O objetivo deste trabalho é filtrar sinais corrompidos por ruído Gaussiano ou impulsivo, preservando a amplitude e a morfologia do sinal original. Normalmente, um filtro linear é utilizado nesta tarefa, porém este filtro altera significativamente as amplitudes e as bordas dos sinais, bem como insere atrasos no sinal. Mostra-se neste trabalho que a difusão anisotrópica em conjunto com filtro mediana é muito mais eficaz do que os filtros lineares para esta aplicação. A difusão anisotrópica é uma filtragem iterativa, onde o sinal é filtrado repetidamente. A difusão anisotrópica é controlada por uma função denominada parada-na-aresta, por um parâmetro de escala e pelo número de iterações. Neste trabalho, testamos três bem conhecidas funções parada-na-aresta, concluindo que a função de parada na aresta de Malik e Perona consegue o maior fator de redução de ruído. Infelizmente, esta função é extremamente sensível ao número de iterações, onde o fator de redução de ruído deteriora-se rapidamente antes e depois do ponto ótimo. Como não se conhece o sinal sem ruído, não é possível determinar precisamente qual é o melhor momento de encerrar as iterações do filtro anisotrópico. Desenvolve-se neste trabalho um novo método de parada de difusão baseado na análise da resposta de freqüência do sinal filtrado. Também mostramos como determinar automaticamente um valor de escala adequado. Aplicamos a técnica proposta em eletrocardiograma (ECG). complexo QRS e as Contrações Ventriculares Prematuras (Premature Ventricular Contractions - PVCs) são informações importantes contidas no sinal de ECG. Quando esses sinais são adquiridos no mundo real, eles são freqüentemente corrompidos por eletromiogramas (EMG), artefatos ruidosos provenientes da atividade elétrica associada às contrações musculares. EMG é considerado o ruído de ECG mais difícil de ser eliminado. Ao filtrar o sinal de ECG para remover EMG, não se pode alterar a informação do complexo QRS e anomalia PVC, para não comprometer o diagnóstico clínico. O sinal EMG é modelado como sendo ruído Gaussiano ou, de uma forma mais realística, como ruído com distribuição alfa-estável com características impulsivas. Aplicamos a técnica proposta para filtrar sinais de eletrocardiograma reais do banco de dados de Massachusetts Institute of Technology - Beth Israel Hospital (MIT-BIH). Também é analisada nesta tese a filtragem de sinais provenientes de sensor piezoelétrico. Estes sinais são usados em sistemas reais de corte de aço duro. Em geral uma ferramenta de corte tem sensores piezoelétricos, usados para medição do esforço do corte. Quando a ferramenta de corte se encosta à peça a ser cortada, o sinal do sensor produz uma informação que decai erroneamente ao longo do tempo. Aplicamos a difusão anisotrópica em conjunto com o filtro mediana para determinar o decaimento do sinal do sensor piezoelétrico ao longo do tempo, e assim compensar esta distorção e melhorar o corte de aço duro. / This thesis aims to filter signals corrupted by Gaussian or impulsive noise, preserving the amplitude and the morphology of the original signal. Typically, a linear filter is used for this task, but this filter significantly alters the amplitudes and the edges of the signals and inserts delays in the signal. This work shows that the anisotropic diffusion in conjunction with median filter is much more effective than linear filters for this application. The anisotropic diffusion is an iterative filter, where the signal is filtered repeatedly. An edge-stopping function, a scale parameter and the number of iterations control the anisotropic diffusion. In this study, we tested three well-known edge-stopping functions, concluding that the Perona and Maliks function yields the largest noise reduction factor. Unfortunately, this function is extremely sensitive to the number of iterations, where the noise reduction factor deteriorates quickly before and after the optimal point. As we do not have access to the original noiseless signal, it is not possible to determine precisely the best moment to stop the iterations of the anisotropic filtering. We develop in this paper a new method to determine the best stopping time based on the analysis of the frequency response of the filtered signal. We also show how to determine automatically an adequate scale parameter. We apply the proposed technique to filter electrocardiogram (ECG). The QRS complex and Premature Ventricular Contractions (PVCs) are important information in the ECG signal. When these signals are acquired in the real world, they are often corrupted with noise artifacts from the electrical activity associated with muscle contractions called Electromyography (EMG). EMC is considered the most difficult noise to be eliminated from ECG. When the ECG signal is filtered to remove EMG, the information of the QRS complex and the PVC abnormality must not be altered, to not compromise the clinical diagnosis. We model the EMG signal as Gaussian noise or, more realistically, as alpha stable distribution noise with impulsive characteristics. We apply this technique to filter the real ECG signals from the Massachusetts Institute of Technology - Beth Israel Hospital database (MIT-BIH). This thesis also analyzes the filtering of signals from piezoelectric sensor. These signals are used in real systems for cutting hard steel. In general, a cutting tool has piezoelectric sensors, used to measure the cutting force. When the cutting tool touches the part to be cut, the signal from the sensor produces information that falsely decays over the time. We apply the anisotropic diffusion in conjunction with the median filter to determine the decay of the signal, and therefore offset this distortion and improve the hard steel cutting.

