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.

Speech as the basic interface for assistive technology

Speech interfaces for Assistive Technologies are not common and are usually replaced by others. The market they are targeting is not considered attractive and speech technologies are still not well spread. Industry still thinks they present some performance risks, especially Speech Recognition systems. As speech is the most elemental and natural way for communication, it has strong potential for enhancing inclusion and quality of life for broader groups of users with special needs, such as people with cerebral palsy and elderly staying at their homes. This work is a position paper in which the authors argue for the need to make speech become the basic interface in assistive technologies. Among the main arguments, we can state: speech is the easiest way to interact with machines; there is a growing market for embedded speech in assistive technologies, since the number of disabled and elderly people is expanding; speech technology is already mature to be used but needs adaptation to people with special needs; there is still a lot of R&D to be done in this area, especially when thinking about the Portuguese market. The main challenges are presented and future directions are proposed.

Automatic syllabification for danish text-to-speech systems

In this paper, a rule-based automatic syllabifier for Danish is described using the Maximal Onset Principle. Prior success rates of rule-based methods applied to Portuguese and Catalan syllabification modules were on the basis of this work. The system was implemented and tested using a very small set of rules. The results gave rise to 96.9% and 98.7% of word accuracy rate, contrary to our initial expectations, being Danish a language with a complex syllabic structure and thus difficult to be rule-driven. Comparison with data-driven syllabification system using artificial neural networks showed a higher accuracy rate of the former system.

Kalman tracking linear predictor for vowel intelligibility enhancement on european portuguese HMM based speech synthesis

The recent developments on Hidden Markov Models (HMM) based speech synthesis showed that this is a promising technology fully capable of competing with other established techniques. However some issues still lack a solution. Several authors report an over-smoothing phenomenon on both time and frequencies which decreases naturalness and sometimes intelligibility. In this work we present a new vowel intelligibility enhancement algorithm that uses a discrete Kalman filter (DKF) for tracking frame based parameters. The inter-frame correlations are modelled by an autoregressive structure which provides an underlying time frame dependency and can improve time-frequency resolution. The system’s performance has been evaluated using objective and subjective tests and the proposed methodology has led to improved results.

Maximum likelihood detection for OFDM signals with strong nonlinear distortion effects

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

Development of The Viking Speech Scale to Classify the Speech of Children with Cerebral Palsy

Surveillance registers monitor the prevalence of cerebral palsy and the severity of resulting impairments across time and place. The motor disorders of cerebral palsy can affect children’s speech production and limit their intelligibility. We describe the development of a scale to classify children’s speech performance for use in cerebral palsy surveillance registers, and its reliability across raters and across time. Speech and language therapists, other healthcare professionals and parents classified the speech of 139 children with cerebral palsy (85 boys, 54 girls; mean age 6.03 years, SD 1.09) from observation and previous knowledge of the children. Another group of health professionals rated children’s speech from information in their medical notes. With the exception of parents, raters reclassified children’s speech at least four weeks after their initial classification. Raters were asked to rate how easy the scale was to use and how well the scale described the child’s speech production using Likert scales. Inter-rater reliability was moderate to substantial (k > .58 for all comparisons). Test–retest reliability was substantial to almost perfect for all groups (k > .68). Over 74% of raters found the scale easy or very easy to use; 66% of parents and over 70% of health care professionals judged the scale to describe children’s speech well or very well. We conclude that the Viking Speech Scale is a reliable tool to describe the speech performance of children with cerebral palsy, which can be applied through direct observation of children or through case note review.

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)]

Integration of speech-processing technologies into Activobank's client interaction process

This dissertation analyzes the possibilities of utilizing speech-processing technologies to transform the user experience of ActivoBank’s customers while using remote banking solutions. The technologies are examined through different criteria to determine if they support the bank’s goals and strategy and whether they should be incorporated in the bank’s offering. These criteria include the alignment with ActivoBank’s values, the suitability of the technology providers, the benefits these technologies entail, potential risks, appeal to the customers and impact on customer satisfaction. The analysis suggests that ActivoBank might not be in a position to adopt these technologies at this point in time.

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.

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.

STAR: Speech Therapy with Augmented Reality for children with autism spectrum disorders

Graphics based systems of Augmented and Alternative Communication are widely used to promote communication in people with Autism Spectrum Disorders. This study discusses an integration of Augmented Reality in communication interventions, by relating elements of Augmented and Alternative Communication and Applied Behaviour Analysis strategies. An architecture for an Augmented Reality based interactive system to assist interventions is proposed. STAR provides an Augmented Reality tool to assist interventions performed by therapists and support for parents to join in and participate in the child’s intervention. Finally we report on the usage of the Augmented Reality tool in interventions with children with Autism Spectrum Disorders.

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

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

Estimation of nonparametric probability density functions with applications to automatic speech recognition

Magdeburg, Univ., Fak. für Elektrotechnik und Informationstechnik, Diss., 2007