Does independent component analysis play a role in unmixing hyperspectral data?

Independent component analysis (ICA) has recently been proposed as a tool to unmix hyperspectral data. ICA is founded on two assumptions: 1) the observed spectrum vector is a linear mixture of the constituent spectra (endmember spectra) weighted by the correspondent abundance fractions (sources); 2)sources are statistically independent. Independent factor analysis (IFA) extends ICA to linear mixtures of independent sources immersed in noise. Concerning hyperspectral data, the first assumption is valid whenever the multiple scattering among the distinct constituent substances (endmembers) is negligible, and the surface is partitioned according to the fractional abundances. The second assumption, however, is violated, since the sum of abundance fractions associated to each pixel is constant due to physical constraints in the data acquisition process. Thus, sources cannot be statistically independent, this compromising the performance of ICA/IFA algorithms in hyperspectral unmixing. This paper studies the impact of hyperspectral source statistical dependence on ICA and IFA performances. We conclude that the accuracy of these methods tends to improve with the increase of the signature variability, of the number of endmembers, and of the signal-to-noise ratio. In any case, there are always endmembers incorrectly unmixed. We arrive to this conclusion by minimizing the mutual information of simulated and real hyperspectral mixtures. The computation of mutual information is based on fitting mixtures of Gaussians to the observed data. A method to sort ICA and IFA estimates in terms of the likelihood of being correctly unmixed is proposed.

Does Independent Component Analysis Play a Role in Unmixing Hyperspectral Data?

Chapter in Book Proceedings with Peer Review First Iberian Conference, IbPRIA 2003, Puerto de Andratx, Mallorca, Spain, JUne 4-6, 2003. Proceedings

Experimental Study And Evaluation Of Paper-Based Inkjet Electrodes For ECG Signal Acquisition

Applications involving biosignals, such as Electrocardiography (ECG), are becoming more pervasive with the extension towards non-intrusive scenarios helping targeting ambulatory healthcare monitoring, emotion assessment, among many others. In this study we introduce a new type of silver/silver chloride (Ag/AgCl) electrodes based on a paper substrate and produced using an inkjet printing technique. This type of electrodes can increase the potential applications of biosignal acquisition technologies for everyday life use, given that there are several advantages, such as cost reduction and easier recycling, resultant from the approach explored in our work. We performed a comparison study to assess the quality of this new electrode type, in which ECG data was collected with three types of Ag/AgCl electrodes: i) gelled; ii) dry iii) paper-based inkjet printed. We also compared the performance of each electrode when acquired using a professional-grade gold standard device, and a low cost platform. Experimental results showed that data acquired using our proposed inkjet printed electrode is highly correlated with data obtained through conventional electrodes. Moreover, the electrodes are robust to high-end and low-end data acquisition devices. Copyright © 2014 SCITEPRESS - Science and Technology Publications. All rights reserved.

On independent component analysis applied to unmixing hyperspectral data

One of the most challenging task underlying many hyperspectral imagery applications is the spectral unmixing, which decomposes a mixed pixel into a collection of reectance spectra, called endmember signatures, and their corresponding fractional abundances. Independent Component Analysis (ICA) have recently been proposed as a tool to unmix hyperspectral data. The basic goal of ICA is to nd a linear transformation to recover independent sources (abundance fractions) given only sensor observations that are unknown linear mixtures of the unobserved independent sources. In hyperspectral imagery the sum of abundance fractions associated to each pixel is constant due to physical constraints in the data acquisition process. Thus, sources cannot be independent. This paper address hyperspectral data source dependence and its impact on ICA performance. The study consider simulated and real data. In simulated scenarios hyperspectral observations are described by a generative model that takes into account the degradation mechanisms normally found in hyperspectral applications. We conclude that ICA does not unmix correctly all sources. This conclusion is based on the a study of the mutual information. Nevertheless, some sources might be well separated mainly if the number of sources is large and the signal-to-noise ratio (SNR) is high.

Evolução dos sistema de telegestão da Empresa Portuguesa das Águas Livres, S.A.

