Cancelling Harmonic Power Line Interference in Biopotentials

Biopotential signals, like the electrocardiogram (ECG), electroencephalogram (EEG), electromyogram (EMG), and so on, contain vital information about the health state of human body. The morphology and time/frequency parameters of the biopotentials are of interest when diagnostic information is extracted and analyzed. The powerline interference (PLI), with the fundamental PLI component of 50 Hz/60 Hz and its harmonics, is one of the most disturbing noise sources in biopotential recordings that hampers the analysis of the electrical signals generated by the human body. The aim of this chapter is to review the existing methods to eliminate harmonics PLI from biopotential signals and to analyze the distortion introduced by some of the most basic approaches for PLI cancelation and whether this distortion affects the diagnostic performance in biopotentials investigations

Magnetocardiography in unshielded environment based on optical magnetometry and adaptive noise cancellation

This thesis proposes and demonstrates the concept of a magnetocardiographic system employing an array of optically-pumped quantum magnetometers and an adaptive noise cancellation for heart magnetic field measurement within a magnetically-unshielded environment. Optically-pumped quantum magnetometers are based on the use of the atomic-spin-dependent optical properties of an atomic medium. An Mxconfiguration- based optically-pumped quantum magnetometer employing two sensing cells containing caesium vapour is theoretically described and experimentally developed, and the dependence of its sensitivity and frequency bandwidth upon the light power and the alkali vapour temperature is experimentally demonstrated. Furthermore, the capability of the developed magnetometer of measuring very weak magnetic fields is experimentally demonstrated in a magnetically-unshielded environment. The adaptive noise canceller is based on standard Least-Mean-Squares (LMS) algorithms and on two heuristic optimization techniques, namely, Genetic Algorithms (GA) and Particle Swarm Optimization (PSO). The use of these algorithms is investigated for suppressing the power line generated 50Hz interference and recovering of the weak magnetic heart signals from a much higher electromagnetic environmental noise. Experimental results show that all the algorithms can extract a weak heart signal from a much-stronger magnetic noise, detect the P, QRS, and T heart features and highly suppress the common power line noise component at 50 Hz. Moreover, adaptive noise cancellation based on heuristic algorithms is shown to be more efficient than adaptive noise canceller based on standard or normalised LMS algorithm in heart features detection