The impact of colour and lighting conditions on the emotions and performance of people is gaining greater importance in our urban societies. While large resources are allocated for well designed spaces with the right choices of colour and lighting conditions, there is little scientific evidence that supports these choices. Although the literature on light and colour is extensive, it does not present a uniform set of findings for a consistent perspective on the influence of colour and light. Most of the research reported in this field uses subjective measures to study the emotional effects of light and colour on people. It has been reported in literature that emotion manifests itself in three separate sections; (i) physiological (i.e. objective measures), (ii) psychological (subjective measures), (iii) behavioral, and it is necessary that studies not be limited to the assessment of a single response but include sample measures from each of the three manifestations. This research is built on the current body of knowledge that there is a need for a study on the emotional effects of light and colour on people using physiological and psychological measures, to ensure the objectivity and reproductivity of the experiments. It is well documented in literature that there is close correlation between emotions, heart rate (HR), and skin conductance (SC). Hence HR and SC are expected to be good physiological measures of environmental conditions on people. Thus this thesis reports changes in the HR, SC and self-assessment reports of arousal and valence (SAM) for people when exposed to different colour and intensity lights. The aim is to help provide an objective rationale for the choice for light intensity and colour by architects, interior designers and other professionals. The experiments were conducted on 15 participants who were exposed to 8 different colour and intensity light conditions. The participants' HR and SC were recorded under each colour and intensity light, and they were asked to complete SAM. The research demonstrates that there is a change in HR, SC, arousal and valence of participants due to change in the colour and intensity of lights. However, the direction of change was subject dependent, where the same colour and intensity light can have different effects on people. The research suggests that architects and designers of any space must take into account the individual differences of the predicted users when designing the lights and colours. It is also seen from the results that some colour and intensity lights have greater impact on the emotions of participants than others. Although it is not possible to correlate the colour and lighting conditions to a specific effect on all participants, general effects for some colour lights were drawn from the results. It is well documented in literature that HR and SC are a good measure of emotion. However the results of this study show very high inter subject variation in HR and SC. This is due to people having different HR and SC in normal conditions. This research demonstrates that the use of HR and SC to measure the effect of a stimulus on a group of people is unreliable because it is hard to compare the results.

<p>Death from heart diseases is the most common type of mortality in western countries and the survival rate of cardiac arrest is dismally low. In the treatment of cardiac arrest, two therapeutic methods are most important: cardiopulmonary resuscitation (CPR; chest compressions and ventilations) and defibrillation (electrical shocks to restart a fibrillating heart).</p><p>An automated external defibrillator is commonly used for such shocks, and records and performs signal analysis on the electrocardiogram(ECG) in order to advice when to shock the patient. However, the mechanical activity during CPR introduces artifact components in the ECG. To perform reliable ECG signal analysis, CPR is therefore discontinued for a substantial time before the potential delivery of a shock. This wastes valuable therapy time, and if this hands-off time could be reduced or eliminated by removing these artifacts, it should improve the chance of return of spontaneous circulation.</p><p>We propose a method for removing CPR artifacts using a novel multichannel adaptive filter, the computationally efficient and numerically robust MultiChannel Recursive Adaptive Matching Pursuit(MC-RAMP) filter. Using the most realistic data set to date, human out-of-hospital cardiac arrest data of both shockable and non-shockable rhythms, we test MC-RAMP and evaluate the feasibility of ECG analysis during CPR. In our experiments we use a shock advice algorithm and individual ECG signal features to reach the conclusion that after CPR artifact filtering, ECG rhythm analysis during ongoing CPR is feasible. </p><p>Finally, we analyze and quantify the time intervals without blood flow (no flow time(NFT)) during external automatic defibrillation in cardiac arrest patients and show that these patients were not perfused around half of the time. We propose methods using CPR artifact filtering to reduce the NFT, and show their significant and promising potential. By introducing the proposed methods into defibrillators, the NFT would be significantly reduced, hopefully increasing the survival.</p>

