Use of Multiscale Entropy to Characterize Fetal Autonomic Development

The idea that uterine environment and adverse events during fetal development could increase the chances of the diseases in adulthood was first published by David Barker in 1998. Since then, investigators have been employing several methods and methodologies for studying and characterizing the ontological development of the fetus, e.g., fetal movement, growth and cardiac metrics. Even with most recent and developed methods such as fetal magnetocardiography (fMCG), investigators are continuously challenged to study fetal development; the fetus is inaccessible. Finding metrics that realize the full capacity of characterizing fetal ontological development remains a technological challenge. In this thesis, the use and value of multiscale entropy to characterize fetal maturation across third trimester of gestation is studied. Using multiscale entropy obtained from participants of a clinical trial, we show that MSE can characterize increasing complexity due to maturation in the fetus, and can distinguish a growing and developing fetal system from a mature system where loss of irregularity is due to compromised complexity from increasing physiologic load. MSE scales add a nonlinear metric that seems to accurately reflect the ontological development of the fetus and hold promise for future use to investigate the effects of maternal stress, intrauterine growth restriction, or predict risk for sudden infant death syndrome

A Comprehensive Review of Techniques for Processing and Analyzing Fetal Heart Rate Signals

The availability of standardized guidelines regarding the use of electronic fetal monitoring (EFM) in clinical practice has not effectively helped to solve the main drawbacks of fetal heart rate (FHR) surveillance methodology, which still presents inter- and intra-observer variability as well as uncertainty in the classification of unreassuring or risky FHR recordings. Given the clinical relevance of the interpretation of FHR traces as well as the role of FHR as a marker of fetal wellbeing autonomous nervous system development, many different approaches for computerized processing and analysis of FHR patterns have been proposed in the literature. The objective of this review is to describe the techniques, methodologies, and algorithms proposed in this field so far, reporting their main achievements and discussing the value they brought to the scientific and clinical community. The review explores the following two main approaches to the processing and analysis of FHR signals: traditional (or linear) methodologies, namely, time and frequency domain analysis, and less conventional (or nonlinear) techniques. In this scenario, the emerging role and the opportunities offered by Artificial Intelligence tools, representing the future direction of EFM, are also discussed with a specific focus on the use of Artificial Neural Networks, whose application to the analysis of accelerations in FHR signals is also examined in a case study conducted by the authors

Intrapartum hypoxia and power spectral analysis of fetal heart rate variability

Reliable detection of intrapartum fetal acidosis is crucial for preventing morbidity. Hypoxia-related changes of fetal heart rate variability (FHRV) are controlled by the autonomic nervous system. Subtle changes in FHRV that cannot be identified by inspection can be detected and quantified by power spectral analysis. Sympathetic activity relates to low-frequency FHRV and parasympathetic activity to both low- and high-frequency FHRV. The aim was to study whether intra partum fetal acidosis can be detected by analyzing spectral powers of FHRV, and whether spectral powers associate with hypoxia-induced changes in the fetal electrocardiogram and with the pH of fetal blood samples taken intrapartum. The FHRV of 817 R-R interval recordings, collected as a part of European multicenter studies, were analyzed. Acidosis was defined as cord pH ≤ 7.05 or scalp pH ≤ 7.20, and metabolic acidosis as cord pH ≤ 7.05 and base deficit ≥ 12 mmol/l. Intrapartum hypoxia increased the spectral powers of FHRV. As fetal acidosis deepened, FHRV decreased: fetuses with significant birth acidosis had, after an initial increase, a drop in spectral powers near delivery, suggesting a breakdown of fetal compensation. Furthermore, a change in excess of 30% of the low-to-high frequency ratio of FHRV was associated with fetal metabolic acidosis. The results suggest that a decrease in the spectral powers of FHRV signals concern for fetal wellbeing. A single measure alone cannot be used to reveal fetal hypoxia since the spectral powers vary widely intra-individually. With technical developments, continuous assessment of intra-individual changes in spectral powers of FHRV might aid in the detection of fetal compromise due to hypoxia.Siirretty Doriast

