10 research outputs found

    Adaptive Signal Process Techniques for Extracting Craniate’s Electrocardiograms

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    This investigation introduces a robotized and non intrusive innovation utilizing a coordinated fetal transabdominal electrocardiogram framework and Doppler cardiogram (DCG) to distinguish fetal heart oddities. The Multiresolution wavelet investigation and Jensen-Shannon disparity (JSD) techniques were utilized to recognize the recurrence substance of the Doppler signs to be connected to the opening and shutting of the heart's valves (Aortic and mitral). For the everyday babies, PEP (Pre-discharge period), VET (Ventricular launch time), ICT (Isovolumic constriction time) and IVRT (Isovolumic unwinding time) were observed to be 75.0±11.9 (msec), 153.2±18.9 (msec), 50.0±15.9 (msec) and 69.6±9.7 (msec) separately. Then again, for hatchlings with heart inconsistencies, these planning interims were observed to be 89.0±10.3 (msec), 168.6±25.0 (msec), 52.2±17.2 (msec) and 51.6±13.7 (msec) separately. Punch, VET and IVRT values are altogether (p< zero.01) numerous between the two gatherings

    Development of a Novel Dataset and Tools for Non-Invasive Fetal Electrocardiography Research

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    This PhD thesis presents the development of a novel open multi-modal dataset for advanced studies on fetal cardiological assessment, along with a set of signal processing tools for its exploitation. The Non-Invasive Fetal Electrocardiography (ECG) Analysis (NInFEA) dataset features multi-channel electrophysiological recordings characterized by high sampling frequency and digital resolution, maternal respiration signal, synchronized fetal trans-abdominal pulsed-wave Doppler (PWD) recordings and clinical annotations provided by expert clinicians at the time of the signal collection. To the best of our knowledge, there are no similar dataset available. The signal processing tools targeted both the PWD and the non-invasive fetal ECG, exploiting the recorded dataset. About the former, the study focuses on the processing aimed at the preparation of the signal for the automatic measurement of relevant morphological features, already adopted in the clinical practice for cardiac assessment. To this aim, a relevant step is the automatic identification of the complete and measurable cardiac cycles in the PWD videos: a rigorous methodology was deployed for the analysis of the different processing steps involved in the automatic delineation of the PWD envelope, then implementing different approaches for the supervised classification of the cardiac cycles, discriminating between complete and measurable vs. malformed or incomplete ones. Finally, preliminary measurement algorithms were also developed in order to extract clinically relevant parameters from the PWD. About the fetal ECG, this thesis concentrated on the systematic analysis of the adaptive filters performance for non-invasive fetal ECG extraction processing, identified as the reference tool throughout the thesis. Then, two studies are reported: one on the wavelet-based denoising of the extracted fetal ECG and another one on the fetal ECG quality assessment from the analysis of the raw abdominal recordings. Overall, the thesis represents an important milestone in the field, by promoting the open-data approach and introducing automated analysis tools that could be easily integrated in future medical devices

    A non-invasive multimodal foetal ECG–Doppler dataset for antenatal cardiology research

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    Non-invasive foetal electrocardiography (fECG) continues to be an open topic for research. The development of standard algorithms for the extraction of the fECG from the maternal electrophysiological interference is limited by the lack of publicly available reference datasets that could be used to benchmark different algorithms while providing a ground truth for foetal heart activity when an invasive scalp lead is unavailable. In this work, we present the Non-Invasive Multimodal Foetal ECG-Doppler Dataset for Antenatal Cardiology Research (NInFEA), the first open-access multimodal early-pregnancy dataset in the field that features simultaneous non-invasive electrophysiological recordings and foetal pulsed-wave Doppler (PWD). The dataset is mainly conceived for researchers working on fECG signal processing algorithms. The dataset includes 60 entries from 39 pregnant women, between the 21st and 27th week of gestation. Each dataset entry comprises 27 electrophysiological channels (2048 Hz, 22 bits), a maternal respiration signal, synchronised foetal trans-abdominal PWD and clinical annotations provided by expert clinicians during signal acquisition. MATLAB snippets for data processing are also provided

    BPNN based MECG elimination from the abdominal signal to extract fetal signal for continuous fetal monitoring

