Wyniki wyszukiwania - BazTech

Ograniczanie wyników

Znaleziono wyników: 3

Liczba wyników na stronie

Wyniki wyszukiwania

Wyszukiwano:
w słowach kluczowych: miary złożoności

Sortuj według:

Ogranicz wyniki do:

Early diagnosis of threatened premature labor by electrohysterographic recordings – The use of digital signal processing

Lemancewicz A., Borowska M., Kuć P., Jasińska E., Laudański P., Laudański T., Oczeretko E.

Biocybernetics and Biomedical Engineering

2016

Vol. 36, no. 1

302--307

Prevention and early diagnosis of imminent preterm labor are considered to be the most important perinatal challenge nowadays. Significant progress has been observed on postnatal care of premature infants, but without reducing the prevalence of preterm delivery. Our study was focused on comparison of three methods of spectral analysis of electro-hysterographic (EHG) signals: fast Fourier transform (FFT), wavelet transform (WT) and autoregressive modeling (AR). Complexity of the electrohysterographic signals was analyzed by using: the approximate entropy (ApEn), Lempel–Ziv complexity measure (L–Z). Additionally, the work evaluated the applicability of EHG in diagnosing imminent premature labor. EHG signals were recorded among 60 patients with threatened preterm labor symptoms between the 24th and 34th week of pregnancy. Patients included to the study had a shortened cervix (less than 20 mm) without regular uterine contractions recorded on regular cardiotocography (CTG). The women were divided into two groups: those delivering within 7 days – group A (n = 15) and women delivering after 7 days – group B (n = 45). The study confirmed differences in bioelectrical activity of uterus between patients delivering prematurely within 7 days and after from the EHG registration for all analyzed methods.

Entropia w badaniach zaburzeń rytmu serca

Graff B., Graff G., Kolesiak A.

Matematyka Stosowana : matematyka dla społeczeństwa

2008

Nr 9

46-56

Artykuł prezentuje zastosowanie Approximate Entropy, będącej miarą stopnia złożoności szeregów czasowych, do analizy zmienności rytmu serca.

Healthy human heart rate is characterized by oscillations observed in intervals between consecutive heartbeats (RR intervals). Conventional methods of heart rate variability analysis measure the overall magnitude of RR interval fluctuations around its mean value or the magnitude of fluctuations in predetermined frequencies. The new methods of chaos theory and nonlinear dynamics provide powerful tools, which allow to predict clinical outcome in patients with cardiovascular diseases. The main aim of our article is to present Approximate Entropy (ApEn), a measure of system regularity and complexity, introduced by Pincus in 1991. ApEn estimation used for clinical purposes is applied for finite number of records, divided in vectors, and depends on two fixed parameters m and r. Then Approximate Entropy may be interpreted as the average of negative natural logarithms of conditional probability, that two vectors of length m + 1 are similar (we define here r-similarity), if two vectors of the length m are similar. The article provides a formal mathematical description of ApEn and presents a simple algorithm for its assessment. The choice of input parameters m and r is also discussed. In vast majority of publications r depends on standard deviation (SD) of average of all records, when individual features of heart rhythm are taken into account. The fraction of r, equal to 0, 2SD, and m = 2 are usually chosen on the basis of previous findings of good statistical validity. With the above set of parameters we can avoid the influence of outliers and do not loose too much information. ApEn has also some disadvantages - the main is counting self similarities. To reduce this kind of bias some improvements of the methods based on Pincus’ algorithm were developed. For example Sample Entropy (SampEn), which has similar algorithm but does not count self-matches, was proposed and easily applied to clinical time-series. In the article we present also an application of ApEn in predicting atrial fibrillation (AF), a type of arrhythmia which is the most common sustained heart rhythm disturbance. Both ApEn and SampEn decrease before the spontaneous onset of AF. What is more, ApEn is not sensitive to ectopy beats and therefore can be assessed fully automatically. The potential application of ApEn is the possibility to detect an increased vulnerability to AF before the onset of arrhythmia during continuous heart rate recording, for example for patients with implantable pacemakers. The recognition of the higher risk of AF would be followed by immediate pacemaker reprogramming to prevent an episode of arrhythmia. It would result not only in better quality of life of the patient but also in decreased number of hospitalization and cost of treatment.

Wstępne implikacje analizy systemów złożonych dla przypadku układu oddechowego

Jabłoński I., Mroczka J.

Pomiary Automatyka Kontrola

2007

R. 53, nr 9 bis

402--405

Charakterystyczne wzorce czasowej zmienności są przejawem zdefiniowanej właściwości systemów złożonych [[9], [17]], także tych biologicznych, których interesującym przypadkiem jest układ oddechowy. U wykazujących ogólną systemową stabilność złożonych systemów biologicznych stwierdzić jednakże można relacje pomiędzy wystąpieniem stanu patologicznego a zmianą indywidualnej trajektorii zachowań w przestrzeni obserwacji. Artykuł podejmuje problematykę możliwości pomiaru regularności oraz ich zmian w kontekście analizy złożoności. Posługując się sztucznie wygenerowanymi danymi, autorzy wstępnie szacują potencjał wybranych narzędzi teoretycznych do pracy z sygnałami rejestrowanymi w układzie oddechowym. Szczególnie interesujące wyniki uzyskano dla miar entropijnych, a także dla grafów rekurencyjnych, będących wyrazem topologicznej reprezentacji złożoności systemów. Przedstawione wyniki wstępne sugerują potrzebę kontynuacji prac, tak w obszarze samych narzędzi jak i czysto aplikacyjnym.

Characteristic patterns of temporal variations manifest a defining feature of complex systems [[9], [17]], also this biological ones, among which the respiratory system is an interesting example. For the group of the complex biological systems, with characteristic property of general systemic stability, yet it can be stated the relationship between the appearance of a pathological state and the change of the individual trajectory of behaviour in the space of observations. The paper deals with the issues of ability to measure regularities, their changes in the context of complex analysis. Using artificially generated data, the authors have tentatively estimated the potential of the chosen theoretical tools to the work with the signals accessible in the respiratory system. Especially interesting results were obtained for the entropy measures as well as for the recurrent graphs, which are the topological representation of system complexity. The presented, introductory results suggest the need to continue the investigations, both in the area of the tools and purely appliqué one.