<p>The aim was to contribute to the optimal use of the resting ECG by exploring, in middle-aged and elderly men, the development and regression of ECG abnormalities; the prognostic value of the ECG for cardiovascular disease compared to conventional risk factors; and the impact of age at baseline and follow-up time for prediction of cardiovascular disease.</p><p>It was based on the Uppsala Study of Adult Men cohort that was started in 1970. Participants were examined at ages 50, 70, 77, and 82, with annual updates on mortality and in-hospital morbidity using national registries. </p><p>The studies indicated that the prevalence of silent MI and frequency of regression of major Q/QS patterns may be higher than previously believed. Considering that persistent T wave abnormalities and ST segment depression carried twice as high a risk for future cardiovascular disease (CVD) mortality as new or reverted abnormalities, the results suggested that serial electrocardiograms (ECG) would contribute to proper risk assessment. Also, the inclusion of ischemic ECG findings significantly increased the predictive power of the Framingham score at age 70 for CVD. </p><p>While hypertension and dyslipidemia were consistent long-term risk factors for myocardial infarction at ages 50 and 70, the length of follow-up period and age at baseline affected the predictive power of ECG abnormalities, fasting insulin, BMI, and smoking. </p><p>For stroke, midlife values for blood pressure and ECG abnormalities retained prognostic value over long follow-up periods, even though they improved when re-measured in elderly participants. ApoB/apoA1 ratio, driven by apoA1, was associated with stroke in elderly but not middle-aged men. Hyperinsulinemia and diabetes mellitus were more specifically associated with ischemic stroke than with any-cause stroke. </p><p>In summary, the resting ECG carried prognostic information beyond conventional risk factors. Even though the low prevalence of ECG abnormalities at the age of 50 calls into question the role of the ECG as a screening tool, the additional risk information it carries with it justifies its regular and repeated registration above the age of 50. </p>

Death from heart diseases is the most common type of mortality in western countries and the survival rate of cardiac arrest is dismally low. In the treatment of cardiac arrest, two therapeutic methods are most important: cardiopulmonary resuscitation (CPR; chest compressions and ventilations) and defibrillation (electrical shocks to restart a fibrillating heart). An automated external defibrillator is commonly used for such shocks, and records and performs signal analysis on the electrocardiogram(ECG) in order to advice when to shock the patient. However, the mechanical activity during CPR introduces artifact components in the ECG. To perform reliable ECG signal analysis, CPR is therefore discontinued for a substantial time before the potential delivery of a shock. This wastes valuable therapy time, and if this hands-off time could be reduced or eliminated by removing these artifacts, it should improve the chance of return of spontaneous circulation. We propose a method for removing CPR artifacts using a novel multichannel adaptive filter, the computationally efficient and numerically robust MultiChannel Recursive Adaptive Matching Pursuit(MC-RAMP) filter. Using the most realistic data set to date, human out-of-hospital cardiac arrest data of both shockable and non-shockable rhythms, we test MC-RAMP and evaluate the feasibility of ECG analysis during CPR. In our experiments we use a shock advice algorithm and individual ECG signal features to reach the conclusion that after CPR artifact filtering, ECG rhythm analysis during ongoing CPR is feasible. Finally, we analyze and quantify the time intervals without blood flow (no flow time(NFT)) during external automatic defibrillation in cardiac arrest patients and show that these patients were not perfused around half of the time. We propose methods using CPR artifact filtering to reduce the NFT, and show their significant and promising potential. By introducing the proposed methods into defibrillators, the NFT would be significantly reduced, hopefully increasing the survival.

The aim was to contribute to the optimal use of the resting ECG by exploring, in middle-aged and elderly men, the development and regression of ECG abnormalities; the prognostic value of the ECG for cardiovascular disease compared to conventional risk factors; and the impact of age at baseline and follow-up time for prediction of cardiovascular disease. It was based on the Uppsala Study of Adult Men cohort that was started in 1970. Participants were examined at ages 50, 70, 77, and 82, with annual updates on mortality and in-hospital morbidity using national registries. The studies indicated that the prevalence of silent MI and frequency of regression of major Q/QS patterns may be higher than previously believed. Considering that persistent T wave abnormalities and ST segment depression carried twice as high a risk for future cardiovascular disease (CVD) mortality as new or reverted abnormalities, the results suggested that serial electrocardiograms (ECG) would contribute to proper risk assessment. Also, the inclusion of ischemic ECG findings significantly increased the predictive power of the Framingham score at age 70 for CVD. While hypertension and dyslipidemia were consistent long-term risk factors for myocardial infarction at ages 50 and 70, the length of follow-up period and age at baseline affected the predictive power of ECG abnormalities, fasting insulin, BMI, and smoking. For stroke, midlife values for blood pressure and ECG abnormalities retained prognostic value over long follow-up periods, even though they improved when re-measured in elderly participants. ApoB/apoA1 ratio, driven by apoA1, was associated with stroke in elderly but not middle-aged men. Hyperinsulinemia and diabetes mellitus were more specifically associated with ischemic stroke than with any-cause stroke. In summary, the resting ECG carried prognostic information beyond conventional risk factors. Even though the low prevalence of ECG abnormalities at the age of 50 calls into question the role of the ECG as a screening tool, the additional risk information it carries with it justifies its regular and repeated registration above the age of 50.

