of the studied methods is evaluated. The results reported in this study may be useful in classifying the states of electrocardiographic signals and serve as a landmark for comparing healthy individuals to individuals with cardiovascular disease. The high information content of the used nonlinear methods for HRV analysis opens perspectives for their future use in the diagnosis and prognosis of cardiovascular diseases.

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