Advances in Digital Processing of Low-Amplitude Components of Electrocardiosignals

This manual has been published within the framework of the BME-ENA project under the responsibility of National Technical University of Ukraine. The BME-ENA “Biomedical Engineering Education Tempus Initiative in Eastern Neighbouring Area”, Project Number: 543904-TEMPUS-1-2013-1-GR-TEMPUS-JPCR is a Joint Project within the TEMPUS IV program. This project has been funded with support from the European Commission.Навчальний посібник присвячено розробці методів та засобів для неінвазивного виявлення та дослідження тонких проявів електричної активності серця. Особлива увага приділяється вдосконаленню інформаційного та алгоритмічного забезпечення систем електрокардіографії високого розрізнення для ранньої діагностики електричної нестабільності міокарда, а також для оцінки функціонального стану плоду під час вагітності. Теоретичні основи супроводжуються прикладами реалізації алгоритмів за допомогою системи MATLAB. Навчальний посібник призначений для студентів, аспірантів, а також фахівців у галузі біомедичної електроніки та медичних працівників.The teaching book is devoted to development and research of methods and tools for non-invasive detection of subtle manifistations of heart electrical activity. Particular attention is paid to the improvement of information and algorithmic support of high resolution electrocardiography for early diagnosis of myocardial electrical instability, as well as for the evaluation of the functional state of the fetus during pregnancy examination. The theoretical basis accompanied by the examples of implementation of the discussed algorithms with the help of MATLAB. The teaching book is intended for students, graduate students, as well as specialists in the field of biomedical electronics and medical professionals

Laboratory practice of discipline «Registration and processing of biosignals and medical images»

The tutorial is intended for bachelor's degree students of the educational program "Medical Engineering", specialty 163 "Biomedical engineering". It is dedicated to helping students to complete the laboratory practice of the discipline "Registration and processing of biosignals and medical images". The educational component "Registration and processing of biosignals and medical images" contributes to the development of professional expertise in knowledge of methods for processing and analysis of biomedical signals of different nature. The main purpose of the discipline is to form a holistic view of signals and methods of their study, as well as the acquisition of knowledge, skills, abilities and experience in using methods of registration, processing and analysis of biosignals and images in practice. Laboratory works are performed on the following topics: types of signals, their visualization, linear systems, spectral analysis, filtration, correlation analysis, wavelet analysis, and image processing

Age estimation of black locust (Robinia pseudoacacia) based on morphometric traits

The use of black locust (Robinia pseudoacacia L.) is still controversial, especially in managed forests, due to its invasive nature. The black locust has been proven effective in reclamation of degraded lands when native species are not an alternative in the face of the climate change and desertification. Therefore, the importance of black locust in European ecosystems remains a matter of debate. Of course, it is an adventitious species originating from another continent. However, the ecological characteristics of the species in its natural range are very useful for ensuring the restoration of vegetation cover in areas that have experienced significant anthropogenic pressure. This species has a large number of important and useful features that make it an important agent in the forestry system and provide significant environmental and economic benefits. The status of black locust as an invasive species, i.e. one that is capable of uncontrolled spread, remains speculative. Such a conclusion requires various studies, including those identifying exact age of the plants based on morphometric parameters. In our study, we tested the hypothesis that plant height and trunk diameter will allow for an accurate assessment of black locust age. The plants of black locust were measured in the zone of spontaneous self-seeding of plants from a planted 60-years-old forest. The plants dispersed towards a fallow land, formed in the corner of an agricultural field. The spreading began 15 to 20 years ago. The plants are mainly propagated by seedlings. An expert estimated the age of the plants visually. The measured trees were cut to obtain cross sections to account for the number of annual rings. A total of 68 trees were examined for morphometric characters. Black locust communities during self-dispersal are represented by individuals of different ages. The spatial pattern of distribution of individuals of different ages can reveal the spatial and temporal dynamics of the formation of spontaneous populations of black locust. For this purpose, it is critical to accurately identify the age of a large sample. Expert estimation of age is fast and fairly accurate, but it depends greatly on the qualifications of the expert and oftentimes plant ages are underestimated, especially in the early stages of population development. Plant height is also a good predictor of plant age, but the model gives poor predictions for plants older than 10 years. The tree height ranged 2.3 to 16.0 meters. The diameter at breast height (DBH) ranged 1.0 to 17.5 cm. The diameter at the root collar (DRC) ranged 1.6 to 21.7 cm. The age of the studied trees, determined by the number of annual rings per transect, ranged 6 to 17 years. The age of the trees according to the expert estimates was 8.2 ± 4.8 years. The expert estimates of age and the age according to the number of annual rings were statistically significantly different. The expert estimates of tree age were linearly related to tree size, while estimates of the number of annual rings showed a logarithmic relationship with tree height. Expert estimates also showed a closer relationship with tree height, while the relationship of estimates based on the number of annual rings had a slightly lower dependence on the morphometric traits. Regression analysis showed that there is a linear relationship between morphometric traits of the black locust. The coefficient of determination for the dependence of diameter at breast height on tree height was 0.96, and for the dependence of diameter at the base of the trunk on diameter at breast height was 0.97. This indicates a high level of multicollinearity of these morphometric traits when considering them as predictors of plant age. Taking into account the diameter at breast height and the diameter at the level of the root collar significantly improved the predictive ability of the model for identifying the age of the black locust trees

