Theoretical Analysis of Multimodal Four-Wave Mixing in Optical Microwires

Optical fiber microwires (OFMs) are nonlinear optical waveguides that support several spatial modes. The multimodal generalized nonlinear Schrodinger equation (MM-GNLSE) is deduced taking into account the linear and nonlinear modal coupling. A detailed theoretical description of four-wave mixing (FWM) considering the modal coupling is developed. Both, the intramode and the intermode phase-matching conditions is calculated for an optical microwire in a strong guiding regime. Finally, the FWM dynamics is studied and the amplitude evolution of the pump beams, the signal and the idler are analyzed.

Classification and staging of chronic liver disease from multimodal data

Chronic liver disease (CLD) is most of the time an asymptomatic, progressive, and ultimately potentially fatal disease. In this study, an automatic hierarchical procedure to stage CLD using ultrasound images, laboratory tests, and clinical records are described. The first stage of the proposed method, called clinical based classifier (CBC), discriminates healthy from pathologic conditions. When nonhealthy conditions are detected, the method refines the results in three exclusive pathologies in a hierarchical basis: 1) chronic hepatitis; 2) compensated cirrhosis; and 3) decompensated cirrhosis. The features used as well as the classifiers (Bayes, Parzen, support vector machine, and k-nearest neighbor) are optimally selected for each stage. A large multimodal feature database was specifically built for this study containing 30 chronic hepatitis cases, 34 compensated cirrhosis cases, and 36 decompensated cirrhosis cases, all validated after histopathologic analysis by liver biopsy. The CBC classification scheme outperformed the nonhierachical one against all scheme, achieving an overall accuracy of 98.67% for the normal detector, 87.45% for the chronic hepatitis detector, and 95.71% for the cirrhosis detector.

Embedded System for ECG Biometrics

Comunication in Internationa Conference with Peer Review First International Congress on Cardiovasular Technologies - CARDIOTECHNIX, Vilamoura, Portugal, 2013

Dominant set approach to ECG biometrics

Electrocardiographic (ECG) signals are emerging as a recent trend in the field of biometrics. In this paper, we propose a novel ECG biometric system that combines clustering and classification methodologies. Our approach is based on dominant-set clustering, and provides a framework for outlier removal and template selection. It enhances the typical workflows, by making them better suited to new ECG acquisition paradigms that use fingers or hand palms, which lead to signals with lower signal to noise ratio, and more prone to noise artifacts. Preliminary results show the potential of the approach, helping to further validate the highly usable setups and ECG signals as a complementary biometric modality.

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 Biometrics: A Template Selection Approach

Electrocardiography (ECG) biometrics is emerging as a viable biometric trait. Recent developments at the sensor level have shown the feasibility of performing signal acquisition at the fingers and hand palms, using one-lead sensor technology and dry electrodes. These new locations lead to ECG signals with lower signal to noise ratio and more prone to noise artifacts; the heart rate variability is another of the major challenges of this biometric trait. In this paper we propose a novel approach to ECG biometrics, with the purpose of reducing the computational complexity and increasing the robustness of the recognition process enabling the fusion of information across sessions. Our approach is based on clustering, grouping individual heartbeats based on their morphology. We study several methods to perform automatic template selection and account for variations observed in a person's biometric data. This approach allows the identification of different template groupings, taking into account the heart rate variability, and the removal of outliers due to noise artifacts. Experimental evaluation on real world data demonstrates the advantages of our approach.

Enhancing Multimodal Silent Speech Interfaces With Feature Selection

In research on Silent Speech Interfaces (SSI), different sources of information (modalities) have been combined, aiming at obtaining better performance than the individual modalities. However, when combining these modalities, the dimensionality of the feature space rapidly increases, yielding the well-known "curse of dimensionality". As a consequence, in order to extract useful information from this data, one has to resort to feature selection (FS) techniques to lower the dimensionality of the learning space. In this paper, we assess the impact of FS techniques for silent speech data, in a dataset with 4 non-invasive and promising modalities, namely: video, depth, ultrasonic Doppler sensing, and surface electromyography. We consider two supervised (mutual information and Fisher's ratio) and two unsupervised (meanmedian and arithmetic mean geometric mean) FS filters. The evaluation was made by assessing the classification accuracy (word recognition error) of three well-known classifiers (knearest neighbors, support vector machines, and dynamic time warping). The key results of this study show that both unsupervised and supervised FS techniques improve on the classification accuracy on both individual and combined modalities. For instance, on the video component, we attain relative performance gains of 36.2% in error rates. FS is also useful as pre-processing for feature fusion. Copyright © 2014 ISCA.