Development of an optical cardio-magnetometer

Diese Arbeit beschreibt die Entwicklung eines neuen Typs von Kardiomagnetometer, d.h. eines Geräts mit dem man das Magnetfeld des schlagenden menschlichen Herzens messen kann. Diese ausserordentlich schwachen Magnetfelder tragen medizinisch relevante Informationen und können nichtinvasiv an der Oberfläche des Körpers gemessen werden. Bisher wurden solche Messungen ausschliesslich mit supraleitenden Magnetometern (SQUID) durchgeführt, welche die notwendige magnetometrische Empfindlichkeit (< 1 pT) haben, um Feldänderungen, die fünfzig Millionen Mal kleiner als das Erdmagnetfeld sind, nachzuweisen. SQUIDs sind allerdings auf eine aufwändige Kühlung mit verflüssigten Gasen angewiesen. Die mit der Kühlung verbundenen Kosten sind einer der Gründe dafür, dass sich die Kardiomagnetometrie bis jetzt nicht in der medizinischen Praxis etablieren konnte, trotz der erwiesenen Vorteile der Methode bei der oft schwierigen Diagnose von Herzkrankheiten. Der neue Typ eines Kardiomagnetometers, der in dieser Arbeit beschrieben wird, basiert auf einer völlig anderen Technik, der optisch detektierten Magnetresonanz (ODMR), welche ohne Kühlung auskommt. Die ODMR kombiniert Laserspektroskopie und Magnetresonanz in einem Dampf von paramagnetischen Atomen — in diesem Fall Cäsium — in einer evakuierten Glaszelle. Der Drehimpuls (Spin) der Valenzelektronen der Atome bestimmt die optischen Eigenschaften des Dampfs. Da der Spin Über das assoziierte magnetische Moment auch mit Magnetfeldern wechselwirkt, kann ein äusseres Magnetfeld die optischen Eigenschaften des Mediums beeinflussen. Somit kann aus einer Messung dieser Eigenschaften, wie z.B. dem Absorptionskoeffizienten, das Magnetfeld bestimmt werden. Die Methode ist seit den sechziger Jahren bekannt und in kommerziellen Geräten verfügbar, die von Archäologen und Geologen eingesetzt werden, um Variationen des Erdmagnetfeldes zu messen. Im Gegensatz zu diesen Geräten, in denen als Lichtquelle Spektrallampen verwendet werden, benutzt unser Magnetometer einen frequenzstabilisierten Diodenlaser als Lichtquelle. Unter optimierten Bedingungen erreicht das Magnetometer eine Auflösung von 63 fT=Hz1=2 und eine Bandbreite von 140 Hz mit einem Zellenvolumen von 6 cm3. Um Störfelder im Labor zu unterdrücken, betrieben wir zwei solcher Sensoren in einer gradiometrischen Anordnung. Dabei misst ein Sensor so nah wie möglich am Herz das Herzmagnetfeld zusammen mit den Störungen. Der zweite Sensor etwas weiter entfernt vom Herz misst nur noch die Störungen, da das Herzmagnetfeld schnell mit wachsender Entfernung abfällt. Im Differenzsignal fallen dann die homogenen Störungen heraus, was es uns ermöglicht hat, Herzmagnetfelder in einer schwach magnetisch abgeschirmten Umgebung zu messen. Durch die Messung des Herzmagnetfeldes an verschiedenen Stellen Über der Brust lassen sich Magnetfeldkarten des Herzen erzeugen. Dank EKG-getriggerter Mittelung gelang es, solche Karten für jeden Zeitpunkt des Herzzyklus zu messen. Die Dynamik der Herzmagnetfeldkarten von vier gesunden Probanden haben wir mit SQUID generierten Referenzdaten verglichen. Ein direkter Vergleich der Magnetfeldkarten von zwei Probanden gemessen mit einem kommerziellen SQUID Magnetometer und unserem optischen Magnetometer wurde an der Universität Rom durchgeführt. Die Ergebnisse zeigen, dass die Daten kompatibel sind, was uns zuversichtlich stimmt, dass optische Herzmagnetometrie eines Tages als medizinisches Standardverfahren etabliert werden könnte.This thesis describes the development of a new type of cardiomagnetometer, a device that can measure the magnetic field generated by the beating human heart. Such exceedingly weak magnetic fields carry diagnostically relevant information and can be measured noninvasively at the surface of the body. Cardiomagnetic measurements were previously performed using superconducting magnetometers (SQUID) that have the required sensitivity (< 1 pT) to measure field changes fifty million times smaller than the earth's magnetic field. However, SQUIDs need to be cooled using liquified gases. The cost associated with that cooling is one of the reasons that prevented the widespread use of magnetocardiometry (MCG) in medical practice, despite the fact that MCG measurements have proven to be beneficial in the diagnosis of heart diseases. The new type of cardiomagnetometer described herein is based on a completely different technology, optically detected magnetic resonance (ODMR), that does not need expensive cooling. ODMR combines laser spectroscopy and magnetic resonance in a vapor of paramagnetic atoms — Cs in our case — sealed in a glass cell. The angular momenta (spins) of the atomic valence electrons determine the optical properties of the medium. Magnetic fields can change those optical properties because of the coupling between the spin and the field mediated by the magnetic moment. This allows us to determine the magnetic field from a measurement of the alteration of optical properties such as the absorption coefficient. The method is known since the 1960's and commercial lamp-based devices are used by archaeologists and geologists to measure variations of the earth's magnetic field. In contrast to those devices our magnetometer uses a frequency-stabilized diode-laser as light source. Under optimal conditions the magnetometer has a resolution of 63 fT/Hz1=2 and a detection bandwidth of 140 Hz using a cell of 6 cm3 volume. We used two such magnetometers in a gradiometric configuration to suppress interfering magnetic fields. One sensor was mounted close to the heart measuring both the heart field and the interfering field. The second sensor, some distance away, measured only the interfering field since the heart field drops rapidly with increasing distance. Homogeneous interfering fields cancel in the differential signal from both sensors. This setup allowed us to measure heart magnetic fields in weakly shielded environments. By measuring the field at different positions in a plane above the chest a map of the heart magnetic field can be obtained. Using ECG-triggered averaging we could measure such maps for all times in the cardiac cycle. The dynamics of the magnetic field maps from four healthy volunteers were compared to SQUID-generated reference data. A direct comparison of magnetic field maps recorded with a commercial SQUID magnetometer and with our optical magnetometer was performed at the University of Rome. The results shows that the data are compatible and makes us confident that optical cardiomagnetometry may be used one day as a standard medical technique

Investigating the effects of an on-chip pre-classifier on wireless ECG monitoring