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    Fetal monitoring may help with possible recognition of problems in the fetus. This research work focuses on the design of the Back-propagation Neural Network (BPNN) and Adaptive Linear Neural Network (ADALINE) to extract the Fetal Electrocardiogram (FECG) from the Abdominal ECG (AECG). FECG is extracted to assess the fetus well-being during the pregnancy period of a mother to overcome some existing difficulties regarding the fetal heart rate (FHR) monitoring system. Different sets of ECG signal has been tested to validate the algorithm performance. The accuracy of the QRS detection using the designed algorithm is 99%. This research work further made a comparison study between various methods' performance and accuracy and found that the developed algorithm gives the highest accuracy. This paper opens up a passage to biomedical scientists, researchers, and end users to advocate to extract the FECG signal from the AECG signal for FHR monitoring system by providing valuable information to help them for developing more dominant, flexible and resourceful applications.Muhammad Asraful Hasan and Md Mamu

    Cardiac Arrhythmias

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    The most intimate mechanisms of cardiac arrhythmias are still quite unknown to scientists. Genetic studies on ionic alterations, the electrocardiographic features of cardiac rhythm and an arsenal of diagnostic tests have done more in the last five years than in all the history of cardiology. Similarly, therapy to prevent or cure such diseases is growing rapidly day by day. In this book the reader will be able to see with brighter light some of these intimate mechanisms of production, as well as cutting-edge therapies to date. Genetic studies, electrophysiological and electrocardiographyc features, ion channel alterations, heart diseases still unknown , and even the relationship between the psychic sphere and the heart have been exposed in this book. It deserves to be read

    Extracción de parámetros tiempo-frecuencia-energía del primer sonido cardiaco fetal

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    Los sonidos cardíacos fetales (SCF) son vibraciones acústicas que contienen información acerca de la condición del sistema cardiovascular. Tradicionalmente, estos SCF se han usado solo para estudiar el estado de las válvulas cardíacas y medir la frecuencia cardíaca fetal, no obstante, se ha reconocido que también tienen el potencial para estudiar el desarrollo de la contractilidad miocárdica, la cual se ha vinculado con cambios en las frecuencias de los SCF y otras características morfológicas adicionales. Sin embargo, de acuerdo con los valores reportados en la literatura, aún existen diferencias importantes en sus frecuencias, y sus características adicionales aún siguen sin cuantificarse. En este trabajo se consideró que estas diferencias podrían deberse a las limitaciones de la técnica de análisis tradicional y se usó una alternativa que al incrementar la resolución permitió identificar las vibraciones (o eventos acústicos) constitutivas de S1 y extraer características tiempo, frecuencia, energía (TFE) en registros obtenidos en edades gestacionales diferentes. El objetivo de este estudio fue estudiar las características TFE de las vibraciones del primer sonido cardíaco fetal (S1) ante cambios en la edad gestacional (EG). Para ello se extrajeron sonidos cardíacos S1 a partir de 9 registros fonocardiográficos en EGs entre 33 y 40 semanas, acompañados de un canal de electrocardiografía abdominal. Después de pasar por criterios de inclusión, a estos sonidos S1 se les aplicó la Transformada Wavelet Continua (TWC) mediante la cual se produjo el escalograma wavelet (representación en 3D) de S1 donde fue posible observar 5 vibraciones de alta amplitud. Posteriormente se simplificó esa misma representación para obtener la energía instantánea, etiquetar automáticamente esas vibraciones a estudiar y, por ende, medir su posición temporal y su energía. Después se simplificó el mismo escalograma, pero ahora para obtener la frecuencia instantánea, observar los cambios de las vibraciones etiquetadas y medir su frecuencia. Paso seguido, la muestra se dividió en tres grupos de EG, estos son: grupo G1 (para EGs de 33 semanas), grupo G2 (para EGs de 36 semanas) y grupo G3 (para EG entre 38 y 40 semanas). Finalmente, se analizó el comportamiento de esas mediciones o características en (1) misma EG y (2) entre diferentes EGs. Después del análisis de un total de 20 características de las vibraciones se encontró que independientemente de la EG, los tiempos de las vibraciones fueron diferentes (p < 0.010). Por el contrario, para las frecuencias, independientemente de la EG se encontró que las frecuencias de las vibraciones fueron iguales (sin significancia estadística), es decir, en el mismo grupo no se pueden discernir entre ellas. Para las energías se observó que, en G2 y G3 las energías de las vibraciones fueron diferentes (p < 0.010), sin embargo, en G1 (grupo donde se encuentran las menores EGs) se encontró que las energías de los picos de mayor amplitud etiquetados como EP2- EP3 fueron iguales, y las energías de los picos de mediana amplitud etiquetados como EP1-EP4 también fueron iguales. Con respecto a las comparaciones de las mediciones entre grupos, se encontró que: los tiempos de los eventos acústicos (para los tiempos medidos de manera relativa (a partir del pico R)) suelen cambiar de G1 a G2 y de G2 a G3, en particular a partir del tiempo etiquetado como RP2, G2 fue significativamente diferente de los otros grupos (p < 0.015). Con respecto a las frecuencias, se encontró que independientemente de la vibración bajo estudio las frecuencias fueron diferentes en cada EG (p < 0.015). Igual que el anterior, las energías de estos eventos acústicos resultaron ser diferentes en cada EG (p < 0.015), excepto para la vibración etiquetada como EP3. Por último, inesperadamente se encontró que EP3 y el tiempo etiquetado como TP3 (correspondiente a los tiempos medidos de manera local (a partir del inicio del sonido)) permanecen estables al cambiar la EG (sin significancia estadística). En conclusión, las representaciones de energía y frecuencia mostraron claramente 5 vibraciones consistentes que permitieron la fácil medición de sus características TFE. También se pudo observar que para la misma EG solo se encontraron traslapes en las frecuencias y algunas energías en G1. Con referencia a los distintos grupos gestacionales, se encontró, que tanto la frecuencia como la energía cambian consistentemente, siendo la primera vez que se reportan cambios en la energía de las vibraciones en función de la EG. Dados los resultados, se pudo encontrar una similitud en el comportamiento de estas características con las descripciones (de eventos valvulares) hechas por otros autores. Por lo tanto, esto lleva a pensar que el análisis cuantitativo de los SCF podría proveer un método no invasivo e innovador para detectar los eventos valvulares (cierre y apertura de las válvulas atrioventriculares y semilunares), y por consiguiente abrir una ventana de oportunidades para el estudio de la condición fetal y la vigilancia prenatal