Fetal autonomic cardiac response during pregnancy and labour

Timely recognition of fetal distress, during pregnancy and labour, in order to intervene adequately is of major importance to avoid neonatal morbidity and mortality. As discussed in chapter 1, the cardiotocogram (CTG) might be a useful screening test for fetal monitoring but it has insufficient specificity and requires additional diagnostic tests in case of suspected fetal compromise to avoid unnecessary operative deliveries. Potential additional techniques used in clinical practice are fetal scalp blood sampling (FBS) and ST-waveform analysis of the fetal electrocardiogram (ECG; STAN®). However, publications on these techniques provide limited support for the use of these methods in the presence of a non-reassuring CTG for reducing caesarean sections. In addition, these techniques are invasive and can therefore only be used during labour at the term or the near term period. Consequently, it is of great clinical importance that additional methods are developed that contribute to more reliable assessment of fetal condition. Preferably, this information is obtained non-invasively. Valuable additional information on the fetal condition can possibly be obtained by spectral analysis of fetal heart rate variability (HRV). The fetal heart rate fluctuates under the control of the autonomic part of the central nervous system. The autonomic cardiac modulation is discussed in chapter 2. The sympathetic and parasympathetic nervous systems typically operate on partly different timescales. Time-frequency analysis (spectral analysis) of fetal beat-to-beat HRV can hence quantify sympathetic and parasympathetic modulation and characterise autonomic cardiac control . The low frequency (LF) component of HRV is associated with both sympathetic and parasympathetic modulation while the high frequency (HF) component is associated with parasympathetic modulation alone2. Spectral estimates of HRV might indirectly reflect fetal wellbeing and increase insight in the human fetal autonomic cardiac response. In chapter 3, technical details for retrieving fetal beat-to-beat heart rate and its spectral estimates are provided. In this thesis spectral analysis of fetal HRV is investigated. The first objective is to study the value of spectral analysis of fetal HRV as a tool to assess fetal wellbeing during labour at term. The second objective is to monitor spectral estimates of fetal HRV, non-invasively, during gestation to increase insight in the development of human fetal autonomic cardiac control. Since Akselrod reported the relation between autonomic nervous system modulation and LF and HF peaks in frequency domain1, frequency analysis of RR interval fluctuations is widely performed . For human adults, standards for HRV measurement and physiological interpretation have been developed2. Although HRV parameters are reported to be highly prognostic in human adults in case of cardiac disease, little research is done towards the value of these parameters in assessing fetal distress in the human fetus, as shown in chapter 4. In this chapter, the literature about time-frequency analysis of human fetal HRV is reviewed in order to determine the value of spectral estimates for fetal surveillance. Articles that described spectral analysis of human fetal HRV and compared the energy in spectral bands with fetal bloodgas values were included. Only six studies met our inclusion criteria. One study found an initial increase in LF power during the first stage of fetal compromise, which was thought to point to stress-induced sympathetic hyperactivity3. Five out of six studies showed a decrease in LF power in case of fetal distress , , , , ,. This decrease in LF power in case of severe fetal compromise was thought to be the result of immaturity or decompensation of the fetal autonomic nervous system. These findings support the hypothesis that spectral analysis of fetal HRV might be a promising method for fetal surveillance. All studies included in the literature review used absolute values of LF and HF power. Although absolute LF and HF power of HRV provide useful information on autonomic modulation, especially when considering fetal autonomic development, LF and HF power may also be measured in normalised units. Normalised LF (LFn) and normalised HF power (HFn) of HRV represent the relative value of each power component in proportion to the total power2. Adrenergic stimulation can cause a sympathetically-modulated increase in fetal heart rate . A negative correlation however exists between heart rate and HRV . As a result, the sympathetic stimulation can decrease the total power of HRV and even the absolute LF power. When normalising the absolute LF (and HF) with respect to the total power, a shift in activity from HFn to LFn might become visible, revealing the expected underlying sympathetic activity. Thus, because changes in total power influence absolute spectral estimates in the same direction, normalised values of LF and HF power seem more suitable for fetal monitoring. In other words, normalised spectral estimates detect relative changes that are no longer masked by changes in total power2. LFn and HFn power are calculated by dividing LF and HF power, respectively, by total power and represent the controlled and balanced behaviour of the two branches of the autonomic nervous system2. In chapter 5 we hypothesised that the autonomic cardiovascular control is functional in fetuses at term, and that LFn power increases in case of distress due to increased sympathetic modulation. During labour at term, ten acidaemic fetuses were compared with ten healthy fetuses. During the last 30 minutes of labour, acidaemic fetuses had significantly higher LFn power and lower HFn power than control fetuses, which points to increased sympathetic modulation. No differences in absolute LF or HF power were found between both groups. The observed differences in normalised spectral estimates of HRV were not observed earlier in labour. In conclusion, it seems that the autonomic nervous system of human fetuses at term responds adequately to severe stress during labour. Normalised spectral estimates of HRV might be able