In past years, heart disease has been the leading cause of death in most developed countries. Timely detection of a heart condition is necessary in order to prevent life threatening situations. Even when the problem is not a heart condition, the activity of the heart can supply vital information, which makes its monitoring extremely important. A new approach to patient monitoring was taken recently by introducing wireless sensor networks into medical care. The capability of monitoring multiple patients at once makes such a system ideal for pre-hospital and in-hospital emergency care. The main problems associated with wireless sensor networks are power consumption and scaling. The power consumption is a problem due to the need for increased mobility of such a system, while scaling is of concern because a large number of nodes is desired in order to monitor more patients. This thesis addresses the power and bandwidth problems associated with monitoring patients using wireless networks by introducing another level of signal processing at each node. The goal is to design a digital circuit that would detect any abnormality in the ECG signal and enable the data transmission only if such has occurred. Reducing the amount of data being transmitted reduces the necessary bandwidth for each node and with the introduction of the proposed chip, the power consumption of each node is affected as well

Non-invasive fetal electrocardiogram : analysis and interpretation

High-risk pregnancies are becoming more and more prevalent because of the progressively higher age at which women get pregnant. Nowadays about twenty percent of all pregnancies are complicated to some degree, for instance because of preterm delivery, fetal oxygen deficiency, fetal growth restriction, or hypertension. Early detection of these complications is critical to permit timely medical intervention, but is hampered by strong limitations of existing monitoring technology. This technology is either only applicable in hospital settings, is obtrusive, or is incapable of providing, in a robust way, reliable information for diagnosis of the well-being of the fetus. The most prominent method for monitoring of the fetal health condition is monitoring of heart rate variability in response to activity of the uterus (cardiotocography; CTG). Generally, in obstetrical practice, the heart rate is determined in either of two ways: unobtrusively with a (Doppler) ultrasound probe on the maternal abdomen, or obtrusively with an invasive electrode fixed onto the fetal scalp. The first method is relatively inaccurate but is non-invasive and applicable in all stages of pregnancy. The latter method is far more accurate but can only be applied following rupture of the membranes and sufficient dilatation, restricting its applicability to only the very last phase of pregnancy. Besides these accuracy and applicability issues, the use of CTG in obstetrical practice also has another limitation: despite its high sensitivity, the specificity of CTG is relatively low. This means that in most cases of fetal distress the CTG reveals specific patterns of heart rate variability, but that these specific patterns can also be encountered for healthy fetuses, complicating accurate diagnosis of the fetal condition. Hence, a prerequisite for preventing unnecessary interventions that are based on CTG alone, is the inclusion of additional information in diagnostics. Monitoring of the fetal electrocardiogram (ECG), as a supplement of CTG, has been demonstrated to have added value for monitoring of the fetal health condition. Unfortunately the application of the fetal ECG in obstetrical diagnostics is limited because at present the fetal ECG can only be measured reliably by means of an invasive scalp electrode. To overcome this limited applicability, many attempts have been made to record the fetal ECG non-invasively from the maternal abdomen, but these attempts have not yet led to approaches that permit widespread clinical application. One key difficulty is that the signal to noise ratio (SNR) of the transabdominal ECG recordings is relatively low. Perhaps even more importantly, the abdominal ECG recordings yield ECG signals for which the morphology depends strongly on the orientation of the fetus within the maternal uterus. Accordingly, for any fetal orientation, the ECG morphology is different. This renders correct clinical interpretation of the recorded ECG signals complicated, if not impossible. This thesis aims to address these difficulties and to provide new contributions on the clinical interpretation of the fetal ECG. At first the SNR of the recorded signals is enhanced through a series of signal processing steps that exploit specific and a priori known properties of the fetal ECG. More particularly, the dominant interference (i.e. the maternal ECG) is suppressed by exploiting the absence of temporal correlation between the maternal and fetal ECG. In this suppression, the maternal ECG complex is dynamically segmented into individual ECG waves and each of these waves is estimated through averaging corresponding waves