    Smoking and Second Hand Smoking in Adolescents with Chronic Kidney Disease: A Report from the Chronic Kidney Disease in Children (CKiD) Cohort Study

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    The goal of this study was to determine the prevalence of smoking and second hand smoking [SHS] in adolescents with CKD and their relationship to baseline parameters at enrollment in the CKiD, observational cohort study of 600 children (aged 1-16 yrs) with Schwartz estimated GFR of 30-90 ml/min/1.73m2. 239 adolescents had self-report survey data on smoking and SHS exposure: 21 [9%] subjects had “ever” smoked a cigarette. Among them, 4 were current and 17 were former smokers. Hypertension was more prevalent in those that had “ever” smoked a cigarette (42%) compared to non-smokers (9%), p\u3c0.01. Among 218 non-smokers, 130 (59%) were male, 142 (65%) were Caucasian; 60 (28%) reported SHS exposure compared to 158 (72%) with no exposure. Non-smoker adolescents with SHS exposure were compared to those without SHS exposure. There was no racial, age, or gender differences between both groups. Baseline creatinine, diastolic hypertension, C reactive protein, lipid profile, GFR and hemoglobin were not statistically different. Significantly higher protein to creatinine ratio (0.90 vs. 0.53, p\u3c0.01) was observed in those exposed to SHS compared to those not exposed. Exposed adolescents were heavier than non-exposed adolescents (85th percentile vs. 55th percentile for BMI, p\u3c 0.01). Uncontrolled casual systolic hypertension was twice as prevalent among those exposed to SHS (16%) compared to those not exposed to SHS (7%), though the difference was not statistically significant (p= 0.07). Adjusted multivariate regression analysis [OR (95% CI)] showed that increased protein to creatinine ratio [1.34 (1.03, 1.75)] and higher BMI [1.14 (1.02, 1.29)] were independently associated with exposure to SHS among non-smoker adolescents. These results reveal that among adolescents with CKD, cigarette use is low and SHS is highly prevalent. The association of smoking with hypertension and SHS with increased proteinuria suggests a possible role of these factors in CKD progression and cardiovascular outcomes
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