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.

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.

Embedded system for individual recognition based on ECG biometrics

Biometric recognition is emerging has an alternative solution for applications where the privacy of the information is crucial. This paper presents an embedded biometric recognition system based on the Electrocardiographic signals (ECG) for individual identification and authentication. The proposed system implements a real-time state-of-the-art recognition algorithm, which extracts information from the frequency domain. The system is based on a ARM Cortex 4. Preliminary results show that embedded platforms are a promising path for the implementation of ECG-based applications in real-world scenario.

Alterações da força de preensão em portadores de polineuropatia amiloidótica familiar

Introdução: A polineuropatia amiloidótica familiar (PAF) é uma doença autossómica dominante neurodegenerativa relacionada com a deposição sistémica de fibras de amiloide essencialmente a nível do sistema nervoso periférico. Clinicamente, caracteriza-se por uma neuropatia sensitivo-motora iniciando-se quase sempre nos membros inferiores e comprometendo subsequentemente as mãos. Até agora, o único tratamento conhecido com efeitos positivos no atrasar da progressão da doença é o transplante hepático com medicação com efeitos negativos para o metabolismo muscular e consequentemente para a capacidade de produção de força. Do nosso conhecimento, não existem caracterizações quantitativas dos níveis de força nestes indivíduos nem comparações com a população saudável. Este conhecimento seria extremamente importante para verificar a evolução clínica e funcional desta doença e para a eventual prescrição adequada de um programa de reabilitação. Objectivo: O objectivo deste estudo foi descrever e comparar os níveis de força de preensão (peak force) entre doentes PAF com ou sem transplante de fígado (PAFTx e PAFNTx, respectivamente) com um grupo de indivíduos saudáveis (GC). Material e métodos: A amostra total foi constituída por 206 indivíduos, divididos em três grupos: 59 indivíduos PAFNTx (23 homens, 36 mulheres; idade 35 ± 8 anos); 85 indivíduos PAFTx (52 homens, 33 mulheres; idade 34 ± 8 anos) e 62 GC (30 homens, 32 mulheres; idade 33 ± 9 anos). A força de preensão foi avaliada com um dinamómetro de preensão portátil E-Link (Biometrics Ltd, UK). Tanto as posições de medição como as ordens fornecidas foram estandardizadas. O valor de força máxima considerado foi classificado de acordo com as normas do American College of Sports Medicine (ACSM) para a força de preensão. Resultados: Os três grupos são diferentes (p < 0,05) no peso, no IMC e na força de preensão em ambas as mãos, bem como na resistência da mão esquerda. Foram encontradas correlações negativas entre a força e a idade, para os grupos PAFNTx e PAFTx, mas não para o grupo GC. Conclusões: De acordo com os nossos resultados, os indivíduos portadores de PAF apresentaram valores mais baixos para a força de preensão em ambas as mãos do que os indivíduos aparentemente saudáveis e consequentemente uma pior classificação nas normas do ACSM. A maioria dos doentes apresenta valores de força de preensão abaixo da média ou mesmo precária. Estes resultados poderão mostrar as implicações negativas na funcionalidade destes indivíduos e indicam também a necessidade de um programa de reabilitação com especificidade ao nível da motricidade da mão.

Avaliação da força de preensão em indivíduos expostos e não expostos a actividade manual específica (repetitividade e exposição ao frio): estudo comparativo

1º Prémio para melhor comunicação em poster.

