Dynamic Time Warping in Biosignal Processing

Práce je věnována metodě borcení časové osy v oblasti biosignálů, zejména pak jejímu využití pro signály EKG. V úvodu jsou shrnuty teoretické poznatky o elektrokardiografii, následuje rozbor metody DTW společně se stanovením podmínek a požadavků na úspěšnou aplikaci algoritmu. Jsou popsány varianty metody a možnosti její aplikace. Náplní části praktické je návrh samotné metody, seznámení se s výstupy, optimalizace nastavení a realizace metod s borcením časové osy souvisejícíchThis work is dedicated to dynamic time warping in biosignal processing, especially it´s application for ECG signals. On the beginning the theoretical notes about cardiography are summarized. Then, the DTW analysis follows along with conditions and demands assessments for it’s successful application. Next, several variants and application possibilities are described. The practical part covers the design of this method, the outputs comprehension, settings optimization and realization of methods related with DTW

Reconhecimento biométrico considerando a deformação não linear da íris humana

The biometric systems that use the information on iris texture has received great attention in recent years. The extraordinary variation in iris texture allows the creation of recognition and identification systems with almost zero error rates. However, in general, researches ignore the problems associated with contraction and dilation iris movements that can result in significant differences between the enrollment images and the probe image. This work, in addition to developing a traditional iris recognition system, comprising the steps of detection, segmentation, normalization, encoding and comparison, determines quantitatively the iris motion effect in recognition system accuracy. In addition, this paper proposes a new method to reduce the influence of dynamic iris, verified by decidability and the Equal Error Rate (EER), obtained in the comparison between iris codes in very different expansion states. The new method uses Dynamic Time Warping technique to correct and compare the gradient vectors extracted from iris texture. Thus, the most discriminant features of the test image and enrollment image are aligned and compared, considering the non-linear distortion of the iris tissue. Experimental results using dynamic images indicate that system performance gets worse with comparison on images in different states contraction. For direct comparison with contracted and dilated iris the proposed method improves the decidability of 3.50 to 4.39 and EER of 9.69% to 3.36%.Coordenação de Aperfeiçoamento de Pessoal de Nível SuperiorFundação de Amparo a Pesquisa do Estado de Minas GeraisTese (Doutorado)Os sistemas biométricos que utilizam a informação contida na textura da íris têm recebido grande atenção nos últimos anos. A grande variação em textura da íris permite o desenvolvimento de sistemas de reconhecimento e de identificação com taxas de erro quase nulas. Entretanto, de forma geral, as pesquisas nesta área ignoram os problemas associados aos movimentos de contração e dilatação da íris que geram diferenças significativas entre as imagens inscritas em uma base de dados e a imagem de teste. Este trabalho, além de desenvolver um sistema de reconhecimento de íris tradicional, composto pelas etapas de detecção, segmentação, normalização, codificação e comparação, determina de forma quantitativa o efeito dos movimentos da íris na precisão do sistema de reconhecimento. Além disso, este trabalho propõe um novo método para diminuir a influência da dinâmica da íris, verificado pela decidibilidade e pela Taxa de Erro Igual (EER), obtidas na comparação entre códigos de íris em estados de dilatação bem diferentes. O novo método utiliza a técnica Dynamic Time Warping para corrigir e comparar os vetores de gradientes extraídos da textura da íris. Dessa forma, as características mais discriminantes da imagem de teste e da imagem da galeria são alinhadas e comparadas, considerando a deformação não linear do tecido da íris. Os resultados experimentais, utilizando imagens dinâmicas, indicam que a performance do sistema piora quando a comparação é feita com imagens em estados de contração diferentes. Para a comparação direta entre íris bem contraída com íris bem dilatada o método proposto melhora a decidibilidade de 3,50 para 4,39 e a EER de 9,69% para 3,36%

Footfall and the territorialisation of urban places measured through the rhythms of social activity

The UK high street is constantly changing and evolving in response to, for example, online sales, out-of-town developments, and economic crises. With over 10 years of hourly footfall counts from sensors across the UK, this study was an opportunity to perform a longitudinal and quantitative investigation to diagnose how these changes are reflected in the changing patterns of pedestrian activity. Footfall provides a recognised performance measure of place vitality. However, through a lack of data availability due to historic manual counting methods, few opportunities to contextualise the temporal patterns longitudinally have existed. This study therefore investigates daily, weekly, and annual footfall patterns, to diagnose the similarities and differences between places as social activity patterns from UK high streets evolve over time. Theoretically, footfall is conceptualised within the framework of Territorology and Assemblage Theory, conceptually underpinning a quantitative approach to represent the collective meso-level (street and town-centre) patterns of footfall (social) activity. To explore the data, the periodic signatures of daily, weekly, and annual footfall are extracted using STL (seasonal trend decomposition using Loess) algorithms and the outputs are then analysed using fuzzy clustering techniques. The analyses successfully identify daily, weekly, and annual periodic patterns and diagnose the varying social activity patterns for different urban place types and how places, both individually and collectively are changing. Footfall is demonstrated to be a performance measure of meso-scale changes in collective social activity. For place management, the fuzzy analysis provides an analytical tool to monitor the annual, weekly, and daily footfall signatures providing an evidence-based diagnostic of how places are changing over time. The place manager is therefore better able to identify place specific interventions that correspond to the usage patterns of visitors and adapt these interventions as behaviours change