CRITERIA FOR PREDICTING BIOELECTRICAL PROCESSES IN THE HUMAN HEART UNDER VARIOUS STAGES OF ACUTE HYPOXIA

Despite much available information on the heart activity under acute normobaric hypoxia (ANH), there are no data on the leading ECG components and the criteria for predicting their deviations at various stages of ANH and depending on its duration. The aim of the paper is to determine the leading ECG components and the dependence of their deviations on the initial parameters at different stages of acute normobaric hypoxia and depending on its duration in a healthy person. Materials and Methods. The shifts in parameter indicators were determined in two groups of men (aged 18–26) under 20-minute mild (14.5 % O2, n1=30) and medium (12.3 % O2, n2=29) ANH. During the study the authors used 7 ECG parameters and oximetry. Statistica 10.0 software package was used for data processing. The authors determined normality of distribution, they also used factor analysis, correlation, and regression. Results. For all ANH degrees, the leading factor included QT, T1II, and (with one exception) RR. In case of mild ANH, the 1st factor was supplemented by P1II at the 5th minute of exposure, and in case of medium ANH at the 20th minute. The second most important factor in case of mild ANH was determined by BAR and RII at the 5th and 20th min and by BAR at the 10th min. In case of medium ANH it was supplemented by P1II at the 5th min, by RII and BAR at the 10th min, and by BAL at the 20th min. It was shown that in case of mild ANH P1II, RII, BAR, and RR deviations reliably depend on the initial parameters; for medium ANH, such dependence is observed for RR and QT at the 5th and 10th min, for RII at the 10th and 20th min, and for P1II at the 20th min. Conclusion. The main markers of heart bioelectrical processes under ANH are QT, T1II and RR, other parameters are variable. The availability to predict deviations of ECG parameters by their initial parameters depends on ANH stage. Key words: human, hypoxia, oximetry, electrocardiography, factorial, correlation, regression analysis. Несмотря на имеющиеся многочисленные сведения о деятельности сердца при острой нормобарической гипоксии (ОНГ), данные о ведущих компонентах ЭКГ и критериях прогнозирования их отклонений при разной степени ОНГ и в зависимости от ее длительности отсутствуют. Цель работы – определить ведущие компоненты ЭКГ и зависимости их отклонений от исходных величин при разных степенях острой нормобарической гипоксии и в зависимости от её длительности у здорового человека. Материалы и методы. С помощью ЭКГ (7 параметров) и оксигемометрии определены сдвиги их показателей у мужчин (18–26 лет) двух групп при легкой (14,5 % О2, n1=30) и средней (12,3 % О2, n2=29) ОНГ в течение 20 мин. Материал обработан с помощью программного пакета Statistica 10.0. Определяли нормальность распределения, применяли факторный анализ, корреляцию, регрессию. Результаты. При всех степенях ОНГ ведущий фактор включал QT, T1II и (с одним исключением) RR. При легкой ОНГ 1-й фактор на 5-й мин воздействия дополняется P1II, а при средней ОНГ на 20-й мин – P1II. Второй по весомости фактор при легкой ОНГ на 5-й и 20-й мин определяется BAR и RII, на 10-й мин – BAR, а при средней ОНГ на 5-й мин – P1II, на 10-й мин – RII и BAR, на 20-й мин – BAL. Показано, что при легкой ОНГ от исходных данных достоверно зависят отклонения P1II, RII, BAR и RR, при средней ОНГ такая зависимость наблюдается для RR и QT на 5-й и 10-й мин, для RII на 10-й и 20-й мин и для P1II на 20-й мин. Выводы. Основными маркерами биоэлектрических процессов сердца при ОНГ являются QT, T1II и RR, остальные параметры отличаются вариабельностью. Возможность прогноза отклонений параметров ЭКГ по их исходным величинам зависит от степени ОНГ. Ключевые слова: человек, гипоксия, оксигемометрия, электрокардиография, факторный, корреляционный, регрессионный анализы.

Some psychophysiological parameters of a person during a passive orthostatic test

The study involved 14 volunteer students. Situational anxiety was determined, tests were carried out to determine simple and complex sensorimotor reactions, the cardiac rhythm of the subjects was recorded. Oxygen saturation was determined using an oximeter. Dynamic parameters were recorded: lying in a state of functional rest (background 1), vertical at 65-70° (vertical), lying after verticalization (horizontal), lying in a state of functional rest (background 2). The analysis of the data obtained was carried out using the Excel and StatPlus Pro programs. It was revealed that during verticalization, changes in the regulation of the heart activity of the subjects are carried out mainly due to the central mechanisms of regulation through the sympathetic nervous system. The transfer from a vertical to a horizontal state is accompanied by a restructuring of the regulatory system towards the activation of subcortical nerve centers and a shift in the balance of the SNS/PSNS towards the parasympathetic nervous system. Key words: passive orthostatic test, cardiac rhythm, simple sensorimotor reaction.

PEDOT:PSS-Modified Cotton Conductive Thread for Mass Manufacturing of Textile-Based Electrical Wearable Sensors by Computerized Embroidery

The textile industry has advanced processes that allow computerized manufacturing of garments at large volumes with precise visual patterns. The industry, however, is not able to mass fabricate clothes with seamlessly integrated wearable sensors, using its precise methods of fabrication (such as computerized embroidery). This is due to the lack of conductive threads compatible with standard manufacturing methods used in industry. In this work, we report a low-cost poly(3,4-ethylenedioxythiophene) polystyrene sulfonate (PEDOT:PSS)-modified cotton conductive thread (PECOTEX) that is compatible with computerized embroidery. The PECOTEX was produced using a crosslinking reaction between PEDOT:PSS and cotton thread using divinyl sulfone as the crosslinker. We extensively characterized and optimized our formulations to create a mechanically robust conductive thread that can be produced in large quantities in a roll-to-roll fashion. Using PECOTEX and a domestic computerized embroidery machine, we produced a series of wearable electrical sensors including a facemask for monitoring breathing, a t-shirt for monitoring heart activity and textile-based gas sensors for monitoring ammonia as technology demonstrators. PECOTEX has the potential to enable mass manufacturing of new classes of low-cost wearable sensors integrated into everyday clothes.