from preceding ECG complexes. The maternal ECG template generated by combining the estimated waves is subsequently subtracted from the original signal to yield a non-invasive recording in which the maternal ECG has been suppressed. This suppression method is demonstrated to be more accurate than existing methods. Other interferences and noise are (partly) suppressed by exploiting the quasiperiodicity of the fetal ECG through averaging consecutive ECG complexes or by exploiting the spatial correlation of the ECG. The averaging of several consecutive ECG complexes, synchronized on their QRS complex, enhances the SNR of the ECG but also can suppress morphological variations in the ECG that are clinically relevant. The number of ECG complexes included in the average hence constitutes a trade-off between SNR enhancement on the one hand and loss of morphological variability on the other hand. To relax this trade-off, in this thesis a method is presented that can adaptively estimate the number of ECG complexes included in the average. In cases of morphological variations, this number is decreased ensuring that the variations are not suppressed. In cases of no morphological variability, this number is increased to ensure adequate SNR enhancement. The further suppression of noise by exploiting the spatial correlation of the ECG is based on the fact that all ECG signals recorded at several locations on the maternal abdomen originate from the same electrical source, namely the fetal heart. The electrical activity of the fetal heart at any point in time can be modeled as a single electrical field vector with stationary origin. This vector varies in both amplitude and orientation in three-dimensional space during the cardiac cycle and the time-path described by this vector is referred to as the fetal vectorcardiogram (VCG). In this model, the abdominal ECG constitutes the projection of the VCG onto the vector that describes the position of the abdominal electrode with respect to a reference electrode. This means that when the VCG is known, any desired ECG signal can be calculated. Equivalently, this also means that when enough ECG signals (i.e. at least three independent signals) are known, the VCG can be calculated. By using more than three ECG signals for the calculation of the VCG, redundancy in the ECG signals can be exploited for added noise suppression. Unfortunately, when calculating the fetal VCG from the ECG signals recorded from the maternal abdomen, the distance between the fetal heart and the electrodes is not the same for each electrode. Because the amplitude of the ECG signals decreases with propagation to the abdominal surface, these different distances yield a specific, unknown attenuation for each ECG signal. Existing methods for estimating the VCG operate with a fixed linear combination of the ECG signals and, hence, cannot account for variations in signal attenuation. To overcome this problem and be able to account for fetal movement, in this thesis a method is presented that estimates both the VCG and, to some extent, also the signal attenuation. This is done by determining for which VCG and signal attenuation the joint probability over both these variables is maximal given the observed ECG signals. The underlying joint probability distribution is determined by assuming the ECG signals to originate from scaled VCG projections and additive noise. With this method, a VCG, tailored to each specific patient, is determined. With respect to the fixed linear combinations, the presented method performs significantly better in the accurate estimation of the VCG. Besides describing the electrical activity of the fetal heart in three dimensions, the fetal VCG also provides a framework to account for the fetal orientation in the uterus. This framework enables the detection of the fetal orientation over time and allows for rotating the fetal VCG towards a prescribed orientation. From the normalized fetal VCG obtained in this manner, standardized ECG signals can be calculated, facilitating correct clinical interpretation of the non-invasive fetal ECG signals. The potential of the presented approach (i.e. the combination of all methods described above) is illustrated for three different clinical cases. In the first case, the fetal ECG is analyzed to demonstrate that the electrical behavior of the fetal heart differs significantly from the adult heart. In fact, this difference is so substantial that diagnostics based on the fetal ECG should be based on different guidelines than those for adult ECG diagnostics. In the second case, the fetal ECG is used to visualize the origin of fetal supraventricular extrasystoles and the results suggest that the fetal ECG might in future serve as diagnostic tool for relating fetal arrhythmia to congenital heart diseases. In the last case, the non-invasive fetal ECG is compared to the invasively recorded fetal ECG to gauge the SNR of the transabdominal recordings and to demonstrate the suitability of the non-invasive fetal ECG in clinical applications that, as yet, are only possible for the invasive fetal ECG

