Fetal electrocardiograms, direct and abdominal with reference heartbeat annotations

Monitoring fetal heart rate (FHR) variability plays a fundamental role in fetal state assessment. Reliable FHR signal can be obtained from an invasive direct fetal electrocardiogram (FECG), but this is limited to labour. Alternative abdominal (indirect) FECG signals can be recorded during pregnancy and labour. Quality, however, is much lower and the maternal heart and uterine contractions provide sources of interference. Here, we present ten twenty-minute pregnancy signals and 12 five-minute labour signals. Abdominal FECG and reference direct FECG were recorded simultaneously during labour. Reference pregnancy signal data came from an automated detector and were corrected by clinical experts. The resulting dataset exhibits a large variety of interferences and clinically significant FHR patterns. We thus provide the scientific community with access to bioelectrical fetal heart activity signals that may enable the development of new methods for FECG signals analysis, and may ultimately advance the use and accuracy of abdominal electrocardiography methods.Web of Science71art. no. 20

Estrazione non invasiva del segnale elettrocardiografico fetale da registrazioni con elettrodi posti sull’addome della gestante (Non-invasive extraction of the fetal electrocardiogram from abdominal recordings by positioning electrodes on the pregnant woman’s 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 un’anatomia significativamente differenti, a causa della differente circolazione cardiovascolare. Il benessere fetale si valuta monitorando l’attività cardiaca mediante elettrocardiografia fetale (ECGf). L’ECGf invasivo (acquisito posizionando elettrodi allo scalpo fetale) è considerato il gold standard, ma l’invasività che lo caratterizza ne limita la sua applicabilità. Al contrario, l’uso clinico dell’ECGf non invasivo (acquisito posizionando elettrodi sull’addome della gestante) è limitato dalla scarsa qualità del segnale risultante. L’ECGf non invasivo si estrae da registrazioni addominali, che sono corrotte da differenti tipi di rumore, fra i quali l’interferenza primaria è rappresentata dall’ECG 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 dell’ECG estratto da registrazioni rumorose, preservando la fisiologica variabilità 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 all’ECG adulto al fine di dimostrare la sua robustezza al rumore, l’SBMM è stato poi applicato al caso fetale. Particolarmente significativi sono i risultati relativi alle applicazioni su ECGf non invasivo, dove l’SBMM fornisce segnali caratterizzati da un rapporto segnale-rumore comparabile a quello caratterizzante l’ECGf invasivo. Tuttavia, l’SBMM può contribuire alla diffusione dell’ECGf 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

Hybrid Methods for Fetal Electrocardiogram Extraction

Cílem této diplomové práce je neinvazivní zpracování plodového elektrokardiogramu (fEKG) pomocí hybridních metod, které kombinují dvě a více transabdominálních metod. Teoretická část práce je věnována problematice plodové elektrokardiografie, rozsáhlé rešerši již existujících hybridních metod a matematickému popisu implementovaných metod. Experimentální část je primárně zaměřena na testování a analýzu vzájemných kombinací analýzy nezávislých komponent (ICA), vlnkové transformace (WT), prahování vlnkových koeficientů (WS), empirické modální dekompozice (EMD), souboru empirické modální dekompozice (EEMD) a analýzy hlavních komponent (PCA). Hodnocení extrakce je provedeno na základě stanovení variability tepové frekvence plodu (fHRV). Použitím hybridních metod je v této práci dosaženo lepších výsledků než při samotném použití metody ICA. Výstupem práce je také implementace metod v grafickém uživatelské rozhraní v prostředí Matlab.The aim of this thesis is non-invasive processing of fetal electrocardiogram (fECG) using hybrid methods, which combine two or more transabdominal methods. The theoretical part is dedicated to the problems of fetal electrocardiography, complex overview of already existing hybrid methods and mathematical description of implemented methods. The experimental part is primarily focused on testing and analysis combinations of independent component analysis (ICA), wavelet transform (WT), wavelet shrinkage (WS), empirical mode decomposition (EMD), ensemble empirical mode decomposition (EEMD) and principal component analysis (PCA). The evaluation of extraction quality is based on the determination of fetal heart rate variability (fHRV). The performence of hybrid methods in this thesis is better than usage of individual ICA method. The output of the thesis is also implementation of methods in the graphical user interface in Matlab.450 - Katedra kybernetiky a biomedicínského inženýrstvívýborn