Heavy metal accumulation by Acer platanoides and Robinia pseudoacacia in an industrial city (Northern Steppe of Ukraine)

The role of tree species as a tool for bioaccumulation of heavy metals is an important current issue within the context of the increase of anthropogenic pressure in urban ecosystems. The article presents the results of research on the level of soil contamination with heavy metals and the processes of their accumulation by native and introduced tree species in green spaces of Dnipro city. Inductively coupled plasma mass spectrometry (ICP-MS) was used to detect concentrations of heavy metals (Zn, Cu, Cd, Pb) in soil samples and the assimilation component in trees of black locust (Robinia pseudoacacia) and Norway maple (Acer platanoides). The ranges of mean concentrations of heavy metals at different study sites within the city’s green infrastructure were as follows (mg/kg): 30.7–185.5 for Zn, 5.7–22.4 for Cu, 9.0–31.3 for Pb, and 0.213–0.598 for Cd. With respect to all four of these metals, the soils of the Metallurgists Square location were characterized by the highest concentrations of the metals, and the Pridneprovsky Park in the area of the outskirts of Dnipro city was characterized by the lowest ones. Compared to soils, the two investigated tree species had a significantly lower content of all studied metals in leaves. The heavy metal accumulations in the leaves of both R. pseudoacacia and A. platanoides were observed in the following decreasing order: Zn > Cu > Pb > Cd. Regarding the migration of heavy metals in the soil-plant system, the concentrations of ecopollutants in the plants were found not to be dependent on their content in the soil environment. The calculated bioaccumulation coefficients of heavy metals for both tree species were < 1. However, the results of heavy metal concentration in leaves of both introduced and native tree species evidenced their special role in heavy metal bioaccumulation. Compared to R. pseudoacacia, such native species as A. platanoides can be considered to be a more “sensitive” bioindicator of environmental pollution caused by heavy metals. Planting fast-growing tree species such as R. pseudoacacia and A. platanoides can in a short time be an environmentally appropriate and cost-effective measure to mitigate the unfavourable effects of heavy metals on the environment

Влияние технологических процессов резки листовых материалов на качественные характеристики продукции

В статті проведено аналіз технологічних процесів різання аркушевих матеріалів та їх вплив на якісні показники поліграфічної продукції.In the article the analysis of technological processes of cutting sheet materials and their influence on the high-quality indexes of printing products.В статье проведен анализ технологических процессов резки листовых материалов и их влияние на качественные показатели полиграфической продукции

