756 research outputs found
Mathematical tools for identifying the fetal response to physical exercise during pregnancy
In the applied mathematics literature there exist a significant number of tools that can reveal the interaction between mother and fetus during rest and also during and after exercise. These tools are based on techniques from a number of areas such as signal processing, time series analysis, neural networks, heart rate variability as well as dynamical systems and chaos. We will briefly review here some of these methods, concentrating on a method of extracting the fetal heart rate from the mixed maternal-fetal heart rate signal, that is based on phase space reconstructio
Semi-blind source extraction algorithm for fetal electrocardiogram based on generalized autocorrelations and reference signals
AbstractBlind source extraction (BSE) has become one of the promising methods in the field of signal processing and analysis, which only desires to extract âinterestingâ source signals with specific stochastic property or features so as to save lots of computing time and resources. This paper addresses BSE problem, in which desired source signals have some available reference signals. Based on this prior information, we develop an objective function for extraction of temporally correlated sources. Maximizing this objective function, a semi-blind source extraction fixed-point algorithm is proposed. Simulations on artificial electrocardiograph (ECG) signals and the real-world ECG data demonstrate the better performance of the new algorithm. Moreover, comparisons with existing algorithms further indicate the validity of our new algorithm, and also show its robustness to the estimated error of time delay
Estrazione non invasiva del segnale elettrocardiografico fetale da registrazioni con elettrodi posti sullâaddome della gestante (Non-invasive extraction of the fetal electrocardiogram from abdominal recordings by positioning electrodes on the pregnant womanâs abdomen)
openIl cuore è il primo organo che si sviluppa nel feto, particolarmente nelle primissime settimane di
gestazione. Rispetto al cuore adulto, quello fetale ha una fisiologia ed unâanatomia significativamente
differenti, a causa della differente circolazione cardiovascolare. Il benessere fetale si valuta
monitorando lâattivitĂ cardiaca mediante elettrocardiografia fetale (ECGf). LâECGf invasivo (acquisito
posizionando elettrodi allo scalpo fetale) è considerato il gold standard, ma lâinvasivitĂ che lo
caratterizza ne limita la sua applicabilitĂ . Al contrario, lâuso clinico dellâECGf non invasivo (acquisito
posizionando elettrodi sullâaddome della gestante) è limitato dalla scarsa qualitĂ del segnale risultante.
LâECGf non invasivo si estrae da registrazioni addominali, che sono corrotte da differenti tipi di rumore,
fra i quali lâinterferenza primaria è rappresentata dallâECG materno. Il Segmented-Beat Modulation
Method (SBMM) è stato da me recentemente proposto come una nuova procedura di filtraggio basata
sul calcolo del template del battito cardiaco. SBMM fornisce una stima ripulita dellâECG estratto da
registrazioni rumorose, preservando la fisiologica variabilitĂ ECG del segnale originale. Questa
caratteristica è ottenuta grazie alla segmentazione di ogni battito cardiaco per indentificare i segmenti
QRS e TUP, seguito dal processo di modulazione/demodulazione (che include strecciamento e
compressione) del segmento TUP, per aggiustarlo in modo adattativo alla morfologia e alla durata di
ogni battito originario. Dapprima applicato allâECG adulto al fine di dimostrare la sua robustezza al
rumore, lâSBMM è stato poi applicato al caso fetale. Particolarmente significativi sono i risultati relativi
alle applicazioni su ECGf non invasivo, dove lâSBMM fornisce segnali caratterizzati da un rapporto
segnale-rumore comparabile a quello caratterizzante lâECGf invasivo. Tuttavia, lâSBMM può
contribuire alla diffusione dellâECGf non invasiva nella pratica clinica.The heart is the first organ that develops in the fetus, particularly in the very early stages
of pregnancy. Compared to the adult heart, the physiology and anatomy of the fetal heart
exhibit some significant differences. These differences originate from the fact that the fetal
cardiovascular circulation is different from the adult circulation. Fetal well-being
evaluation may be accomplished by monitoring cardiac activity through fetal
electrocardiography (fECG). Invasive fECG (acquired through scalp electrodes) is the
gold standard but its invasiveness limits its clinical applicability. Instead, clinical use of
non-invasive fECG (acquired through abdominal electrodes) has so far been limited by its
poor signal quality. Non-invasive fECG is extracted from the abdominal recording and is
corrupted by different kind of noise, among which maternal ECG is the main interference.
