Observação e modelação do comportamento dinâmico do viaduto do Corgo: utilização integrada de modelos de identificação modal e modelos de elementos finitos de barra

Trabalho Final de Mestrado elaborado no Laboratório Nacional de Engenharia Civil (LNEC) para a obtenção do grau de Mestre em Engenharia Civil pelo Instituto Superior de Engenharia de Lisboa no âmbito do protocolo de Cooperação entre o ISEL e o LNEC

ECG Analysis Using Consensus Clustering

Biosignals analysis has become widespread, upstaging their typical use in clinical settings. Electrocardiography (ECG) plays a central role in patient monitoring as a diagnosis tool in today's medicine and as an emerging biometric trait. In this paper we adopt a consensus clustering approach for the unsupervised analysis of an ECG-based biometric records. This type of analysis highlights natural groups within the population under investigation, which can be correlated with ground truth information in order to gain more insights about the data. Preliminary results are promising, for meaningful clusters are extracted from the population under analysis. © 2014 EURASIP.

ECG-based biometrics: A real time classification approach

Behavioral biometrics is one of the areas with growing interest within the biosignal research community. A recent trend in the field is ECG-based biometrics, where electrocardiographic (ECG) signals are used as input to the biometric system. Previous work has shown this to be a promising trait, with the potential to serve as a good complement to other existing, and already more established modalities, due to its intrinsic characteristics. In this paper, we propose a system for ECG biometrics centered on signals acquired at the subject's hand. Our work is based on a previously developed custom, non-intrusive sensing apparatus for data acquisition at the hands, and involved the pre-processing of the ECG signals, and evaluation of two classification approaches targeted at real-time or near real-time applications. Preliminary results show that this system leads to competitive results both for authentication and identification, and further validate the potential of ECG signals as a complementary modality in the toolbox of the biometric system designer.

Benchmarking de identificação de ano: criação de um site para benchmarking de técnicas de identificação de dano

Dissertação para obtenção do grau de Mestre em Engenharia Mecânica na Área de Manutenção e Produção

Blind hyperspectral unmixing

Hyperspectral unmixing methods aim at the decomposition of a hyperspectral image into a collection endmember signatures, i.e., the radiance or reflectance of the materials present in the scene, and the correspondent abundance fractions at each pixel in the image. This paper introduces a new unmixing method termed dependent component analysis (DECA). This method is blind and fully automatic and it overcomes the limitations of unmixing methods based on Independent Component Analysis (ICA) and on geometrical based approaches. DECA is based on the linear mixture model, i.e., each pixel is a linear mixture of the endmembers signatures weighted by the correspondent abundance fractions. These abundances are modeled as mixtures of Dirichlet densities, thus enforcing the non-negativity and constant sum constraints, imposed by the acquisition process. The endmembers signatures are inferred by a generalized expectation-maximization (GEM) type algorithm. The paper illustrates the effectiveness of DECA on synthetic and real hyperspectral images.

Long-term biosignals visualization and processing

Thesis submitted in the fulfillment of the requirements for the Degree of Master in Biomedical Engineering

Parallel programming in biomedical signal processing

Dissertação para obtenção do Grau de Mestre em Engenharia Biomédica

On the routines of wild-type silk fibroin processing toward silk-inspired materials: a review

For years, silk fibroin of a domestic silkworm, Bombyx mori, has been recognized as a valuable material and extensively used. In the last decades, new application fields are emerging for this versatile material. Those final, specific applications of silk dictate the way it has been processed in industry and research. This review focuses on the description of various approaches for silk downstream processing in a laboratory scale, that fall within several categories. The detailed description of workflow possibilities from the naturally found material to a finally formulated product is presented. Considerable attention is given to (bio-) chemical approaches of silk fibroin transformation, particularly, to its enzyme-driven modifications. The focus of the current literature survey is exclusively on the methods applied in research and not industry.

Kinematics and dynamic complexity of postural transitions in frail elderly subjects.

The aim of this study was to propose a methodology allowing a detailed characterization of body sit-to-stand/stand-to-sit postural transition. Parameters characterizing the kinematics of the trunk movement during sit-to-stand (Si-St) postural transition were calculated using one initial sensor system fixed on the trunk and a data logger. Dynamic complexity of these postural transitions was estimated by fractal dimension of acceleration-angular velocity plot. We concluded that this method provides a simple and accurate tool for monitoring frail elderly and to objectively evaluate the efficacy of a rehabilitation program.