to discriminate between normal and abnormal fetal condition. Although we found significant differences in normalised spectral estimates between healthy and acidaemic fetuses, we wondered whether spectral power of HRV is also related to fetal distress in an earlier stage. The next step in chapter 6 was therefore, to investigate whether spectral estimates are related to fetal scalp blood pH during labour. Term fetuses during labour, in cephalic presentation, that underwent one or more scalp blood samples were studied. Beat-to-beat fetal heart rate segments, preceding the scalp blood measurement, were used to calculate spectral estimates. In total 39 FBS from 30 patients were studied. We found that normalised spectral estimates are related to fetal scalp blood pH while absolute spectral estimates are not related to fetal pH. It was further demonstrated that LFn power is negatively related and HFn power is positively related to fetal pH. These findings point to increased sympathetic and decreased parasympathetic cardiac modulation in human fetuses at term upon decrease of their pH value. This study confirms the hypothesis that normalised spectral values of fetal HRV are related to fetal distress in an early stage. Previous studies showed that absolute LF and HF power increase as pregnancy progresses, which is attributed to fetal autonomic maturation , . Since it is yet unclear how LFn and HFn evolve with progressing pregnancy, before using spectral analysis for fetal monitoring, it has to be determined whether gestational age has to be corrected for. In addition, fetal autonomic fluctuations, and thus spectral estimates of HRV, are influenced by fetal behavioural state . Since these states continue to change during labour , thorough understanding of the way in which these changes in state influence spectral power is necessary for the interpretation of spectral values during labour at term. Therefore, in chapter 7, we examined whether differences in spectral estimates exist between healthy near term and post term fetuses during labour. In case such differences do exist, they should be taken into consideration for fetal monitoring. The quiet and active sleep states were studied separately to determine the influence of fetal behavioural state on spectral estimates of HRV during labour around term. No significant differences in spectral estimates were found between near term and post term fetuses during active sleep. During quiet sleep, LFn power was lower and HF and HFn power were higher in post term compared to near term fetuses, no significant differences in LF power were observed between both groups. LF, HF and LFn power were higher and HFn power was lower during active sleep compared to quiet sleep in both groups. This seems to point to sympathetic predominance during the active state in fetuses around term. In addition, post term parasympathetic modulation during rest seems increased compared to near term. In conclusion, fetal behavioural state and gestational age cause a considerable variability in spectral estimates in fetuses during labour, around term, which should be taken into consideration when using spectral estimates for fetal monitoring. In chapters 4 to 6, spectral estimates of beat-to-beat fetal HRV were studied using fetal ECG recordings that were obtained directly from the fetal scalp during labour. However, the second objective of this thesis is to obtain spectral estimates non-invasively during gestation to increase insight in the development of human fetal autonomic cardiac control. The fetal ECG is also present on the maternal abdomen, although much smaller in amplitude and obscured by the maternal ECG and noise. Chapter 8 focused on non-invasive measurement of the fetal ECG from the maternal abdomen. These measurements allow for obtaining beat-to-beat fetal heart rate non-invasively. Therefore, this method can be used to obtain spectral estimates of fetal HRV throughout gestation. Although abdominal recording of the fetal ECG may offer valuable additional information, it is troubled by poor signal-to-noise ratios (SNR) during certain parts of pregnancy, e.g. during the immature period and during the vernix period. To increase the usability of abdominal fetal ECG recordings, an algorithm was developed that uses a priori knowledge on the physiology of the fetal heart to enhance the fetal ECG components in multi-lead abdominal fetal ECG recordings, before QRS-detection. Evaluation of the method on generated fetal ECG recordings with controlled SNR showed excellent results. The method for non-invasive fetal ECG and beat-to-beat heart rate detection presented in chapter 8 was used for analysis in chapter 9. The feasibility of this method in a longitudinal patient study was investigated. In addition, changes in spectral estimates of HRV during pregnancy were studied and related to fetal rest-activity state to study the development of fetal autonomic cardiac control. We found that approximately 3% of non-invasive fetal ECG recordings could be used for spectral analysis. Therefore, improvement of both equipment and algorithms is still needed to obtain more good-quality data. The percentage of successfully retrieved data depends on gestational age. Before 18 and between 30 and 34 weeks no good-quality beat-to-beat heart rate data were available. We found an increase in LF and HF power of fetal HRV with increasing gestational age, between 21 to 30 weeks of gestation. This increase in LF and HF power is probably due to increased sympathetic and parasympathetic modulation and might be a sign of autonomic development. Furthermore, we found sympathetic predominance during the active state compared to the quiet state in near term fetuses (34 to 41 weeks of gestation), comparable to the results observed during labour around term. During 34 to 41 weeks a (non-significant) decrease in LF and LFn power and a (non-significant) increase in HF and HFn power were observed. These non-significant changes in spectral estimates in near term fetuses might be associated with changes in fetal rest-activity state and increased parasympathetic modulation as pregnancy progresses. However, more research is needed to confirm this