Hybrid Methods for Processing of Fetal Electrocardiogram

Tato doktorská disertační práce se zaměřuje na návrh, realizaci a následnou verifikaci nového typu hybridního extrakčního systému pro zpracování neinvazivního plodového elektrokardiogramu (NI-fEKG). Navržený systém sdružuje výhody jednotlivých adaptivních a neadaptivních metod. Tato práce ověřuje dva inovativní hybridní systémy s názvem ICA-ANFIS-WT a ICA-RLS-WT. Jedná se o kombinaci analýzy nezávislých komponent (ICA), adaptivního neuro-fuzzy inferenčního systému (ANFIS) nebo algoritmu založeném na rekurzivní optimální adaptaci (RLS) a vlnkové transformace (WT). Studie byla realizována na datech z klinické praxe (rozšířená databáze abdominálního a přímého fetálního elektrokardiogramu (ADFECGDB) a databáze EKG physionet challenge 2013) z pohledu neinvazivního monitorování fetální tepové frekvence (fHR) na základě stanovení celkové pravděpodobnosti správné detekce (ACC), senzitivity (SE), pozitivní prediktivní hodnoty (PPV) a harmonického průměru mezi SE a PPV (F1). Funkcionalita systému byla verifikována vůči relevantní referenci dané anotacemi. Tato práce ukázala, že hybridní systém ICA-RLS-WT dosáhl lepších výsledků než ICA-ANFIS-WT. Při experimentu na záznamech z databáze ADFECGDB dosáhla hybridní metoda ICA-RLS-WT hodnoty ACC > 80 % u 10 z 12 záznamů a hybridní metoda ICA-ANFIS-WT hodnoty ACC > 80 % pouze u 6 z 12 záznamů. Při experimentu na záznamech z databáze EKG physionet challenge 2013 dosáhla hybridní metoda ICA-RLS-WT hodnoty ACC > 80 % u 13 z 25 záznamů a hybridní metoda ICA-ANFIS-WT hodnoty ACC > 80 % pouze u 7 z 25 záznamů. Oba navržené hybridní systémy dosáhly prokazatelně lepších výsledků než jednotlivé metody v předchozích studiích.This dissertation focuses on the design, implementation and subsequent verification of a new type of hybrid extraction system for noninvasive fetal electrocardiogram (NI-fECG) processing. The designed system combines the advantages of individual adaptive and non-adaptive methods. This thesis reviews two innovative hybrid systems called ICA-ANFIS-WT and ICA-RLS-WT. This is a combination of independent component analysis (ICA), adaptive neuro-fuzzy inference system (ANFIS) or recursive least squares (RLS) algorithm and wavelet transform (WT). The study was conducted on clinical practice data (extended abdominal and direct fetal electrocardiogram database (ADFECGDB) and Physionet Challenge 2013 database) from the perspective of non-invasive fetal heart rate (fHR) monitoring based on the determination of the overall probability of correct detection (ACC), sensitivity (SE), positive predictive value (PPV) and harmonic mean between SE and PPV (F1). System functionality was verified against a relevant reference obtained by annotations. The study showed that ICA-RLS-WT hybrid system achieve better results than ICA-ANFIS-WT. During experiment on ADFECGDB database, the ICA-RLS-WT hybrid system reached ACC > 80 % on 10 recordings out of 12 and the ICA-ANFIS-WT hybrid system reached ACC > 80 % only on 6 recordings out of 12. During experiment on Physionet Challenge 2013 database the ICA-RLS-WT hybrid system reached ACC > 80 % on 13 recordings out of 25 and the ICA-ANFIS-WT hybrid system reached ACC > 80 % only on 7 recordings out of 25. Both hybrid systems achieve provably better results than the individual methods tested in previous studies.450 - Katedra kybernetiky a biomedicínského inženýrstvívyhově