Dense Deformation Field Estimation for Atlas Registration using the Active Contour Framework

In this paper, we propose a new paradigm to carry outthe registration task with a dense deformation fieldderived from the optical flow model and the activecontour method. The proposed framework merges differenttasks such as segmentation, regularization, incorporationof prior knowledge and registration into a singleframework. The active contour model is at the core of ourframework even if it is used in a different way than thestandard approaches. Indeed, active contours are awell-known technique for image segmentation. Thistechnique consists in finding the curve which minimizesan energy functional designed to be minimal when thecurve has reached the object contours. That way, we getaccurate and smooth segmentation results. So far, theactive contour model has been used to segment objectslying in images from boundary-based, region-based orshape-based information. Our registration technique willprofit of all these families of active contours todetermine a dense deformation field defined on the wholeimage. A well-suited application of our model is theatlas registration in medical imaging which consists inautomatically delineating anatomical structures. Wepresent results on 2D synthetic images to show theperformances of our non rigid deformation field based ona natural registration term. We also present registrationresults on real 3D medical data with a large spaceoccupying tumor substantially deforming surroundingstructures, which constitutes a high challenging problem.

Intracranial hypertension: what additional information can be derived from ICP waveform after head injury?

OBJECTIVE: Although intracranial hypertension is one of the important prognostic factors after head injury, increased intracranial pressure (ICP) may also be observed in patients with favourable outcome. We have studied whether the value of ICP monitoring can be augmented by indices describing cerebrovascular pressure-reactivity and pressure-volume compensatory reserve derived from ICP and arterial blood pressure (ABP) waveforms. METHOD: 96 patients with intracranial hypertension were studied retrospectively: 57 with fatal outcome and 39 with favourable outcome. ABP and ICP waveforms were recorded. Indices of cerebrovascular reactivity (PRx) and cerebrospinal compensatory reserve (RAP) were calculated as moving correlation coefficients between slow waves of ABP and ICP, and between slow waves of ICP pulse amplitude and mean ICP, respectively. The magnitude of 'slow waves' was derived using ICP low-pass spectral filtration. RESULTS: The most significant difference was found in the magnitude of slow waves that was persistently higher in patients with a favourable outcome (p<0.00004). In patients who died ICP was significantly higher (p<0.0001) and cerebrovascular pressure-reactivity (described by PRx) was compromised (p<0.024). In the same patients, pressure-volume compensatory reserve showed a gradual deterioration over time with a sudden drop of RAP when ICP started to rise, suggesting an overlapping disruption of the vasomotor response. CONCLUSION: Indices derived from ICP waveform analysis can be helpful for the interpretation of progressive intracranial hypertension in patients after brain trauma.

SA2RAGE: a new sequence for fast B1+ -mapping.

At high magnetic field strengths (≥ 3T), the radiofrequency wavelength used in MRI is of the same order of magnitude of (or smaller than) the typical sample size, making transmit magnetic field (B1+) inhomogeneities more prominent. Methods such as radiofrequency-shimming and transmit SENSE have been proposed to mitigate these undesirable effects. A prerequisite for such approaches is an accurate and rapid characterization of the B1+ field in the organ of interest. In this work, a new phase-sensitive three-dimensional B1+-mapping technique is introduced that allows the acquisition of a 64 × 64 × 8 B1+-map in ≈ 20 s, yielding an accurate mapping of the relative B1+ with a 10-fold dynamic range (0.2-2 times the nominal B1+). Moreover, the predominant use of low flip angle excitations in the presented sequence minimizes specific absorption rate, which is an important asset for in vivo B1+-shimming procedures at high magnetic fields. The proposed methodology was validated in phantom experiments and demonstrated good results in phantom and human B1+-shimming using an 8-channel transmit-receive array.

