Automatic sleep apnea detection and sleep classification using the ECG and the SpO2 signals

Dissertation for a Masters Degree in Computer and Electronic Engineering

Biometric recognition system using low bandwidth ECG signals

Biometric recognition has recently emerged as part of applications where the privacy of the information is crucial, as in the health care field. This paper presents a biometric recognition system based on the Electrocardiographic signal (ECG). The proposed system is based on a state-of-the-art recognition method which extracts information from the frequency domain. In this paper we propose a new method to increase the spectral resolution of low bandwidth ECG signals due to the limited bandwidth of the acquisition sensor. Preliminary results show that the proposed scheme reveals a higher identification rate and lower equal error rate when compared to previous approaches.

Algorithms for time series clustering applied to biomedical signals

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

A Review on the Characterization of Signals and Systems by Power Law Distributions

Power laws, also known as Pareto-like laws or Zipf-like laws, are commonly used to explain a variety of real world distinct phenomena, often described merely by the produced signals. In this paper, we study twelve cases, namely worldwide technological accidents, the annual revenue of America׳s largest private companies, the number of inhabitants in America׳s largest cities, the magnitude of earthquakes with minimum moment magnitude equal to 4, the total burned area in forest fires occurred in Portugal, the net worth of the richer people in America, the frequency of occurrence of words in the novel Ulysses, by James Joyce, the total number of deaths in worldwide terrorist attacks, the number of linking root domains of the top internet domains, the number of linking root domains of the top internet pages, the total number of human victims of tornadoes occurred in the U.S., and the number of inhabitants in the 60 most populated countries. The results demonstrate the emergence of statistical characteristics, very close to a power law behavior. Furthermore, the parametric characterization reveals complex relationships present at higher level of description.

Maximum likelihood detection for OFDM signals with strong nonlinear distortion effects

Dissertação para obtenção do Grau de Mestre em Engenharia Electrotécnica e de Computadores

Time series morphological analysis applied to biomedical signals events detection

Dissertation submitted in the fufillment of the requirements for the Degree of Master in Biomedical Engineering

Exploring deregulated signals involved in motor neuron-microglia cross-talk in ALS

Part of the results discussed in this thesis was presented in the following meetings: Cunha MI, Cunha C, Vaz AR, Brites D. Studying microglial-motoneuron cross-talk in ALS pathology. 6th iMed.UL Postgraduate Students Meeting, Lisbon, July 2, 2014. [Abstract and Poster] Vaz AR. Motoneuron degeneration and glial reactivity in ALS: insights from cellular to animal models. Neuroscience Seminars at IMM 2012, Instituto de Medicina Molecular, Universidade de Lisboa, Lisbon, Portugal, June 9, 2014. [Oral Communication (by invitation)]

Estudo do controlo motor via Sincronias entre sinais de EEG e de EMG / Motor control study through sincrony between EEG and EMG signals

Um dos maiores desafios da neurofisiologia é o de compreender a forma como a informação é transmitida através do sistema nervoso. O estudo do sistema nervoso tem várias aplicações, tanto na neurologia, permitindo avanços ao nível clínico, como noutras áreas, e.g., nos sistemas de processamento de informação baseados em redes neuronais. A transmissão de informação entre neurónios é feita por via de sinais elétricos. A compreensão deste fenómeno é ainda incompleta e há projectos a nível europeu e mundial com o objetivo de modular o sistema nervoso no seu todo de forma a melhor o compreender. Uma das teses que se desenvolve hoje em dia é a de que a transmissão de sinais elétricos no sistema nervoso é influenciada por fenómenos de sincronia. O objetivo desta dissertação é o de otimizar um protocolo de aquisição e análise de dados reais de eletroencefalograma e eletromiograma com o propósito de observar fenómenos de sincronia, baseando-se num algoritmo (análise por referência de fase, ou RPA, do inglês reference phase analysis) que deteta sincronias de fase entre os sinais de eletroencefalograma (EEG) e um sinal de referência, que é, no caso presente, o eletromiograma (EMG). A otimização deste protocolo e sua validação indicaram a existência de fenómenos significativos de sincronia no sinal elétrico, transmitido entre os músculos da mão e o córtex motor, no decorrer da ação motora.

