13 resultados para Signal Peptides
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Nonlinear Dynamics, Vol. 29
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SignalProcessing, Vol. 81, nº 3
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In Proceedings of the “ECCTD '01 - European Conference on Circuit Theory and Design, Espoo, Finland, August 2001
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Proceedings of the European Control Conference, ECC’01, Porto, Portugal, September 2001
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Thesis presented in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the subject of Electrical and Computer Engineering by the Universidade Nova de Lisboa,Faculdade de Ciências e Tecnologia
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Dissertation presented to obtain the Ph.D degree in Biology by Universidade Nova de Lisboa, Instituto de Tecnologia Química e Biológica, Instituto Gulbenkian de Ciência.
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Dissertação para obtenção do Grau de Mestre em Engenharia Biomédica
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Dissertação para obtenção do Grau de Mestre em Engenharia Biomédica
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Dissertação apresentada para obtenção do Grau de Doutor em Biologia, na especialidade de Genética Molecular, pela Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia
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Dissertation presented to Faculdade de Ciências e Tecnologia, Universidade Nova de Lisboa for obtaining the master degree in Membrane Engineering
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Dissertation presented to obtain the Ph.D degree in Biochemistry, Engineering and Technological Sciences
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Amyotrophic Lateral Sclerosis (ALS) is a neurodegenerative disease characterized by motor neurons degeneration, which reduces muscular force, being very difficult to diagnose. Mathematical methods are used in order to analyze the surface electromiographic signal’s dynamic behavior (Fractal Dimension (FD) and Multiscale Entropy (MSE)), evaluate different muscle group’s synchronization (Coherence and Phase Locking Factor (PLF)) and to evaluate the signal’s complexity (Lempel-Ziv (LZ) techniques and Detrended Fluctuation Analysis (DFA)). Surface electromiographic signal acquisitions were performed in upper limb muscles, being the analysis executed for instants of contraction for ipsilateral acquisitions for patients and control groups. Results from LZ, DFA and MSE analysis present capability to distinguish between the patient group and the control group, whereas coherence, PLF and FD algorithms present results very similar for both groups. LZ, DFA and MSE algorithms appear then to be a good measure of corticospinal pathways integrity. A classification algorithm was applied to the results in combination with extracted features from the surface electromiographic signal, with an accuracy percentage higher than 70% for 118 combinations for at least one classifier. The classification results demonstrate capability to distinguish members between patients and control groups. These results can demonstrate a major importance in the disease diagnose, once surface electromyography (sEMG) may be used as an auxiliary diagnose method.
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The Electrohysterogram (EHG) is a new instrument for pregnancy monitoring. It measures the uterine muscle electrical signal, which is closely related with uterine contractions. The EHG is described as a viable alternative and a more precise instrument than the currently most widely used method for the description of uterine contractions: the external tocogram. The EHG has also been indicated as a promising tool in the assessment of preterm delivery risk. This work intends to contribute towards the EHG characterization through the inventory of its components which are: • Contractions; • Labor contractions; • Alvarez waves; • Fetal movements; • Long Duration Low Frequency Waves; The instruments used for cataloging were: Spectral Analysis, parametric and non-parametric, energy estimators, time-frequency methods and the tocogram annotated by expert physicians. The EHG and respective tocograms were obtained from the Icelandic 16-electrode Electrohysterogram Database. 288 components were classified. There is not a component database of this type available for consultation. The spectral analysis module and power estimation was added to Uterine Explorer, an EHG analysis software developed in FCT-UNL. The importance of this component database is related to the need to improve the understanding of the EHG which is a relatively complex signal, as well as contributing towards the detection of preterm birth. Preterm birth accounts for 10% of all births and is one of the most relevant obstetric conditions. Despite the technological and scientific advances in perinatal medicine, in developed countries, prematurity is the major cause of neonatal death. Although various risk factors such as previous preterm births, infection, uterine malformations, multiple gestation and short uterine cervix in second trimester, have been associated with this condition, its etiology remains unknown [1][2][3].