Integrated methodologies to study human transcriptional regulation from functional genomics data

Abstract : The human body is composed of a huge number of cells acting together in a concerted manner. The current understanding is that proteins perform most of the necessary activities in keeping a cell alive. The DNA, on the other hand, stores the information on how to produce the different proteins in the genome. Regulating gene transcription is the first important step that can thus affect the life of a cell, modify its functions and its responses to the environment. Regulation is a complex operation that involves specialized proteins, the transcription factors. Transcription factors (TFs) can bind to DNA and activate the processes leading to the expression of genes into new proteins. Errors in this process may lead to diseases. In particular, some transcription factors have been associated with a lethal pathological state, commonly known as cancer, associated with uncontrolled cellular proliferation, invasiveness of healthy tissues and abnormal responses to stimuli. Understanding cancer-related regulatory programs is a difficult task, often involving several TFs interacting together and influencing each other's activity. This Thesis presents new computational methodologies to study gene regulation. In addition we present applications of our methods to the understanding of cancer-related regulatory programs. The understanding of transcriptional regulation is a major challenge. We address this difficult question combining computational approaches with large collections of heterogeneous experimental data. In detail, we design signal processing tools to recover transcription factors binding sites on the DNA from genome-wide surveys like chromatin immunoprecipitation assays on tiling arrays (ChIP-chip). We then use the localization about the binding of TFs to explain expression levels of regulated genes. In this way we identify a regulatory synergy between two TFs, the oncogene C-MYC and SP1. C-MYC and SP1 bind preferentially at promoters and when SP1 binds next to C-NIYC on the DNA, the nearby gene is strongly expressed. The association between the two TFs at promoters is reflected by the binding sites conservation across mammals, by the permissive underlying chromatin states 'it represents an important control mechanism involved in cellular proliferation, thereby involved in cancer. Secondly, we identify the characteristics of TF estrogen receptor alpha (hERa) target genes and we study the influence of hERa in regulating transcription. hERa, upon hormone estrogen signaling, binds to DNA to regulate transcription of its targets in concert with its co-factors. To overcome the scarce experimental data about the binding sites of other TFs that may interact with hERa, we conduct in silico analysis of the sequences underlying the ChIP sites using the collection of position weight matrices (PWMs) of hERa partners, TFs FOXA1 and SP1. We combine ChIP-chip and ChIP-paired-end-diTags (ChIP-pet) data about hERa binding on DNA with the sequence information to explain gene expression levels in a large collection of cancer tissue samples and also on studies about the response of cells to estrogen. We confirm that hERa binding sites are distributed anywhere on the genome. However, we distinguish between binding sites near promoters and binding sites along the transcripts. The first group shows weak binding of hERa and high occurrence of SP1 motifs, in particular near estrogen responsive genes. The second group shows strong binding of hERa and significant correlation between the number of binding sites along a gene and the strength of gene induction in presence of estrogen. Some binding sites of the second group also show presence of FOXA1, but the role of this TF still needs to be investigated. Different mechanisms have been proposed to explain hERa-mediated induction of gene expression. Our work supports the model of hERa activating gene expression from distal binding sites by interacting with promoter bound TFs, like SP1. hERa has been associated with survival rates of breast cancer patients, though explanatory models are still incomplete: this result is important to better understand how hERa can control gene expression. Thirdly, we address the difficult question of regulatory network inference. We tackle this problem analyzing time-series of biological measurements such as quantification of mRNA levels or protein concentrations. Our approach uses the well-established penalized linear regression models where we impose sparseness on the connectivity of the regulatory network. We extend this method enforcing the coherence of the regulatory dependencies: a TF must coherently behave as an activator, or a repressor on all its targets. This requirement is implemented as constraints on the signs of the regressed coefficients in the penalized linear regression model. Our approach is better at reconstructing meaningful biological networks than previous methods based on penalized regression. The method is tested on the DREAM2 challenge of reconstructing a five-genes/TFs regulatory network obtaining the best performance in the "undirected signed excitatory" category. Thus, these bioinformatics methods, which are reliable, interpretable and fast enough to cover large biological dataset, have enabled us to better understand gene regulation in humans.