The Segmented-Beat Modulation Method (SBMM) was recently proposed by myself as a
new template-based filtering procedure able to provide a clean ECG estimation from a
noisy recording by preserving physiological ECG variability of the original signal. The
former feature is achieved thanks to a segmentation procedure applied to each cardiac
beat in order to identify the QRS and TUP segments, followed by a
modulation/demodulation process (involving stretching and compression) of the TUP
segments to adaptively adjust each estimated cardiac beat to the original beat morphology
and duration. SBMM was first applied to adult ECG applications, in order to demonstrate
its robustness to noise, and then to fECG applications. Particularly significant are the
results relative to the non-invasive applications, where SBMM provided fECG signals
characterized by a signal-to-noise ratio comparable to that characterizing invasive fECG.
Thus, SBMM may contribute to the spread of this noninvasive fECG technique in the
clinical practice.INGEGNERIA DELL'INFORMAZIONEAgostinelli, AngelaAgostinelli, Angel
Extracting Fetal Electrocardiogram from Being Pregnancy Based on Nonlinear Projection
Fetal heart rate extraction from the abdominal ECG is of great importance due to the information that carries in assessing appropriately the fetus well-being during pregnancy. In this paper, we describe a method to suppress the maternal signal and noise contamination to discover the fetal signal in a single-lead fetal ECG recordings. We use a locally linear phase space projection technique which has been used for noise reduction in deterministically chaotic signals. Henceforth, this method is capable of extracting fetal signal even when noise and fetal component are of comparable amplitude. The result is much better if the noise is much smaller (P wave and T wave can be discovered)
Non-invasive procedure for fetal electrocardiography
Antenatal fetal surveillance is a field of increasing importance in modern obstetrics.
Measurements extracted (such as fetal heart rate) from antenatal fetal monitoring techniques have the potential to reduce the social, personal and financial burdens of fetal death on families, health care systems and the community.
Techniques to monitor the fetus through pregnancy have been developed with the aim of providing information to enable the clinician to diagnose fetal wellbeing, characterise
development and detect abnormality. An early diagnosis before delivery may increase the effectiveness of the appropriate treatment.
Over the years, various research efforts have been carried out in the field of fetal
electrocardiography by attaching surface electrodes to the maternal body. Unfortunately the desired fetal heartbeat signals at the electrode output are buried in an additive mixture of undesired interference disturbances.
In this thesis, a non-invasive fetal electrocardiogram machine has been designed, constructed and implemented. This machine is composed of three modified electrocardiogram circuits and an external soundcard. Data was acquired from four surface electrodes placed on the maternal body.
Eleven pregnant subjects, with a gestation age between the 30th and 40th weeks of pregnancy, were used to investigate the validity of this machine. Fetal R-waves were detected in 72.7 percent of subjects.
The development of a non-invasive machine, capable of detecting and recording valuable anatomic and electrophysiological information of a fetus, represents an important tool in clinical and investigative obstetrics
Comparison of non-invasive electrohysterographic recording techniques for monitoring uterine dynamics
Non-invasive recording of uterine myoelectric activity (electrohysterogram, EHG) could provide an alternative to monitoring uterine dynamics by systems based on tocodynamometer (TOCO). Laplacian recording of bioelectric signals has been shown to give better spatial resolution and less interference than mono and bipolar surface recordings. The aim of this work was to study the signal quality obtaines from monopolar, bipolar and Laplacian techniques in EHG recordings, as well as to assess their ability to detect uterine contractions. Twenty-two recording sessions were carried out on singleton pregnant women during the active phase of labour. In each session the following simultaneous recordings were obtained: internal uterine pressure (IUP), external tension of abdominal wall (TOCO) and EHG signals (5 monopolar and 4 bipolar recordings, 1 discrete aproximation to the Laplacian of the potential and 2 estimates of the Laplacian from two active annular electrodes). The results obtained show that EHG is able to detect a higher number of uterine contractions than TOCO. Laplacian recordings