Urban park layers: Spatial variation in plant community structure

Horizontal structure of natural plant communities attracted the attention of researchers for a long time, while the problem of horizontal structure of urban park plantations was not studied sufficiently. Species richness of different tiers of park plantation in the large industrial city of Dnipro (Ukraine) was revealed in this study. Also features of variation in the structure of plant communities at different spatial levels were revealed, the influence of park plantation canopy on the understory and herbaceous layer of the park. There were 30 plant species in the tree layer of the park plantation. The most common species were Robinia pseudoacacia L., Acer platanoides L., A. negundo L., Gleditsia triacanthos L., Aesculus hippocastanum L., Populus carolinensis Moench. The variance-to-mean ratio revealed that 13 tree species were randomly distributed throughout the park, and 14 species were aggregated. The number of occurrences of a given tree species per site and variance-to-mean ratio were positively correlated. The numerous tree species showed a tendency of aggregated distribution within the park. Sixteen plant species were found in the understory. Among them, the most abundant species were Acer platanoides L., A. negundo L., A. pseudoplatanus L., Sambucus nigra L., Robinia pseudoacacia L. Eight species were found to be randomly distributed over the park area, and eight species showed an aggregate distribution. The number of species encountered in the understory and variance-to-mean ratio were positively correlated. In the herbaceous stand, 99 plant species were found, of which Chelidonium majus L., Viola odorata L., Impatiens parviflora DC., Parthenocissus quinquefolia (L.) Planch., Geum urbanum L. predominated. The variance-to-mean ratio of all species was significantly less than unity, indicating regular spatial distribution. The values of alpha- and gamma-diversity of the plant community in separate layers are very different. The highest gamma diversity was found for the herbaceous stand, while the diversity of the tree stand and understory was significantly lower. Alpha biodiversity of the tree stand and the understory did not practically differ. Beta diversity values between the layers are very close, and beta diversity is practically equal for tree stand and herbaceous layer. Thus, we can assume that the mechanisms of species turnover for the plant communities of different layers are determined by the common causes. The spatial broad-scale component was able to explain 8.2% of community variation, the medium-scale component was able to explain 4.2% of community variation, and the fine-scale component was able to explain 0.7% of community variation. The understory is the most sensitive to the environmental factors, the herbaceous stand is somewhat less sensitive, and the tree stand is the least sensitive to the environmental factors. The environmental factors in this study are represented by a set of variables. The spatial variation of the stand is predominantly influenced by the factors of trophicity and moisture of the edaphotope. These same factors also act on the herbaceous stand and understory, but along with them are included the environmental variables, which are determined by the architectonics of the crown space and thus the light regime, which is regulated by the tree stand. It is important to note that the variation of the communities of the different layers of the park plantation is subject to spatial patterns. The herbaceous and understory variation is more spatially structured than the tree stand variation. The spatial patterns can arise as a result of the influence of spatially structured environmental factors and as a result of factors of a neutral nature. The latter aspect of variation is best described by the pure spatial component of community variation

Modeling the spatial variation of urban park ecological properties using remote sensing data

Parks perform a wide range of ecosystem services in urban environments. The functional importance of parks depends on the composition and structure of the tree stand and the specific influence on soil and microclimatic conditions. The article reveals the dependence of soil and microclimatic properties on the structure of the crown space of a park stand. Spectral indices were also shown to be applicable for predicting the spatial variability of soil and climatic properties and indicators of crown space. Soil properties (temperature, moisture, and electrical conductivity in the 5–7 cm layer) and microclimatic parameters (light exposure, air temperature, and atmospheric humidity) were measured in the park plantation using a quasi-regular grid. The canopy structure and gap light transmission indices were extracted from the true-colour fisheye photographs. Thirty species of trees and shrubs were detected in the stand and understory. Robinia pseudoacacia L. was found most frequently (24.5% of all tree records). Acer negundo L. and A. platanoides L. were also frequent (12.4% and 15.5%, respectively). The first four principal components, whose eigenvalues exceeded unity, were extracted by the principal components analysis of the variability of ecological properties and vegetation indices. The principal component 1 explained 50.5% of the variation of the traits and positively correlated with the spectral vegetation indices. The principal component 1 reflected the variability of tree cover densities due to the edaphic trophicity. The principal component 2 described 13% of the variation in the feature space. This component correlated positively with the spectral indices. The principal component 2 was interpreted as a trend of vegetation cover variability induced by moisture variation. The principal component 3 described 8.6% of trait variation. It was most strongly correlated with the atmospheric humidity. An increase in atmospheric humidity was associated with an increase in the soil moisture and electrical conductivity and a decrease in the soil and atmospheric temperature. The principal component 4 described 7.5 % of the variation of traits. An increase in the values of principal component 4 was associated with an increase in the soil moisture and electrical conductivity and atmospheric moisture and was associated with a decrease in the soil and atmospheric temperature. The combinations of the trophotope and hygrotope create the optimal conditions for specific tree species, which is a condition for achieving the maximization of ecosystem services. The mineral nutrition conditions of plants and soil moisture exhibit spatial patterns that allow them to be considered in the design and management of park plantations. The ecological indices measured in the field were shown to be predicted using the vegetation indices. Multiple regression models were able to explain 11–61% of indicator variation. The regression relationships between markers of soil and microclimatic conditions and vegetation predictors are important for monitoring the condition of park plantations and evaluating the performance of park plantation management tools

