Empirical Mode Decomposition Combined with Local Linear Quantile Regression for Automatic Boundary Correction

Empirical mode decomposition (EMD) is particularly useful in analyzing nonstationary and nonlinear time series. However, only partial data within boundaries are available because of the bounded support of the underlying time series. Consequently, the application of EMD to finite time series data results in large biases at the edges by increasing the bias and creating artificial wiggles. This study introduces a newtwo-stagemethod to automatically decrease the boundary effects present inEMD.At the first stage, local polynomial quantile regression (LLQ) is applied to provide an efficient description of the corrupted and noisy data.The remaining series is assumed to be hidden in the residuals. Hence, EMD is applied to the residuals at the second stage. The final estimate is the summation of the fitting estimates from LLQ and EMD. Simulation was conducted to assess the practical performance of the proposed method. Results show that the proposed method is superior to classical EMD

Empirical Mode Decomposition of Pressure Signal for Health Condition Monitoring in Waterjet Cutting

Waterjet/abrasive waterjet cutting is a flexible technology that can be exploited for different operations on a wide range of materials. Due to challenging pressure conditions, cyclic pressure loadings, and aggressiveness of abrasives, most of the components of the ultra-high pressure (UHP) pump and the cutting head are subject to wear and faults that are difficult to predict. Therefore, the continuous monitoring of machine health conditions is of great industrial interest, as it allows implementing condition-based maintenance strategies, and providing an automatic reaction to critical faults, as far as unattended processes are concerned. Most of the literature in this frame is focused on indirect workpiece quality monitoring and on fault detection for critical cutting head components (e.g., orifices and mixing tubes). A very limited attention has been devoted to the condition monitoring of critical UHP pump components, including cylinders and valves. The paper investigates the suitability of the water pressure signal as a source of information to detect different kinds of fault that may affect both the cutting head and the UHP pump components. We propose a condition monitoring approach that couples empirical mode decomposition (EMD) with principal component analysis to detect any pattern deviation with respect to a reference model, based on training data. The EMD technique is used to separate high-frequency transient patterns from low-frequency pressure ripples, and the computation of combined mode functions is applied to cope with the mode mixing effect. Real industrial data, acquired under normal working conditions and in the presence of actual faults, are used to demonstrate the performances provided by the proposed approach

An Adaptive Hilbert-Huang Transform System

This thesis presents a system which can be used to generate Intrinsic Mode Functions and the associated Hilbert spectrum resulting from techniques based on the Empirical Mode Decomposition as pioneered by N. E. Huang at the end of the 20th century. Later dubbed the Hilbert-Huang Transform by NASA, the process of decomposing data manually through repetitive detrending and subtraction followed by applying the Hilbert transform to the results was presented as a viable alternative to the wavelet transform which was gaining traction at the time but had shown significant limitations. In the last 20 years, the Hilbert-Huang Transform has received a lot of attention, but that attention has been miniscule relative to the amount of attention received by wavelet transformation. This is, in part, due to the limitations of the Empirical Mode Decomposition and also in part due to the difficulty in developing a theoretical basis for the manner in which the Empirical Mode Decomposition works. While the question of theoretical foundations is an important and tricky one, this thesis presents a system that breaks many of the previously known limits on band-width resolution, mode mixing, and viable decomposable frequency range relative to sampling frequency of the Empirical Mode Decomposition. Many recent innovations do not simply improve on N. E. Huang’s algorithm, but rather provide new approaches with different decompositional properties. By choosing the best technique at each step, a superior total decomposition can be arrived at. Using the Hilbert-Huang Transform itself during the decomposition as a guide as suggested by R. Deering in 2005, the final HHT can show distinct improvements. The AHHT System utilizes many of the properties of various Empirical Mode Decomposition techniques from literature, includes some novel innovations on those techniques, and then manages the total decomposition in an adaptive manner. The Adaptive Hilbert-Huang Transform System (AHHT) is demonstrated successfully on many different artificial signals, many with varying levels of noise down to -5dB SNR, as well as on an electrocardiogram and for comparison with a surface electromyographic study which found biopotential frequency-shifting associated with the fatigue of fast-twitch muscle fibers

Modeling the Effects of the Local Environment on a Received GNSS Signal

There is an ongoing need in the GNSS community for the development of high-fidelity simulators which generate data that replicates what can truly be expected from a challenging environment such as an urban canyon or an indoor environment. The algorithm developed for use in the research in this dissertation, the Signal Decomposition and Parameterization Algorithm (SDPA), is presented in order to respond to this need. This algorithm is designed to decompose a signal received using a GNSS recording and playback system and output parameters that can be used to reconstruct the effects on the signal of the environment local to the receiver at the time of recording. The SDPA itself is presented and compared with what is believed to be the state-of-the-art in GNSS multipath parameterization, a Space Alternating Generalized Expectation Maximization (SAGE) algorithm. The development and characterization of a stopping criteria that can be used to halt the SDPA when parameterization of salient components within a recorded signal has been completed