Symbolic Dynamics Analysis: a new methodology for foetal heart rate variability analysis

Cardiotocography (CTG) is a widespread foetal diagnostic methods. However, it lacks of objectivity and reproducibility since its dependence on observer's expertise. To overcome these limitations, more objective methods for CTG interpretation have been proposed. In particular, many developed techniques aim to assess the foetal heart rate variability (FHRV). Among them, some methodologies from nonlinear systems theory have been applied to the study of FHRV. All the techniques have proved to be helpful in specific cases. Nevertheless, none of them is more reliable than the others. Therefore, an in-depth study is necessary. The aim of this work is to deepen the FHRV analysis through the Symbolic Dynamics Analysis (SDA), a nonlinear technique already successfully employed for HRV analysis. Thanks to its simplicity of interpretation, it could be a useful tool for clinicians. We performed a literature study involving about 200 references on HRV and FHRV analysis; approximately 100 works were focused on non-linear techniques. Then, in order to compare linear and non-linear methods, we carried out a multiparametric study. 580 antepartum recordings of healthy fetuses were examined. Signals were processed using an updated software for CTG analysis and a new developed software for generating simulated CTG traces. Finally, statistical tests and regression analyses were carried out for estimating relationships among extracted indexes and other clinical information. Results confirm that none of the employed techniques is more reliable than the others. Moreover, in agreement with the literature, each analysis should take into account two relevant parameters, the foetal status and the week of gestation. Regarding the SDA, results show its promising capabilities in FHRV analysis. It allows recognizing foetal status, gestation week and global variability of FHR signals, even better than other methods. Nevertheless, further studies, which should involve even pathological cases, are necessary to establish its reliability.La Cardiotocografia (CTG) è una diffusa tecnica di diagnostica fetale. Nonostante ciò, la sua interpretazione soffre di forte variabilità intra- e inter- osservatore. Per superare tali limiti, sono stati proposti più oggettivi metodi di analisi. Particolare attenzione è stata rivolta alla variabilità della frequenza cardiaca fetale (FHRV). Nel presente lavoro abbiamo suddiviso le tecniche di analisi della FHRV in tradizionali, o lineari, e meno convenzionali, o non-lineari. Tutte si sono rivelate efficaci in casi specifici ma nessuna si è dimostrata più utile delle altre. Pertanto, abbiamo ritenuto necessario effettuare un’indagine più dettagliata. In particolare, scopo della tesi è stato approfondire una specifica metodologia non-lineare, la Symbolic Dynamics Analysis (SDA), data la sua notevole semplicità di interpretazione che la renderebbe un potenziale strumento di ausilio all’attività clinica. Sono stati esaminati all’incirca 200 riferimenti bibliografici sull’analisi di HRV e FHRV; di questi, circa 100 articoli specificamente incentrati sulle tecniche non-lineari. E’ stata condotta un’analisi multiparametrica su 580 tracciati CTG di feti sani per confrontare le metodologie adottate. Sono stati realizzati due software, uno per l’analisi dei segnali CTG reali e l’altro per la generazione di tracciati CTG simulati. Infine, sono state effettuate analisi statistiche e di regressione per esaminare le correlazioni tra indici calcolati e parametri di interesse clinico. I risultati dimostrano che nessuno degli indici calcolati risulta più vantaggioso rispetto agli altri. Inoltre, in accordo con la letteratura, lo stato del feto e le settimane di gestazione sono parametri di riferimento da tenere sempre in considerazione per ogni analisi effettuata. Riguardo la SDA, essa risulta utile all’analisi della FHRV, permettendo di distinguere – meglio o al pari di altre tecniche – lo stato del feto, la settimana di gestazione e la variabilità complessiva del segnale. Tuttavia, sono necessari ulteriori studi, che includano anche casi di feti patologici, per confermare queste evidenze