The instrumentation amplifier (IA) is one of the crucial blocks in an electrocardiogram recording system. It is the first block in the analog front-end chain that processes the ECG signal from the human body and thus it defines some of the most important specifications of the ECG system like the noise and common mode rejection ratio (CMRR). The extremely low ECG signal bandwidth also makes it difficult to achieve a fully integrated system. In this thesis, a fully integrated IA topology is presented that achieves low noise levels and low power dissipation. The chopper stabilized technique is implemented together with an AC coupled amplifier to reduce the effect of flicker noise while eliminating the effect of the differential electrode offset (DEO). An ultra low power operational transconductance amplifier (OTA) is the only active power consuming block in the IA and so an overall low power consumption is achieved. A new implementation of a large resistor using the T-network is presented which makes it easy to achieve a fully integrated solution. The proposed IA operates on a 2V supply and consumes a total current of 1.4µA while achieving an integrated noise of 1.2µVrms within the bandwidth. The proposed IA will relax the power and noise requirements of the analog-to-digital converter (ADC) that immediately follows it in the signal chain and thus reduce the cost and increase the lifetime of the recording device. The proposed IA has been implemented in the ONSEMI 0.5µm CMOS technology.

Medicinoje duomenys dažniausiai yra analizuojami statistiniais metodais. Tačiau šiame darbe elektrokardiogramos (EKG) parametrus tirsime naudodamiesi algebriniais metodais, nes į kiekvieno žmogaus organizmą žvelgiant kaip į sudėtingą ir unikalią kompleksinę sistemą, statistinio tyrimo nepakanka. Egzistuoja specialus algoritmas, leidžiantis funkciją , aprašytą Teiloro eilute arba jos reikšmėmis, išreikšti baigtine eksponenčių suma. Šio darbo tikslas – baigtine eksponenčių suma aproksimuoti EKG parametrų funkcijos dalis, kurios turi baigtinį kompleksiškumą, bei tirti parametrų kompleksiškumo pokyčius ilgame EKG įraše. / Medical data are often analysed using statistical methods. However the aim of this work is to analyse the complexity of some electrocardiogram (ECG) parameters using algebraic mathematical methods, because if we consider a human organism a complex and individual system, the former methods are not adequate. Mainly, we analyse two parameters of ECG: the complexity of R wave amplitude and duration between R waves. The method of Hankel matrices, in which functions of the finite h-rank are written as linear combinations of exponential functions, is used.

Dinaminiai žmogaus organizmo kaip kompleksinės sistemos procesai atsispindi, registruojant fiziologinių procesų signalus, kuriems būdingos įvairaus laipsnio svyravimai, pavyzdžiui – elektrokardiogramos (EKG) signalai. Paprastai šių signalų analizei pasirenkami statistinės analizės metodai, kurie labiau taikytini globaliems organizmo procesams ir kuriems reikalingas didelis kiekis informacijos. Atitinkamai matematinės analizės metodai taikomi lokaliems organizmo procesams nagrinėti ir tuo pačiu nereikalingas toks didelis kiekis informacijos (mūsų atveju pakanka trijų atskaitymų). Fiziologinių signalų matricinė analizė padeda atskleisti sudėtingus žmogaus organizmo kaip KAS bei nuovargio fenomenus, parodančius netiesinių organizmo funkcinės būklės ir adaptacijos procesų fraktalinio ir chaotinio pobūdžio ypatumus. Atsižvelgiant į tai, šio tyrimo tikslas buvo nustatyti širdies ir kraujagyslių sistemos funkcinių rodiklių sąsajų kaitos ypatumus, vertinant sportuojančių asmenų organizmo būsenas. / The dynamic of the human body as a complex system of processes is reflected in the registration process of physiological signals which are characterized by varying degrees of oscillations, for example - an electrocardiogram (ECG) signals. Typically, these signals are selected for the statistical analysis methods that are more applicable to global processes of the body and requiring large amounts of information. Accordingly, the mathematical analysis methods are used to examine the local processes of the body and thus do not require such a large amount of information (in our case, enough of the three deductions). Physiological signal analysis matrix helps reveal the complex human organism as complex adaptive system and fatigue phenomena, which reflect the functional state of homeostasis and adaptation processes in fractal and chaotic nature of features. In this context, the aim of the study is to reveal the dynamical peculiarities of interactions of cardiovascular system indices in evaluation of sportsmen body’s functional state.

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