Effect of n-3 fatty acids on cerebral markers and the inflammatory response in sepsis

Introduction ICM+ software encapsulates our 20 years' experience in brain monitoring. It collects data from a variety of bedside monitors and produces time trends of parameters defi ned using confi gurable mathematical formulae. To date it is being used in nearly 40 clinical research centres worldwide. We present its application for continuous monitoring of cerebral autoregulation using near-infrared spectroscopy (NIRS). Methods Data from multiple bedside monitors are processed by ICM+ in real time using a large selection of signal processing methods. These include various time and frequency domain analysis functions as well as fully customisable digital fi lters. The fi nal results are displayed in a variety of ways including simple time trends, as well as time window based histograms, cross histograms, correlations, and so forth. All this allows complex information from bedside monitors to be summarized in a concise fashion and presented to medical and nursing staff in a simple way that alerts them to the development of various pathological processes. Results One hundred and fi fty patients monitored continuously with NIRS, arterial blood pressure (ABP) and intracranial pressure (ICP), where available, were included in this study. There were 40 severely headinjured adult patients, 27 SAH patients (NCCU, Cambridge); 60 patients undergoing cardiopulmonary bypass (John Hopkins Hospital, Baltimore) and 23 patients with sepsis (University Hospital, Basel). In addition, MCA fl ow velocity (FV) was monitored intermittently using transcranial Doppler. FV-derived and ICP-derived pressure reactivity indices (PRx, Mx), as well as NIRS-derived reactivity indices (Cox, Tox, Thx) were calculated and showed signifi cant correlation with each other in all cohorts. Errorbar charts showing reactivity index PRx versus CPP (optimal CPP chart) as well as similar curves for NIRS indices versus CPP and ABP were also demonstrated. Conclusions ICM+ software is proving to be a very useful tool for enhancing the battery of available means for monitoring cerebral vasoreactivity and potentially facilitating autoregulation guided therapy. Complexity of data analysis is also hidden inside loadable profi les, thus allowing investigators to take full advantage of validated protocols including advanced processing formulas.

A new ambulatory system for comparative evaluation of the three-dimensional knee kinematics, applied to anterior cruciate ligament injuries

The aim of this study was to develop an ambulatory system for the three-dimensional (3D) knee kinematics evaluation, which can be used outside a laboratory during long-term monitoring. In order to show the efficacy of this ambulatory system, knee function was analysed using this system, after an anterior cruciate ligament (ACL) lesion, and after reconstructive surgery. The proposed system was composed of two 3D gyroscopes, fixed on the shank and on the thigh, and a portable data logger for signal recording. The measured parameters were the 3D mean range of motion (ROM) and the healthy knee was used as control. The precision of this system was first assessed using an ultrasound reference system. The repeatability was also estimated. A clinical study was then performed on five unilateral ACL-deficient men (range: 19-36 years) prior to, and a year after the surgery. The patients were evaluated with the IKDC score and the kinematics measurements were carried out on a 30 m walking trial. The precision in comparison with the reference system was 4.4 degrees , 2.7 degrees and 4.2 degrees for flexion-extension, internal-external rotation, and abduction-adduction, respectively. The repeatability of the results for the three directions was 0.8 degrees , 0.7 degrees and 1.8 degrees . The averaged ROM of the five patients' healthy knee were 70.1 degrees (standard deviation (SD) 5.8 degrees), 24.0 degrees (SD 3.0 degrees) and 12.0 degrees (SD 6.3 degrees for flexion-extension, internal-external rotation and abduction-adduction before surgery, and 76.5 degrees (SD 4.1 degrees), 21.7 degrees (SD 4.9 degrees) and 10.2 degrees (SD 4.6 degrees) 1 year following the reconstruction. The results for the pathologic knee were 64.5 degrees (SD 6.9 degrees), 20.6 degrees (SD 4.0 degrees) and 19.7 degrees (8.2 degrees) during the first evaluation, and 72.3 degrees (SD 2.4 degrees), 25.8 degrees (SD 6.4 degrees) and 12.4 degrees (SD 2.3 degrees) during the second one. The performance of the system enabled us to detect knee function modifications in the sagittal and transverse plane. Prior to the reconstruction, the ROM of the injured knee was lower in flexion-extension and internal-external rotation in comparison with the controlateral knee. One year after the surgery, four patients were classified normal (A) and one almost normal (B), according to the IKDC score, and changes in the kinematics of the five patients remained: lower flexion-extension ROM and higher internal-external rotation ROM in comparison with the controlateral knee. The 3D kinematics was changed after an ACL lesion and remained altered one year after the surgery