Энтропия перестановок сердечного ритма плода при изъятии ударов сердца матери

Розробка і застосування методів ідентифікації фізіологічних станів для матері та плоду, заснованих на неінвазивному моніторингу серцевої діяльності, має велике клінічне значення під час вагітності. У даній роботі досліджуються нові можливості застосування ентропії перестановок (ЕП) – одного з нелінійних методів часового аналізу серцевих скорочень плода. ЕП використовується для описання ритмограм плоду з метою отримання нових даних щодо характеристик серцевого ритму плода. Використовується нова методика виділення фетальної електрокардіограми (фЕКГ), заснована на фільтрації у вейвлет-просторі та реконструкції фЕКГ з використанням коефіцієнтів деталізації. Ентропія перестановок застосовується для отримання числових значень та часових залежностей ЕП для серцевого ритму у випадку необроблених ритмограм плоду та ритмограм, отриманих з виділеними ударами серця матері. Припущення про необхідність видаляти удари серця матері із початкової ритмограми підтверджується різницею у значеннях ЕП для двох випадків.Development and application of maternal and fetal physiological states identification techniques based on the noninvasive electrical heart activity monitoring is of great clinical importance during pregnancy. In this paper, new possibilities of applying one of nonlinear measures of time series behavior analysis to the fetal heart rates are explored, and permutation entropy (PE) characteristics of fetal rhythmograms are used to get new insight on the fetal heart rhythm parameters. The new technique of fetal electrocardiogram (fECG) extraction is used, based on filtration in wavelet domain and reconstruction of fECG using detalization coefficients. Permutation entropy analysis is applied to obtain PE values and trends for the case of raw fetal rhythmograms and those obtained with excluded maternal heart beats. The assumption about the need to extract maternal heartbeats from initial rhythmogram is proven by the difference in PE values for two cases.Разработка и применение методов идентификации физиологических состояний матери и плода, основанных на неинвазивном мониторинге сердечной деятельности, имеет большое клиническое значение при беременности. В данной работе исследуются новые возможности применения энтропии перестановок (ЭП) – одного из нелинейных методов временного анализа сердечных сокращений плода. ЭП используется для описания ритмограмм плода с целью получения новых данных о характеристиках сердечного ритма плода. Используется новая методика выделения фетальной электрокардиограммы (фЭКГ), основанная на фильтрации в вейвлет-пространстве и реконструкции фЭКГ с использованием коэффициентов детализации. Энтропия перестановок применяется для получения числовых значений и временных зависимостей ЭП для сердечного ритма в случае необработанных ритмограмм плода и ритмограмм, полученных с выделенными ударами сердца матери. Предположение о необходимости удалять удары сердца матери из начальной ритмограммы подтверждается разницей в значениях ЭП для двух случаев