Вейвлет-анализ электрокардиосигналов для выявления признаков посттравматической миокардиодистрофии.

Розглянуто особливості впливу травматичної хвороби на серцево-судинну систему. Виконано числові експерименти з дослідження електрокардіосигналів військовослужбовців після мінно-вибухового поранення. У процесі клінічних досліджень реєстрація та обробка електрокардіосигналів виконані за допомогою системи електрокардіографії високого розрізнення. На основі проведеного вейвлет-аналізу електрокардіосигналів запропоновано інтегральні параметри для виявлення ознак посттравматичної міокардіодистрофії.Introduction. The features of the traumatic disease's impact on the cardiovascular system are reviewed. Numerical experiments on electrocardiosignals of the soldiers injuried by mine explosion were held. The nature of the posttraumatic myocardial dystrophy is described. HR ECG signals' analysis. During clinical studies the registration and processing of electrocardiosignals were performed by the high resolution electrocardiography system. The time and amplitude analysis of HR ECG signals was held, and its low efficiency was approved. The integral parameters for detection of the posttraumatic myocardial dystrophy features based on the wavelet analysis of the electrocardiosignals are proposed. Conclusion. Since the myocardial dystrophy is caused by the violation of the processes related to the transport of ions Ca2+, the changes of electrocardiosignals are visible at the highest levels of wavelet decomposition. Thus, the 8th and 9th levels of the 9-level wavelet decomposition of averaged cardiocycles showed the best result for diagnostic.Рассмотрены особенности влияния травматической болезни на сердечно-сосудистую систему. Выполнены численные эксперименты по исследованию электрокардиосигналов военнослужащих после минно-взрывных ранений. В процессе клинических исследований регистрация и обработка электрокардиосигналов выполнены с помощью системы электрокардиографии высокого разрешения. На основе проведенного вейвлет–анализа электрокардиосигналов предложены интегральные параметры для выявления признаков посттравматической миокардиодистрофии

Энтропия перестановок сердечного ритма плода при изъятии ударов сердца матери

Розробка і застосування методів ідентифікації фізіологічних станів для матері та плоду, заснованих на неінвазивному моніторингу серцевої діяльності, має велике клінічне значення під час вагітності. У даній роботі досліджуються нові можливості застосування ентропії перестановок (ЕП) – одного з нелінійних методів часового аналізу серцевих скорочень плода. ЕП використовується для описання ритмограм плоду з метою отримання нових даних щодо характеристик серцевого ритму плода. Використовується нова методика виділення фетальної електрокардіограми (фЕКГ), заснована на фільтрації у вейвлет-просторі та реконструкції фЕКГ з використанням коефіцієнтів деталізації. Ентропія перестановок застосовується для отримання числових значень та часових залежностей ЕП для серцевого ритму у випадку необроблених ритмограм плоду та ритмограм, отриманих з виділеними ударами серця матері. Припущення про необхідність видаляти удари серця матері із початкової ритмограми підтверджується різницею у значеннях ЕП для двох випадків.Development and application of maternal and fetal physiological states identification techniques based on the noninvasive electrical heart activity monitoring is of great clinical importance during pregnancy. In this paper, new possibilities of applying one of nonlinear measures of time series behavior analysis to the fetal heart rates are explored, and permutation entropy (PE) characteristics of fetal rhythmograms are used to get new insight on the fetal heart rhythm parameters. The new technique of fetal electrocardiogram (fECG) extraction is used, based on filtration in wavelet domain and reconstruction of fECG using detalization coefficients. Permutation entropy analysis is applied to obtain PE values and trends for the case of raw fetal rhythmograms and those obtained with excluded maternal heart beats. The assumption about the need to extract maternal heartbeats from initial rhythmogram is proven by the difference in PE values for two cases.Разработка и применение методов идентификации физиологических состояний матери и плода, основанных на неинвазивном мониторинге сердечной деятельности, имеет большое клиническое значение при беременности. В данной работе исследуются новые возможности применения энтропии перестановок (ЭП) – одного из нелинейных методов временного анализа сердечных сокращений плода. ЭП используется для описания ритмограмм плода с целью получения новых данных о характеристиках сердечного ритма плода. Используется новая методика выделения фетальной электрокардиограммы (фЭКГ), основанная на фильтрации в вейвлет-пространстве и реконструкции фЭКГ с использованием коэффициентов детализации. Энтропия перестановок применяется для получения числовых значений и временных зависимостей ЭП для сердечного ритма в случае необработанных ритмограмм плода и ритмограмм, полученных с выделенными ударами сердца матери. Предположение о необходимости удалять удары сердца матери из начальной ритмограммы подтверждается разницей в значениях ЭП для двух случаев