Trajectories of Heart Activity Across Infancy to Early Childhood Differentially Predict Autism and Anxiety Symptoms in Fragile X Syndrome

Background: Fragile X syndrome (FXS) is a monogenic disorder characterized by high rates of autism spectrum disorder (ASD) and anxiety. A longstanding “hyperarousal hypothesis” in FXS has argued that ANS dysfunction underpins many symptoms of FXS. However, the developmental onset and trajectory of ANS dysfunction, as well as the consequences of ANS dysfunction on later psychiatric symptoms, remain poorly understood in FXS. Insight into the emergence, trajectory, and consequences of ANS dysfunction across early development in FXS has critical implications for prevention, intervention, and optimal outcomes in both typical and atypical development. This longitudinal study investigated whether and when males with FXS evidence atypical ANS function from infancy through early childhood, and how trajectories of ANS function across infancy and early childhood predict ASD and anxiety symptom severity later in development.Methods: Participants included 73 males with FXS and 79 age-matched typically developing (TD) males. Baseline heart activity was recorded at multiple assessments between 3 and 83 months of age, resulting in 372 observations. General arousal and parasympathetic activity were indexed via interbeat interval (IBI) and respiratory sinus arrhythmia (RSA), respectively. ASD and anxiety symptoms were assessed at 36 months of age or later in a subgroup of participants (FXS n = 28; TD n = 25).Results: Males with FXS exhibited atypical patterns of developmental change in ANS function across infancy and early childhood. As a result, ANS dysfunction became progressively more discrepant across time, with the FXS group exhibiting significantly shorter IBI and lower RSA by 29 and 24 months of age, respectively. Shorter IBI at 24 months and a flatter IBI slope across development predicted elevated anxiety symptoms, but not ASD symptoms, later in childhood in both FXS and TD males. Reduced RSA at 24 months predicted elevated ASD symptoms, but not anxiety symptoms, in both groups. Developmental change in RSA across early development did not predict later anxiety or ASD symptoms.Conclusion: This is the first longitudinal study to examine the “hyperarousal hypothesis” in infants and young children with FXS. Findings suggest that hyperarousal (i.e., shorter IBI, lower RSA) is evident in males with FXS by 24–29 months of age. Interestingly, unique aspects of early ANS function differentially relate to later ASD and anxiety symptoms. General arousal, indexed by shorter IBI that becomes progressively more discrepant from TD controls, predicts later anxiety symptoms. In contrast, parasympathetic-related factors, indexed by lower levels of RSA, predict ASD symptoms. These findings support the “hyperarousal hypothesis” in FXS, in that ANS dysfunction evident early in development predicts later-emerging symptoms of ASD and anxiety. This study also have important implications for the development of targeted treatments and interventions that could potentially mitigate the long-term effects of hyperarousal in FXS.

Energy efficient convolutional neural networks for arrhythmia detection

Electrocardiograms (ECG) record the heart activity and are the most common and reliable method to detect cardiac arrhythmias, such as atrial fibrillation (AFib). Lately, many commercially available devices such as smartwatches are offering ECG monitoring. Therefore, there is increasing demand for designing deep learning models with the perspective to be physically implemented on these small portable devices with limited energy supply. In this paper, a workflow for the design of small, energy-efficient recurrent convolutional neural network (RCNN) architecture for AFib detection is proposed. However, the approach can be well generalized to every type of long time series. In contrast to previous studies, that demand thousands of additional network neurons and millions of extra model parameters, the logical steps for the generation of a CNN with only 114 trainable parameters are described. The model consists of a small segmented CNN in combination with an optimal energy classifier. The architectural decisions are made by using the energy consumption as a metric in an equally important way as the accuracy. The optimisation steps are focused on the software which can be embedded afterwards on a physical chip. Finally, a comparison with some previous relevant studies suggests that the widely used huge CNNs for similar tasks are mostly redundant and unessentially computationally expensive.

Dynamic near-field microwave diagnostics of lungs.

Results of theoretical and experimental studies of the method of the near-field microwave tomography of the thorax are presented. Integral equations of inverse tomography problem of 3D blood- and air content inhomogeneities by data of multisensory measurements are obtained. Methods of air and blood content profiling in processes of breathing and heart activity by data of bistatic measurements of the scattered signal are proposed and solving algorithms of inverse problems are studied in the numerical simulation. Multifrequency and pulse measurements of scattered signals are carried out in processes of cardiorespiratory activity. By data of bistatic measurements of scattered signals parameters from the thorax, profiling relative air- and blood content profiles has been realized. Application possibilities of the method in the biomedical diagnostics are considered.

FETAL QRS-COMPLEXES DETECTECTIONS IN ABDOMINAL SIGNAL BY USING WAVELET-BISPECTRUM

Fetal hypoxia or distress is a physical stress experienced by a fetus due to a lack of oxygen. Intrauterine hypoxia and the resultant perinatal brain damages may lead to extraordinary effects, including continuous lifelong treatments. One of the ways for detecting symptoms of hypoxia is monitoring of the fetus heart activity. At present, the basic method of monitoring the condition of unborn baby is the ultrasound cardiotocography (CTG). Considerably more information for early detection of the fetal hypoxia may be obtained by analyzing fetal electrocardiogram (FECG).