Extraction and Detection of Fetal Electrocardiograms from Abdominal Recordings

The non-invasive fetal ECG (NIFECG), derived from abdominal surface electrodes, offers novel diagnostic possibilities for prenatal medicine. Despite its straightforward applicability, NIFECG signals are usually corrupted by many interfering sources. Most significantly, by the maternal ECG (MECG), whose amplitude usually exceeds that of the fetal ECG (FECG) by multiple times. The presence of additional noise sources (e.g. muscular/uterine noise, electrode motion, etc.) further affects the signal-to-noise ratio (SNR) of the FECG. These interfering sources, which typically show a strong non-stationary behavior, render the FECG extraction and fetal QRS (FQRS) detection demanding signal processing tasks. In this thesis, several of the challenges regarding NIFECG signal analysis were addressed. In order to improve NIFECG extraction, the dynamic model of a Kalman filter approach was extended, thus, providing a more adequate representation of the mixture of FECG, MECG, and noise. In addition, aiming at the FECG signal quality assessment, novel metrics were proposed and evaluated. Further, these quality metrics were applied in improving FQRS detection and fetal heart rate estimation based on an innovative evolutionary algorithm and Kalman filtering signal fusion, respectively. The elaborated methods were characterized in depth using both simulated and clinical data, produced throughout this thesis. To stress-test extraction algorithms under ideal circumstances, a comprehensive benchmark protocol was created and contributed to an extensively improved NIFECG simulation toolbox. The developed toolbox and a large simulated dataset were released under an open-source license, allowing researchers to compare results in a reproducible manner. Furthermore, to validate the developed approaches under more realistic and challenging situations, a clinical trial was performed in collaboration with the University Hospital of Leipzig. Aside from serving as a test set for the developed algorithms, the clinical trial enabled an exploratory research. This enables a better understanding about the pathophysiological variables and measurement setup configurations that lead to changes in the abdominal signal's SNR. With such broad scope, this dissertation addresses many of the current aspects of NIFECG analysis and provides future suggestions to establish NIFECG in clinical settings.:Abstract Acknowledgment Contents List of Figures List of Tables List of Abbreviations List of Symbols (1)Introduction 1.1)Background and Motivation 1.2)Aim of this Work 1.3)Dissertation Outline 1.4)Collaborators and Conflicts of Interest (2)Clinical Background 2.1)Physiology 2.1.1)Changes in the maternal circulatory system 2.1.2)Intrauterine structures and feto-maternal connection 2.1.3)Fetal growth and presentation 2.1.4)Fetal circulatory system 2.1.5)Fetal autonomic nervous system 2.1.6)Fetal heart activity and underlying factors 2.2)Pathology 2.2.1)Premature rupture of membrane 2.2.2)Intrauterine growth restriction 2.2.3)Fetal anemia 2.3)Interpretation of Fetal Heart Activity 2.3.1)Summary of clinical studies on FHR/FHRV 2.3.2)Summary of studies on heart conduction 2.4)Chapter Summary (3)Technical State of the Art 3.1)Prenatal Diagnostic and Measuring Technique 3.1.1)Fetal heart monitoring 3.1.2)Related metrics 3.2)Non-Invasive Fetal ECG Acquisition 3.2.1)Overview 3.2.2)Commercial equipment 3.2.3)Electrode configurations 3.2.4)Available NIFECG databases 3.2.5)Validity and usability of the non-invasive fetal ECG 3.3)Non-Invasive Fetal ECG Extraction Methods 3.3.1)Overview on the non-invasive fetal ECG extraction methods 3.3.2)Kalman filtering basics 3.3.3)Nonlinear Kalman filtering 3.3.4)Extended Kalman filter for FECG estimation 3.4)Fetal QRS Detection 3.4.1)Merging multichannel fetal QRS detections 3.4.2)Detection performance 3.5)Fetal Heart Rate Estimation 3.5.1)Preprocessing the fetal heart rate 3.5.2)Fetal heart rate statistics 3.6)Fetal ECG Morphological Analysis 3.7)Problem Description 3.8)Chapter Summary (4)Novel Approaches for Fetal ECG Analysis 4.1)Preliminary Considerations 4.2)Fetal ECG Extraction by means of Kalman Filtering 4.2.1)Optimized Gaussian approximation 4.2.2)Time-varying covariance matrices 4.2.3)Extended Kalman filter with unknown inputs 4.2.4)Filter calibration 4.3)Accurate Fetal QRS and Heart Rate Detection 4.3.1)Multichannel evolutionary QRS correction 4.3.2)Multichannel fetal heart rate estimation using Kalman filters 4.4)Chapter Summary (5)Data Material 5.1)Simulated Data 5.1.1)The FECG Synthetic Generator (FECGSYN) 5.1.2)The FECG Synthetic Database (FECGSYNDB) 5.2)Clinical Data 5.2.1)Clinical NIFECG recording 5.2.2)Scope and limitations of this study 5.2.3)Data annotation: signal quality and fetal amplitude 5.2.4)Data annotation: fetal QRS annotation 5.3)Chapter Summary (6)Results for Data Analysis 6.1)Simulated Data 6.1.1)Fetal QRS detection 6.1.2)Morphological analysis 6.2)Own Clinical Data 6.2.1)FQRS correction using the evolutionary algorithm 6.2.2)FHR correction by means of Kalman filtering (7)Discussion and Prospective 7.1)Data Availability 7.1.1)New measurement protocol 7.2)Signal Quality 7.3)Extraction Methods 7.4)FQRS and FHR Correction Algorithms (8)Conclusion References (A)Appendix A - Signal Quality Annotation (B)Appendix B - Fetal QRS Annotation (C)Appendix C - Data Recording GU