JAMAR vs E-Link: análise de concordância

Avaliar a força de preensão é fundamental pela sua relação com a capacidade funcional dos indivíduos, permitindo determinar níveis de risco para incapacidade futura e assim estabelecer estratégias de prevenção. Grande parte dos estudos utiliza o dinamómetro hidráulico JAMAR que fornece o valor da força isométrica obtida durante a execução do movimento de preensão palmar. Contudo, existem outros dinamómetros disponíveis, como é o caso do dinamómetro portátil computorizado E-Link (Biometrics), que fornece o valor da força máxima (peak force), mas também outras variáveis relacionadas, como por exemplo a taxa de fadiga. Não existem, contudo, estudos de análise de concordância que nos permitam aceitar e comparar ou não os valores obtidos com os dois equipamentos e porventura utilizá-los indistintamente.

Força de preensão – Análise de concordância entre dois dinamómetros: JAMAR vs E‑Link

Introdução – Avaliar a força de preensão mostrou ser de primordial importância pela sua relação com a capacidade funcional dos indivíduos, permitindo determinar níveis de risco para incapacidade futura e, assim, estabelecer estratégias de prevenção. Grande parte dos estudos utiliza o dinamómetro hidráulico JAMAR que fornece o valor da força isométrica obtida durante a execução do movimento de preensão palmar. Contudo, existem outros dinamómetros disponíveis, como é o caso do dinamómetro portátil computorizado E‑Link (Biometrics) que fornece o valor da força máxima (peak force), para além de outras variáveis, como a taxa de fadiga. Não existem, contudo, estudos que nos permitam aceitar e comparar ou não os valores obtidos com os dois equipamentos e porventura utilizá‑los indistintamente. Objetivos – Avaliar a concordância entre as medições da força de preensão (força máxima ou peak force em Kg) obtida a partir de dois equipamentos diferentes (dinamómetros portáteis): um computorizado (E‑Link, Biometrics) e outro hidráulico (JAMAR). Metodologia – Foram avaliados 29 indivíduos (13H; 16M; 22±7 anos; 23,2±3,3 kg/m2) em 2 dias consecutivos, na mesma altura do dia. A posição de teste escolhida foi a recomendada pela Associação Americana de Terapeutas Ocupacionais e foi escolhido o melhor resultado de entre 3 tentativas para a mão dominante. Realizou‑se uma análise correlacional entre os valores obtidos na variável analisada em cada equipamento (coeficiente de Spearman) e uma análise de Bland & Altman para verificar a concordância entre as duas medições. Resultados – O coeficiente de correlação entre as duas medições foi elevado (rS= 0,956; p<0,001) e, pela análise de Bland & Altman, os valores obtidos encontram‑se todos dentro do intervalo da média±2SD. Conclusões – As duas medições mostraram ser concordantes, revelando que os dinamómetros testados podem ser comparáveis ou utilizados indistintamente em diferentes estudos e populações. ABSTRACT: Introduction – Assess grip strength has proved to be of vital importance because of its relationship with functional capacity of individuals, in order to determine levels of risk for future disability and thereby establish prevention strategies. Most studies use the JAMAR Hydraulic dynamometer that provides the value of isometric force obtained during the performance of grip movement. However, there are other dynamometers available, such as portable computerized dynamometer E‑Link (Biometrics), which provides the value of maximum force (peak force) in addition to other variables as the rate of fatigue. There are no studies that allow us to accept or not and compare values obtained with both devices and perhaps use them interchangeably. Purpose – To evaluate the agreement between the measurements of grip strength (peak force or maximum force in kg) obtained from two different devices (portable dynamometers): a computerized (E‑Link, Biometrics) and a hydraulic (JAMAR). Methodology – 29 subjects (13H, 16M, 22 ± 7 years, 23.2 ± 3.3 kg/m2) were assessed on two consecutive days at the same time of day. The test position chosen was recommended by the American Association of Occupational Therapists and was considered the best result from three attempts for the dominant hand. A correlation was studied between values obtained in the variable analyzed in each equipment (Spearman coefficient) and Bland‑Altman analysis to assess the agreement between the two measurements. Results – The correlation coefficient between the two measurements was high (rs = 0,956, p <0,001) and Bland & Altman analysis of the values obtained are all within the range of mean±2SD. Conclusions – The two measurements were shown to be concordant, revealing that the tested dynamometers can be comparable or used interchangeably in different studies and populations.