Прогнозування розвитку гестаційного цукрового діабету у вагітних із використан-ням методів машинного навчання

Стаття присвячена застосуванню методів машинного навчання для прогнозування розвитку гес-таційного цукрового діабету на ранніх термінах вагітності. На основі двох публічнодоступних баз даних оцінюється вплив таких показників, як індекс маси тіла, товщина шкірної складки трицепса, ультразвукове вимірювання віс-церального жиру у матері, перше визначення глюкози у плазмі венозної крові натщесерце та інших параметрів для прогнозування розвитку гестаційного цукрового діабету. Методи машинного навчання з вчителем, засновані на деревах рішень, методі опорних векторів, логістичній регресії, класифікаторі k-найближчих сусідів, ансамблевому навчанні, наївному Байєсівському класифікаторі та нейронних мережах були реалізовані для визначення найкра-щих моделей класифікації для комп'ютеризованого прогнозування гестаційного діабету. В роботі визначено та порівняно точність різних класифікаторів. Метод опорних векторів продемонстрував найвищу точність класифі-кації у прогнозуванні розвитку гестаційного діабету на основі навчання з використанням показників з бази даних Pima Indians Diabetes Database (83,0% загальних вірно спрогнозованих випадків, 87,9% для класу здорових жінок та 78,1% для класу гестаційного цукрового діабету). Класифікатор з використанням ансамблевого навчання дерев рішень показав найкращі результати порівняно з іншими методами машинного навчання на основі навчання з використанням показників з бази даних Visceral Adipose Tissue Measurements During Pregnancy - 87,9% загальних вірно прогнозованих випадків, 82,2% для класу здорових жінок та 93,6% для класу гестаційного цукрового діабету).The paper is devoted to the application of machine learning methods to the prediction of the development of gestational diabetes mellitus in early pregnancy. Based on two publicly available databases, study assesses influence of such features as body mass index, thickness of triceps skin folds, ultrasound measurements of maternal visceral fat, first meas-ured fasting glucose, and others a predictors of gestational diabetes mellitus. The supervised machine learning methods based on decision trees, support vector machines, logistic regression, k-nearest neighbors classifier, ensemble learning, Naive Bayes classifier, and neural networks were implemented to determine the best classification models for computerized gesta-tional diabetes mellitus disease prediction. The accuracy of the different classifiers was determined and compared. Support vector machine classifier demonstrated the highest accuracy (83.0% of total correctly prognosed cases, 87.9% for healthy class, and 78.1% for gestational diabetes mellitus) in predicting the development of gestational diabetes based on features from Pima Indians Diabetes Database. Extreme gradient boosting classifier performed the best, comparing to other super-vised machine learning methods, for Visceral Adipose Tissue Measurements during Pregnancy Database. It showed 87.9% of total correctly prognosed cases, 82.2% for healthy class, and 93.6% for gestational diabetes mellitus)