Unveiling the Biometric Potential of Finger-Based ECG Signals

The ECG signal has been shown to contain relevant information for human identification. Even though results validate the potential of these signals, data acquisition methods and apparatus explored so far compromise user acceptability, requiring the acquisition of ECG at the chest. In this paper, we propose a finger-based ECG biometric system, that uses signals collected at the fingers, through a minimally intrusive 1-lead ECG setup recurring to Ag/AgCl electrodes without gel as interface with the skin. The collected signal is significantly more noisy than the ECG acquired at the chest, motivating the application of feature extraction and signal processing techniques to the problem. Time domain ECG signal processing is performed, which comprises the usual steps of filtering, peak detection, heartbeat waveform segmentation, and amplitude normalization, plus an additional step of time normalization. Through a simple minimum distance criterion between the test patterns and the enrollment database, results have revealed this to be a promising technique for biometric applications.

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

SiC pinpin photonic for linking the visible spectrum to the telecom gap

Expanding far beyond traditional applications at telecommunications wavelengths, the SiC photonic devices has recently proven its merits for working with visible range optical signals. Reconfigurable wavelength selectors are essential sub-systems for implementing reconfigurable WDM networks and optical signal processing. Visible range to telecom band spectral translation in SiC/Si can be accomplished using wavelength selector under appropriated optical bias, acting as reconfigurable active filters. In this paper we present a monolithically integrated wavelength selector based on a multilayer SiC/Si integrated optical filters that requires optical switches to select wavelengths. The selector filter is realized by using double pin/pin a-SiC:H photodetector with front and back biased optical gating elements. Red, green, blue and violet communication channels are transmitted together, each one with a specific bit sequence. The combined optical signal is analyzed by reading out the generated photocurrent, under different background wavelengths applied either from the front or the back side. The backgrounds acts as channel selectors that selects one or more channels by splitting portions of the input multi-channel optical signals across the front and back photodiodes. The transfer characteristics effects due to changes in steady state light, irradiation side and frequency are presented. The relationship between the optical inputs and the digital output levels is established. (C) 2014 Elsevier B.V. All rights reserved.

Unified transform architecture for AVC, AVS, VC-1 and HEVC high-performance codecs

A unified architecture for fast and efficient computation of the set of two-dimensional (2-D) transforms adopted by the most recent state-of-the-art digital video standards is presented in this paper. Contrasting to other designs with similar functionality, the presented architecture is supported on a scalable, modular and completely configurable processing structure. This flexible structure not only allows to easily reconfigure the architecture to support different transform kernels, but it also permits its resizing to efficiently support transforms of different orders (e. g. order-4, order-8, order-16 and order-32). Consequently, not only is it highly suitable to realize high-performance multi-standard transform cores, but it also offers highly efficient implementations of specialized processing structures addressing only a reduced subset of transforms that are used by a specific video standard. The experimental results that were obtained by prototyping several configurations of this processing structure in a Xilinx Virtex-7 FPGA show the superior performance and hardware efficiency levels provided by the proposed unified architecture for the implementation of transform cores for the Advanced Video Coding (AVC), Audio Video coding Standard (AVS), VC-1 and High Efficiency Video Coding (HEVC) standards. In addition, such results also demonstrate the ability of this processing structure to realize multi-standard transform cores supporting all the standards mentioned above and that are capable of processing the 8k Ultra High Definition Television (UHDTV) video format (7,680 x 4,320 at 30 fps) in real time.

A new least-squares approach to differintegration modeling

Signal Processing, Vol. 86, nº 10

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

ECG biometrics using a dissimilarity space representation

Electrocardiogram (ECG) biometrics are a relatively recent trend in biometric recognition, with at least 13 years of development in peer-reviewed literature. Most of the proposed biometric techniques perform classifi-cation on features extracted from either heartbeats or from ECG based transformed signals. The best representation is yet to be decided. This paper studies an alternative representation, a dissimilarity space, based on the pairwise dissimilarity between templates and subjects' signals. Additionally, this representation can make use of ECG signals sourced from multiple leads. Configurations of three leads will be tested and contrasted with single-lead experiments. Using the same k-NN classifier the results proved superior to those obtained through a similar algorithm which does not employ a dissimilarity representation. The best Authentication EER went as low as 1:53% for a database employing 503 subjects. However, the employment of extra leads did not prove itself advantageous.

Design and performance evaluation of turbo FDE receivers

Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para obtenção do Grau de Mestre em Engenharia Electrotécnica e de Computadores

Estimation of signal subspace on hyperspectral data

Dimensionality reduction plays a crucial role in many hyperspectral data processing and analysis algorithms. This paper proposes a new mean squared error based approach to determine the signal subspace in hyperspectral imagery. The method first estimates the signal and noise correlations matrices, then it selects the subset of eigenvalues that best represents the signal subspace in the least square sense. The effectiveness of the proposed method is illustrated using simulated and real hyperspectral images.

Análise e implementação de filtros digitais fraccionários

O projeto realizado teve como tema a aplicação das derivadas e integrais fraccionários para a implementação de filtros digitais numa perspetiva de processamento digital de sinais. Numa primeira fase do trabalho, é efetuado uma abordagem teórica sobre os filtros digitais e o cálculo fraccionário. Estes conceitos teóricos são utilizados posteriormente para o desenvolvimento do presente projeto. Numa segunda fase, é desenvolvida uma interface gráfica em ambiente MatLab, utilizando a ferramenta GUIDE. Esta interface gráfica tem como objetivo a implementação de filtros digitais fraccionários. Na terceira fase deste projeto são implementados os filtros desenvolvidos experimentalmente através do ADSP-2181, onde será possível analisar e comparar os resultados experimentais com os resultados obtidos por simulação no MatLab. Como quarta e última fase deste projeto é efetuado uma reflexão sobre todo o desenvolvimento da Tese e o que esta me proporcionou. Com este relatório pretendo apresentar todo o esforço aplicado na realização deste trabalho, bem como alguns dos conhecimentos adquiridos ao longo do curso.

Myoelectric Signal Monitoring System

The Electromyography (EMG) is an important tool for gait analyzes and disorders diagnoses. Traditional methods involve equipment that can disturb the analyses, being gradually substituted by different approaches, like wearable and wireless systems. The cable replacement for autonomous systems demands for technologies capable of meeting the power constraints. This work presents the development of an EMG and kinematic data capture wireless module, designed taking into account power consumption issues. This module captures and converts the analog myoeletric signal to digital, synchronously with the capture of kinetic information. Both data are time multiplexed and sent to a PC via Bluetooth link. The work carried out comprised the development of the hardware, the firmware and a graphical interface running in an external PC. The hardware was developed using the PIC18F14K22, a low power family of microcontrollers. The link was established via Bluetooth, a protocol designed for low power communication. An application was also developed to recover and trace the signal to a Graphic User Interface (GUI), coordinating the message exchange with the firmware. Results were obtained which allowed validating the conceived system in static and with the subject performing short movements. Although it was not possible to perform the tests within more dynamic movements, it is shown that it is possible to capture, transmit and display the captured data as expected. Some suggestions to improve the system performance also were made.

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.

Long-term biosignals visualization and processing

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

Algorithm for the Parkinson’s disease behavioural models characterization using a biosensor

Dissertação para obtenção do Grau de Mestre em Engenharia Biomédica

Advanced instrumentation for superheated liquid detectors in dark matter searches

Dissertação para obtenção do Grau de Doutor em Engenharia Física