Extracting heart rate dependent electrocardiogram templates for a body emulator environment

Abstract. Medical device and analysis method developments often include tests on humans, which are expensive, time consuming, and sometimes even dangerous. In order to perform human tests, special safety conditions and ethical and legal requirements must be taken into account. Emulators that can emulate the physiological functions of the human body could solve these difficulties. In this study, the heart rate depended electrocardiogram templates for this kind of an emulator were extracted. The real-life electrocardiogram preprocessing included a high-pass filter and a Savitzky-Golay filter. A beat detection algorithm was developed to detect QRS complexes in the signals and classify beat artefacts based on the RR interval sequences and two adaptive thresholds. Heart rate levels were detected using the K-means clustering technique. Vectorcardiogram signals were converted from the electrocardiogram signals using the inverse Dower’s transformation matrix, and vectorcardiogram templates were extracted to the respective heart rate levels. Finally, a graphical user interface was created for the mentioned methods. The developed beat detection algorithm was tested with the MIT-BIH Arrhythmia Database and the comparison was made with the state-of-the-art algorithms. The beat detection algorithm resulted the sensitivity of 99.77 \%, precision of 99.65 \%, and detection error rate of 0.58 \%. Based on the results, the proposed methods and extracted vectorcardiogram templates were successful.Sykkeestä riippuvien elektrokardiogrammimallien poiminta kehoemulaattoriympäristöön. Tiivistelmä. Lääketieteellisten laitteiden ja analyysimenetelmien kehitystyö sisältää usein ihmisille suoritettavia testejä, jotka ovat kalliita, aikaa vieviä ja joskus jopa vaarallisia. Ihmiskokeiden toteuttamiseksi on otettava huomioon erityisiä turvallisuusehtoja, sekä eettisiä ja laillisia vaatimuksia. Emulaattorit, jotka pystyvät jäljittelemään ihmiskehon fysiologisia toimintoja, voivat olla ratkaisu näihin ongelmiin. Tässä tutkimuksessa sykkeestä riippuvia elektrokardiogrammimalleja poimittiin tämän tyyppiselle emulaattorille. Tosielämän elektrokardiogrammisignaalien esikäsittely sisälsi ylipäästösuodattimen ja Savitzky-Golay suodattimen. Sydämen lyöntien tunnistussalgoritmi kehitettiin tunnistamaan QRS-komplekseja signaaleista ja luokittelemaan lyöntiartefakteja RR-intervallisekvenssien ja kahden adaptiivisen kynnysarvon perusteella. Syketasot tunnistettiin käyttämällä K-means klusterointitekniikkaa. Vektorikardiogrammisignaalit muunnettiin elektrokardiogrammisignaaleista käyttämällä käänteistä Dowerin muunnosmatriisia ja vektorikardiogrammimallit poimittiin vastaaville syketasoille. Lopuksi luotiin graafnen käyttöliittymä mainituille menetelmille. Kehitetty lyöntien tunnistusalgoritmi testattiin MIT-BIH Arrhythmia Database-tietokannalla ja vertailu suoritettiin vastaavien algoritmien kanssa. Algoritmi suoriutui 99,77 % herkkyydellä, 99,65 % spesifsyydellä ja 0,58 % virheprosentilla. Tulosten perusteella ehdotetut menetelmät ja poimitut vektorikardiogrammimallit olivat onnistuneita

Body sensor network for in-home personal healthcare

A body sensor network solution for personal healthcare under an indoor environment is developed. The system is capable of logging the physiological signals of human beings, tracking the orientations of human body, and monitoring the environmental attributes, which covers all necessary information for the personal healthcare in an indoor environment. The major three chapters of this dissertation contain three subsystems in this work, each corresponding to one subsystem: BioLogger, PAMS and CosNet. Each chapter covers the background and motivation of the subsystem, the related theory, the hardware/software design, and the evaluation of the prototype’s performance

Aerospace Medicine and Biology: A continuing bibliography with indexes, supplement 145

This bibliography lists 301 reports, articles, and other documents introduced into the NASA scientific and technical information system in August 1975

Computer modeling and signal analysis of cardiovascular physiology

This dissertation aims to study cardiovascular physiology from the cellular level to the whole heart level to the body level using numerical approaches. A mathematical model was developed to describe electromechanical interaction in the heart. The model integrates cardio-electrophysiology and cardiac mechanics through excitation-induced contraction and deformation-induced currents. A finite element based parallel simulation scheme was developed to investigate coupled electrical and mechanical functions. The developed model and numerical scheme were utilized to study cardiovascular dynamics at cellular, tissue and organ levels. The influence of ion channel blockade on cardiac alternans was investigated. It was found that the channel blocker may significantly change the critical pacing period corresponding to the onset of alternans as well as the alternans’ amplitude. The influence of electro-mechanical coupling on cardiac alternans was also investigated. The study supported the earlier assumptions that discordant alternans is induced by the interaction of conduction velocity and action potential duration restitution at high pacing rates. However, mechanical contraction may influence the spatial pattern and onset of discordant alternans. Computer algorithms were developed for analysis of human physiology. The 12-lead electrocardiography (ECG) is the gold standard for diagnosis of various cardiac abnormalities. However, disturbances and mistakes may modify physiological waves in ECG and lead to wrong diagnoses. This dissertation developed advanced signal analysis techniques and computer software to detect and suppress artifacts and errors in ECG. These algorithms can help to improve the quality of health care when integrated into medical devices or services. Moreover, computer algorithms were developed to predict patient mortality in intensive care units using various physiological measures. Models and analysis techniques developed here may help to improve the quality of health care

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