Analysis and design of sinusoidal quadrature RC-oscillators

Modern telecommunication equipment requires components that operate in many different frequency bands and support multiple communication standards, to cope with the growing demand for higher data rate. Also, a growing number of standards are adopting the use of spectrum efficient digital modulations, such as quadrature amplitude modulation (QAM) and orthogonal frequency division multiplexing (OFDM). These modulation schemes require accurate quadrature oscillators, which makes the quadrature oscillator a key block in modern radio frequency (RF) transceivers. The wide tuning range characteristics of inductorless quadrature oscillators make them natural candidates, despite their higher phase noise, in comparison with LC-oscillators. This thesis presents a detailed study of inductorless sinusoidal quadrature oscillators. Three quadrature oscillators are investigated: the active coupling RC-oscillator, the novel capacitive coupling RCoscillator, and the two-integrator oscillator. The thesis includes a detailed analysis of the Van der Pol oscillator (VDPO). This is used as a base model oscillator for the analysis of the coupled oscillators. Hence, the three oscillators are approximated by the VDPO. From the nonlinear Van der Pol equations, the oscillators’ key parameters are obtained. It is analysed first the case without component mismatches and then the case with mismatches. The research is focused on determining the impact of the components’ mismatches on the oscillator key parameters: frequency, amplitude-, and quadrature-errors. Furthermore, the minimization of the errors by adjusting the circuit parameters is addressed. A novel quadrature RC-oscillator using capacitive coupling is proposed. The advantages of using the capacitive coupling are that it is noiseless, requires a small area, and has low power dissipation. The equations of the oscillation amplitude, frequency, quadrature-error, and amplitude mismatch are derived. The theoretical results are confirmed by simulation and by measurement of two prototypes fabricated in 130 nm standard complementary metal-oxide-semiconductor (CMOS) technology. The measurements reveal that the power increase due to the coupling is marginal, leading to a figure-of-merit of -154.8 dBc/Hz. These results are consistent with the noiseless feature of this coupling and are comparable to those of the best state-of-the-art RC-oscillators, in the GHz range, but with the lowest power consumption (about 9 mW). The results for the three oscillators show that the amplitude- and the quadrature-errors are proportional to the component mismatches and inversely proportional to the coupling strength. Thus, increasing the coupling strength decreases both the amplitude- and quadrature-errors. With proper coupling strength, a quadrature error below 1° and amplitude imbalance below 1% are obtained. Furthermore, the simulations show that increasing the coupling strength reduces the phase noise. Hence, there is no trade-off between phase noise and quadrature error. In the twointegrator oscillator study, it was found that the quadrature error can be eliminated by adjusting the transconductances to compensate the capacitance mismatch. However, to obtain outputs in perfect quadrature one must allow some amplitude error.

Using artificial neural networks to generate trading signals for crude oil, copper and gold futures

In this thesis, a feed-forward, back-propagating Artificial Neural Network using the gradient descent algorithm is developed to forecast the directional movement of daily returns for WTI, gold and copper futures. Out-of-sample back-test results vary, with some predictive abilities for copper futures but none for either WTI or gold. The best statistically significant hit rate achieved was 57% for copper with an absolute return Sharpe Ratio of 1.25 and a benchmarked Information Ratio of 2.11.

Lang anhaltende Prozesse der retinalen Spreading Depression : Untersuchung des intrinsischen optischen Signals

Excitability, wave, reaction-diffusion, chicken, neuron, glia, potassium, nitric oxide, glycolysis

Forearm surface EMG signals recognition and muscoloskeletal system dynamics identification using intelligent computational methods

Biosignals processing, Biological Nonlinear and time-varying systems identification, Electomyograph signals recognition, Pattern classification, Fuzzy logic and neural networks methods

Comparative Analysis of Signals Restoration by Different Kinds of Approximation

The comparative analysis of continuous signals restoration by different kinds of approximation is performed. The software product, allowing to define optimal method of different original signals restoration by Lagrange polynomial, Kotelnikov interpolation series, linear and cubic splines, Haar wavelet and Kotelnikov-Shannon wavelet based on criterion of minimum value of mean-square deviation is proposed. Practical recommendations on the selection of approximation function for different class of signals are obtained.

Membrane potential dynamics of neocortical projection neurons driving target-specific signals.

Primary sensory cortex discriminates incoming sensory information and generates multiple processing streams toward other cortical areas. However, the underlying cellular mechanisms remain unknown. Here, by making whole-cell recordings in primary somatosensory barrel cortex (S1) of behaving mice, we show that S1 neurons projecting to primary motor cortex (M1) and those projecting to secondary somatosensory cortex (S2) have distinct intrinsic membrane properties and exhibit markedly different membrane potential dynamics during behavior. Passive tactile stimulation evoked faster and larger postsynaptic potentials (PSPs) in M1-projecting neurons, rapidly driving phasic action potential firing, well-suited for stimulus detection. Repetitive active touch evoked strongly depressing PSPs and only transient firing in M1-projecting neurons. In contrast, PSP summation allowed S2-projecting neurons to robustly signal sensory information accumulated during repetitive touch, useful for encoding object features. Thus, target-specific transformation of sensory-evoked synaptic potentials by S1 projection neurons generates functionally distinct output signals for sensorimotor coordination and sensory perception.