give improved signal quality over monopolar and bipolar techniques, reduce maternal cardiac interference and improve the signal-to-noise ratio. The optimal position for recording EHG was found to be the uterine median axis and the lower centre-right umbilical zone.Research partly supported by the Spanish Ministerio de Ciencia y Tecnologia (TEC2010-16945) and the Universitat Politecnica de Valencia (PAID 2009/10-2298). The translation of this paper was funded by the Universitat Politecnica de Valencia, Spain.Alberola Rubio, J.; Prats Boluda, G.; Ye Lin, Y.; Valero, J.; Perales Marin, AJ.; Garcia Casado, FJ. (2013). Comparison of non-invasive electrohysterographic recording techniques for monitoring uterine dynamics. Medical Engineering and Physics. 35(12):1736-1743. https://doi.org/10.1016/j.medengphy.2013.07.008S17361743351
A Fetal Electrocardiogram Signal Extraction Algorithm Based on Fast One-Unit Independent Component Analysis with Reference
Fetal electrocardiogram (FECG) extraction is very important procedure for fetal health assessment. In this article, we propose a fast one-unit independent component analysis with reference (ICA-R) that is suitable to extract the FECG. Most previous ICA-R algorithms only focused on how to optimize the cost function of the ICA-R and payed little attention to the improvement of cost function. They did not fully take advantage of the prior information about the desired signal to improve the ICA-R. In this paper, we first use the kurtosis information of the desired FECG signal to simplify the non-Gaussian measurement function and then construct a new cost function by directly using a nonquadratic function of the extracted signal to measure its non-Gaussianity. The new cost function does not involve the computation of the difference between the function of the Gaussian random vector and that of the extracted signal, which is time consuming. Centering and whitening are also used to preprocess the observed signal to further reduce the computation complexity. While the proposed method has the same error performance as other improved one-unit ICA-R methods, it actually has lower computation complexity than those other methods. Simulations are performed separately on artificial and real-world electrocardiogram signals
Blind Source Separation for the Processing of Contact-Less Biosignals
(Spatio-temporale) Blind Source Separation (BSS) eignet sich fĂźr die Verarbeitung von Multikanal-Messungen im Bereich der kontaktlosen Biosignalerfassung. Ziel der BSS ist dabei die Trennung von (z.B. kardialen) Nutzsignalen und StĂśrsignalen typisch fĂźr die kontaktlosen Messtechniken. Das Potential der BSS kann praktisch nur ausgeschĂśpft werden, wenn (1) ein geeignetes BSS-Modell verwendet wird, welches der Komplexität der Multikanal-Messung gerecht wird und (2) die unbestimmte Permutation unter den BSS-Ausgangssignalen gelĂśst wird, d.h. das Nutzsignal praktisch automatisiert identifiziert werden kann. Die vorliegende Arbeit entwirft ein Framework, mit dessen Hilfe die Effizienz von BSS-Algorithmen im Kontext des kamera-basierten Photoplethysmogramms bewertet werden kann. Empfehlungen zur Auswahl bestimmter Algorithmen im Zusammenhang mit spezifischen Signal-Charakteristiken werden abgeleitet. AuĂerdem werden im Rahmen der Arbeit Konzepte fĂźr die automatisierte Kanalauswahl nach BSS im Bereich der kontaktlosen Messung des Elektrokardiogramms entwickelt und bewertet. Neuartige Algorithmen basierend auf Sparse Coding erwiesen sich dabei als besonders effizient im Vergleich zu Standard-Methoden.(Spatio-temporal) Blind Source Separation (BSS) provides a large potential to process distorted multichannel biosignal measurements in the context of novel contact-less recording techniques for separating distortions from the cardiac signal of interest. This potential can only be practically utilized (1) if a BSS model is applied that matches the complexity of the measurement, i.e. the signal mixture and (2) if permutation indeterminacy is solved among the BSS output components, i.e the component of interest can be practically selected. The present work, first, designs a framework to assess the efficacy of BSS algorithms in the context of the camera-based photoplethysmogram (cbPPG) and characterizes multiple BSS algorithms, accordingly. Algorithm selection recommendations for certain mixture characteristics are derived. Second, the present work develops and evaluates concepts to solve permutation indeterminacy for BSS outputs of contact-less electrocardiogram (ECG) recordings. The novel approach based on sparse coding is shown to outperform the existing concepts of higher order moments and frequency-domain features
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