Reflex syncope : an integrative physiological approach

Síncope, a forma mais comum de perda temporária de consciência é responsável por até 5% das idas aos serviços de emergência e até 3% dos internamentos hospitalares. É um problema médico frequente, com múltiplos gatilhos, incapacitante, potencialmente perigoso e desafiante em termos diagnósticos e terapêuticos. Assim, é necessária uma anamnese detalhada para primeiro estabelecer a natureza da perda de consciência, mas, após o diagnóstico, as medidas terapêuticas existentes são pouco eficazes. Embora a fisiopatologia da síncope vasovagal ainda não tenha sido completamente esclarecida, alguns mecanismos subjacentes foram já desvendados. Em última análise, a síncope depende de uma falha transitória na perfusão cerebral pelo que qualquer factor que afecte a circulação sanguínea cerebral pode determinar a ocorrência de síncope. Assim, o objectivo do presente estudo é caracterizar o impacto hemodinâmico e autonómico nos mecanismos subjacentes à síncope reflexa, para melhorar o diagnóstico, o prognóstico e a qualidade de vida dos doentes e dos seus cuidadores. Para isso, desenhámos e implementámos novas ferramentas matemáticas e computacionais que permitem uma avaliação autonómica e hemodinâmica integrada, de forma a aprofundar a compreensão do seu envolvimento nos mecanismos de síncope reflexa. Além disso, refinando a precisão do diagnóstico, a sensibilidade e a especificidade do teste de mesa de inclinação (“tilt test”), estabelecemos uma ferramenta preditiva do episódio iminente de síncope. Isso permitiu-nos estabelecer alternativas de tratamento eficazes e personalizadas para os doentes refractários às opções convencionais, sob a forma de um programa de treino de ortostatismo (“tilt training”), contribuindo para o aumento da sua qualidade de vida e para a redução dos custos directos e indirectos da sua assistência médica. Assim, num estudo verdadeiramente multidisciplinar envolvendo doentes com síncope reflexa refractária à terapêutica, conseguimos demonstrar uma assincronia funcional das respostas reflexas autonómicas e hemodinâmicas, expressas por um desajuste temporal entre o débito cardíaco e as adaptações de resistência total periférica, uma resposta baroreflexa atrasada e um desequilíbrio incremental do tónus autonómico que, em conjunto, poderão resultar de uma disfunção do sistema nervoso autónomo que se traduz por uma reserva simpática diminuída. Igualmente, desenhámos, testámos e implementámos uma plataforma computacional e respectivo software associado - a plataforma FisioSinal –incluindo novas formas, mais dinâmicas, de avaliação integrada autonómica e hemodinâmica, que levaram ao desenvolvimento de algoritmos preditivos para a estratificação de doentes com síncope. Além disso, na aplicação dessas ferramentas, comprovámos a eficácia de um tratamento não invasivo, não disruptivo e integrado, focado na neuromodulação das variáveis autonómicas e cardiovasculares envolvidas nos mecanismos de síncope. Esta terapêutica complementar levou a um aumento substancial da qualidade de vida dos doentes e à abolição dos eventos sincopais na grande maioria dos doentes envolvidos. Em conclusão, o nosso trabalho contribuiu para preencher a lacuna entre a melhor informação científica disponível e sua aplicação na prática clínica, sustentando-se nos três pilares da medicina translacional: investigação básica, clínica e comunidade.Syncope, the most common form of transient loss of consciousness, accounts for up to 5% of emergency room visits and up to 3% of hospital admissions. It is a frequent medical problem with multiple triggers, potentially dangerous, incapacitating, and challenging to diagnose. Therefore, a detailed clinical history is needed first to establish the nature of the loss of consciousness. However, after diagnosis, the therapeutic measures available are still very poor. Although the exact pathophysiology of vasovagal syncope remains to be clarified, some underlying mechanisms have been unveiled, dependent not only on the cause of syncope but also on age and various other factors that affect clinical presentation. Ultimately, syncope depends on a failure of the circulation to perfuse the brain, so any factor affecting blood circulation may determine syncope occurrence. Thus, the purpose of the present study is to understand the impact of the hemodynamic and autonomic functions on reflex syncope mechanisms to improve patients diagnose, prognosis and general quality of life. Bearing that in mind, we designed and implemented new mathematical and computational tools for autonomic and hemodynamic evaluation, in order to deepen the understanding of their involvement in reflex syncope mechanisms. Furthermore, by refining the diagnostic accuracy, sensitivity and specificity of the head-up tilt-table test, we established a predictive tool for the impending syncopal episode. This allowed us to establish effective and personalised treatment alternatives to patient’s refractory to conventional options, contributing to their increase in the quality of life and a reduction of health care and associated costs. In accordance, in a truly multidisciplinary study involving reflex syncope patients, we were able to show an elemental functional asynchrony of hemodynamic and autonomic reflex responses, expressed through a temporal mismatch between cardiac output and total peripheral resistance adaptations, a deferred baroreflex response and an unbalanced, but incremental, autonomic tone, all contributing to autonomic dysfunction, translated into a decreased sympathetic reserve. Through the design, testing and implementation of a computational platform and the associated software - FisioSinal platform -, we developed novel and dynamic ways of autonomic and hemodynamic evaluation, whose data lead to the development of predictive algorithms for syncope patients’risk stratification. Furthermore, through the application of these tools, we showed the effectiveness of a non-invasive, non-disruptive and integrated treatment, focusing on neuromodulation of the autonomic and cardiovascular variables involved in the syncope mechanisms, leading to a substantial increase of quality of life and the abolishment of syncopal events in a vast majority of the enrolled patients. In conclusion, our work contributed to fill the gap between the best available scientific information and its application in the clinical practice by tackling the three pillars of translational medicine: bench-side, bedside and community