Automatická detekce pohybu plodu pomocí abdominální elektrokardiografie

The aim of the bachelor’s thesis is to introduce an extensive review of fetal movement monitoring methods. The theoretical part describes currently available fetal monitoring methods, primarily non-invasive fetal electrocardiography. The thesis continues to thoroughly describe and characterize fetal movements and the current possibilities of fetal movement detection. The output of the bachelor’s thesis is an analysis of the manifestation of fetal movements on various biological signals, which were further used in the design and development of the graphical user interface for automatic fetal movement detection. Developed fetal movement detection algorithms were evaluated on clinical practice data.Hlavním cílem předložené bakalářské práce je představit rozsáhlý přehled metod sledování pohybu plodu. V teoretické části jsou popsány momentálně dostupné metody monitorování plodu, především neinvazivní fetální elektrokardiografie. Předložená bakalářská práce dále důkladně popisuje a charakterizuje pohyby plodu a současné možnosti detekce pohybu plodu. Výstupem bakalářské práce je analýza projevů pohybů plodu na různých biologických signálech, které byly dále využity při návrhu a vývoji grafického uživatelského rozhraní pro automatickou detekci pohybu plodu. Vyvinuté algoritmy byly následně vyhodnoceny na datech z klinické praxe.450 - Katedra kybernetiky a biomedicínského inženýrstvívýborn

Human Health Engineering Volume II

In this Special Issue on “Human Health Engineering Volume II”, we invited submissions exploring recent contributions to the field of human health engineering, i.e., technology for monitoring the physical or mental health status of individuals in a variety of applications. Contributions could focus on sensors, wearable hardware, algorithms, or integrated monitoring systems. We organized the different papers according to their contributions to the main parts of the monitoring and control engineering scheme applied to human health applications, namely papers focusing on measuring/sensing physiological variables, papers highlighting health-monitoring applications, and examples of control and process management applications for human health. In comparison to biomedical engineering, we envision that the field of human health engineering will also cover applications for healthy humans (e.g., sports, sleep, and stress), and thus not only contribute to the development of technology for curing patients or supporting chronically ill people, but also to more general disease prevention and optimization of human well-being