O sistema de telegestão é uma ferramenta que permite a gestão, em tempo real, de todo o sistema de abastecimento da Empresa Portuguesa das Águas Livres, S.A. (EPAL). Esta gestão pode ser conseguida desde a captação da água até à sua entrega ao cliente final, através dos meios de monitorização necessários às operações de comando que permitem controlar e manobrar à distância os acessórios do sistema (estações elevatórias, reservatórios, válvulas,…). A presente dissertação visa a divulgação e compilação de elementos fundamentais para a otimização das potencialidades que a telegestão oferece, abordando assim, dada a sua especificidade, um tema pouco divulgado mas de extrema importância a quem trabalha ou pretende trabalhar numa entidade gestora similar. Assim, a dissertação é constituída por seis capítulos que compreendem a caracterização do sistema de adução, transporte e distribuição da EPAL, a abordagem genérica das ferramentas de suporte à exploração do sistema, uma resenha histórica do sistema de telegestão na EPAL, bem como informações referentes ao atual sistema de telegestão, nomeadamente a sua arquitetura, principais funcionalidades, tais como o controlo de órgãos de manobra à distância e análise de parâmetros de qualidade em tempo real. Finalmente, apresentam-se algumas conclusões e recomendações para trabalhos futuros. Pretende-se assim que o presente documento contribua para uma aglutinação de informações relativas aos sistemas de telegestão para abastecimento de água, respetivas vantagens aliadas às suas funcionalidades, bem como a identificação de fragilidades do sistema que poderão ser aperfeiçoadas ou mesmo eliminadas.

Correntes harmónicas em lâmpadas compactas: sistema de aquisição e processamento de sinal e impacto nas instalações eléctricas

Dissertação para a obtenção do grau de Mestre em Engenharia Electrotécnica Ramo de Automação e Electrónica Industrial

Classificação de atividades físicas através do uso do acelerómetro do smartphone

Dissertação de natureza científica realizada para a obtenção do grau de Mestre em Engenharia de redes de comunicação e Multimédia

Determinação de propriedades mecânicas através de ensaios de provetes miniatura, "Small Punch"

Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia Mecânica

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.

Parallel implementation of vertex component analysis for hyperspectral endmember extraction

International Conference with Peer Review 2012 IEEE International Conference in Geoscience and Remote Sensing Symposium (IGARSS), 22-27 July 2012, Munich, Germany

BIT: Biosignal Igniter Toolkit

The study of biosignals has had a transforming role in multiple aspects of our society, which go well beyond the health sciences domains to which they were traditionally associated with. While biomedical engineering is a classical discipline where the topic is amply covered, today biosignals are a matter of interest for students, researchers and hobbyists in areas including computer science, informatics, electrical engineering, among others. Regardless of the context, the use of biosignals in experimental activities and practical projects is heavily bounded by the cost, and limited access to adequate support materials. In this paper we present an accessible, albeit versatile toolkit, composed of low-cost hardware and software, which was created to reinforce the engagement of different people in the field of biosignals. The hardware consists of a modular wireless biosignal acquisition system that can be used to support classroom activities, interface with other devices, or perform rapid prototyping of end-user applications. The software comprehends a set of programming APIs, a biosignal processing toolbox, and a framework for real time data acquisition and postprocessing. (C) 2014 Elsevier Ireland Ltd. All rights reserved.

Análise e implementação de filtros e controladores num sistema de processamento digital de sinal

Dissertação para obtenção do grau de Mestre em Engenharia Electrotécnica Ramo de Automação e Electrónica Industrial

Check your biosignals here: a new dataset for off-person ECG biometrics

The Check Your Biosignals Here initiative (CYBHi) was developed as a way of creating a dataset and consistently repeatable acquisition framework, to further extend research in electrocardiographic (ECG) biometrics. In particular, our work targets the novel trend towards off-the-person data acquisition, which opens a broad new set of challenges and opportunities both for research and industry. While datasets with ECG signals collected using medical grade equipment at the chest can be easily found, for off-the-person ECG data the solution is generally for each team to collect their own corpus at considerable expense of resources. In this paper we describe the context, experimental considerations, methods, and preliminary findings of two public datasets created by our team, one for short-term and another for long-term assessment, with ECG data collected at the hand palms and fingers. (C) 2013 Elsevier Ireland Ltd. All rights reserved.

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.

Experimental apparatus for finger ECG biometrics

Current Electrocardiographic (ECG) signal acquisition methods are generally highly intrusive, as they involve the use of pre-gelled electrodes and cabled sensors placed directly on the person, at the chest or limbs level. Moreover, systems that make use of alternative conductive materials to overcome this issue, only provide heart rate information and not the detailed signal itself. We present a comparison and evaluation of two types of dry electrodes as interface with the skin, targeting wearable and low intrusiveness applications, which enable ECG measurement without the need for any apparatus permanently fitted to the individual. In particular, our approach is targeted at ECG biometrics using signals collected at the hand or finger level. A custom differential circuit with virtual ground was also developed for enhanced usability. Our work builds upon the current stateof-the-art in sensoring devices and processing tools, and enables novel data acquisition settings through the use of dry electrodes. Experimental evaluation was performed for Ag/AgCl and Electrolycra materials, and results show that both materials exhibit adequate performance for the intended application.