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The onset of fetal pathologies can be screened during pregnancy by means of Fetal Heart Rate (FHR) monitoring and analysis. Noticeable advances in understanding FHR variations were obtained in the last twenty years, thanks to the introduction of quantitative indices extracted from the FHR signal. This study searches for discriminating Normal and Intra Uterine Growth Restricted (IUGR) fetuses by applying...
Fetal Heart Rate (FHR) monitoring represents a powerful tool for checking the arousal of pathological fetal conditions during pregnancy. This paper proposes a multivariate approach for the discrimination of Normal and Intra Uterine Growth Restricted (IUGR) fetuses based on a small set of parameters computed on the FHR signal. We collected FHR recordings in a population of 120 fetuses (60 normals and...
The main objective of this work is to develop and apply data mining methods for the prediction of patient outcome in nephrology care. Cardiovascular events have an incidence of 20% in the first year of hemodialysis (HD). Real data routinely collected during HD administration were extracted from the Fresenius Medical Care database EuCliD (39 independent variables) and used to develop a random forest...
Twin pregnancies carry an inherently higher risk than singleton pregnancies due to the increased chances of uterine growth restriction. It is thus desirable to monitor the wellbeing of the fetuses during gestation to detect potentially harmful conditions. The detection of fetal heart rate from the maternal abdominal ECG represents one possible approach for noninvasive and continuous fetal monitoring...
In the last decade new ideas were born about the temporal and spatial dynamics of intercellular calcium waves in astrocytes. In this paper we introduce a new approach to analyze the ways in which astrocytes communicate in cultures. We present a method to describe the spatial propagation of Ca2+ waves in vitro and a technique to compare the activity of different cells in vivo and in vitro under different...
One of the main problems that affect fluoroscopic imaging is the difficulty in coupling the recorded activity with the morphological information. The comprehension of fluorescence events in relationship with the internal structure of the cell can be very difficult. At this purpose, we developed a new method able to maximize the fluoroscopic movie quality. The method (maximum intensity enhancement,...
The purpose of this study is to evaluate the information content provided by the fluximetry information and the analysis of fetal heart rate (FHR) signals, obtained from cardiotocographic recordings, during prenatal monitoring, in a high risk population. The parameters assessed on FHR signals are divided in: (i) time domain parameters (ii) frequency domain parameters, and (iii) the complexity parameters:...
Since the late 90s both single and multi-electrode neuronal network recording signals have been characterized as endowed with long-term memory, i.e. a long-lasting decreasing correlation in the signal second-order statistics (e.g., autocorrelation function). Such a characteristic, typical of many fractal processes, indicate that the signal actual value strongly depends on its ldquopast historyrdquo...
The study of nonlinear long-term correlations in neuronal signals is a central topic for advanced neural signal processing. In particular, the existence of long-term correlations in neural signals recorded via multielectrode array (MEA) could provide interesting information about changes in interneuron communications. In this study we propose a new method for long-term correlation analysis of neuronal...
Neuroscience research is even more exploiting technologies developed for electronic engineering use: this is the case of Micro-Electrode Array (MEA) technology, an instrumentation which is able to acquire in vitro neuron spiking activity from a finite number of channels. In this work we present three models of synaptic neuronal network connections, called “Full-Connected”, “Hierarchical” and “Closed-Path”...
A lot of methods were created in last decade for the spatio-temporal analysis of multi-electrode array (MEA) neuronal data sets. The greater part of these methods does not consider the network as a whole but performs an analysis channel by channel. In this paper we illustrate how a very simple approach that considers the total network activity, is able to show interesting neuronal network features...
In the recent years neuroscience research is exploiting technologies initially developed only for electronic engineering use: this is the case of micro-electrode array (MEA) technology, where a finite number of channels acquires in vitro neural spiking activity. In this work we present a new method to process time data series from MEA trough an ad-hoc software-framework. Our aim is to build a classifier...
A crucial problem in fetal monitoring is the correct interpretation of biophysical measurements. An important question is therefore how to decide if fetal small dimensions are physiological or due to a pathological condition, such as intrauterine growth restriction (IUGR), a metabolic dysfunction which does not allow the fetus to achieve its genetically predetermined size. This study proposes to estimate...
In neurobiology an even bigger role is covered by acquisition and processing of data obtained from Micro-Electrode Array (MEA) technology, where a fixed number of channels record in vitro neural spiking activity. In this work we developed a software-tool implementing a specific method to analyze time data series of this spiking activity. Our aim is to quantify a global measure of correlation and dependence...
In this paper we deal with the problem of the interpretation of the fetal heart rate (FHR) signal. From literature is known that FHR contains both linear and non linear components. Starting from this consideration we analyzed FHR as a fractal time series and we evaluated its self similarity behavior using the Hurst's coefficient (H). We first evaluated the stationarity of FHR time series and then...
The purpose of this work is to characterize the heart rate variability (HRV) of patients affected by Congestive Heart Failure (CHF) and to find out the main difference between this pathological condition and the physiological state. Parameters adopted in this work are: the Detrended Fluctuation Analysis (DFA) and the Higuchi Exponent to assess long correlations and self-similarity; the regularity...
In the last years the home monitoring development is increased both for its capability as a real time tool to manage patients health and to reduce hospitalization costs. The home monitoring system is a complex structure that needs the collaboration of different disciplines, from medicine to engineering, and technologies. This project has been developed with the integration of different groups of research...
This study proposes new indexes extracted from fetal heart rate signal in order to identify intrauterine growth restricted (IUGR) fetuses and separate them from healthy small for gestational age ones (SGA). Unfortunately evidence-based guidelines for clinical surveillance are poor and lack of reliable indexes. Therefore we proposed new parameters: the Lempel Ziv complexity (LZC) and the multiscale...
The purpose of this work is to characterize the heart rate variability (HRV) of patients affected by congestive heart failure (CHF) and to find out the main difference between this pathological condition and the physiological state. Parameters adopted in this work are: the detrended fluctuation analysis (DFA) and the Higuchi exponent to assess long correlations and self-similarity; the regularity...
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