Embedded System for ECG Biometrics

Comunication in Internationa Conference with Peer Review First International Congress on Cardiovasular Technologies - CARDIOTECHNIX, Vilamoura, Portugal, 2013Biometric recognition has recently emerged as part of applications where the privacy of the information is crucial, as in the health care field. This paper presents an embedded system for individual recognition based on Electrocardiographic (ECG) biometrics. The proposed system implements a real-time state-of-the-art recognition algorithm, which extracts information from the frequency domain, on an architecture based ARM Cortex 4. The system is designed to be free-standing, non-intrusive and easy to use on different environments. Preliminary results show the successful on-the-fly implementation in a embedded platform, enabling its usage on a myriad of operations

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

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

Algoritmos de Sincronização com a Rede: Estudo, Simulação e Implementação Prática

Ao longo do trabalho desenvolvido estudou-se a arquitectura de quatro dos sistemas de detecção de fase existentes na literatura e que historicamente apresentam um impacto evolutivo nesta área, o sistema Detector de Passagem por Zero (Zero Cross Detector-ZCD), o sistema Ciclo de Procura de Fase (Phase Lock Loop-PLL), o sistema PLL com Filtro Rejeita Banda (Notch Filter PLL – NPLL) e o sistema SOGI-PLL (Second Order Generalized Integrator–PLL). Foram analisadas as fragilidades existentes em cada uma das tecnologias estudadas e que serviram de base para que estes algoritmos fossem evoluindo ao longo dos anos, muito em função das necessidades e especificidades encontradas. Procedeu-se ao desenvolvimento matemático de cada um dos algoritmos e, posteriormente, à sua implementação, para simular os perfis de resposta, no programa Matlab®. Para base de teste dos algoritmos em estudo, fez-se o dimensionamento de uma interface electrónica para aquisição e modulação do sinal de tensão da rede real tendo em conta as necessidades de isolamento e segurança. Fez-se ainda um estudo da arquitectura e funcionamento do microcontrolador em uso e, em função desses parâmetros, desenvolveu-se o código numa linguagem compatível e testaram-se os diferentes algoritmos.Along the development of this work it was possible to look at the architecture of four phase detector processes that can easily be found in literature and which represent the one with the most impact on this field of study, the Zero Cross Detector (ZCD), the Phase Lock Loop (PLL), the PLL with a Noch Filter (NPLL) and the Second Order Generalized Integrator (SOGI-PLL). As new requirements and specifications arose, the study of the weaknesses of each of these architectures allowed for the improvement of the algorithms over time. A mathematical study allowed for the creation of models that could be implemented on Matlab® permitting the testing of the algorithms in order to highlight the differences between each of their responses. To simulate the behavior of the algorithms on an environment closer to the ones they are designed for, an electronic platform capable of acquiring and modulating the grids signal was designed and developed taking into account isolation and security measures. This dissertation also includes a study on the architecture and operation of the microcontroller, the details on programming the device and the testing of the different algorithms in a close to reality environment

Tuning iris recognition for noisy images

The use of iris recognition for human authentication has been spreading in the past years. Daugman has proposed a method for iris recognition, composed by four stages: segmentation, normalization, feature extraction, and matching. In this paper we propose some modifications and extensions to Daugman's method to cope with noisy images. These modifications are proposed after a study of images of CASIA and UBIRIS databases. The major modification is on the computationally demanding segmentation stage, for which we propose a faster and equally accurate template matching approach. The extensions on the algorithm address the important issue of pre-processing that depends on the image database, being mandatory when we have a non infra-red camera, like a typical WebCam. For this scenario, we propose methods for reflection removal and pupil enhancement and isolation. The tests, carried out by our C# application on grayscale CASIA and UBIRIS images show that the template matching segmentation method is more accurate and faster than the previous one, for noisy images. The proposed algorithms are found to be efficient and necessary when we deal with non infra-red images and non uniform illumination

Monitorização do processo de condução e alertas baseados no contexto

Motivação e visão geral do sistema: A fadiga é considerada como um dos principais fatores responsável pela sinistralidade rodoviária. Uma agência norte-americana estimou, em 2013, que condutores com sonolência causada pela fadiga provocaram mais de 70 mil acidentes, resultando mais de 40 mil feridos e cerca de 800 mortos. 4 Tipicamente, para realizar a deteção destes aspetos é realizado processamento de imagem, como por exemplo, da retina. Porém, é possível utilizar outras abordagens, nomeadamente os sinais fisiológicos como é feito pelo Cardiowheel. O CardioWheel é um sistema embebido integrável em automóveis, tem como objetivo detetar automaticamente estados de fadiga e a identidade biométrica. Para tal é medido no volante um elemento biométrico do condutor, o sinal cardíaco, e emitidos alertas de fadiga para o exterior através de comunicações por GPRS.info:eu-repo/semantics/publishedVersio

Population density, reproduction cycle and nutritional value of Sphaerechinus granularis (Echinodermata: Echinoidea) in an oceanic insular ecosystem

Sea urchins play an important role in island coastal ecosystems as keystone species and as potential resources for harvesting and aquaculture. In Southern Europe, the most valuable and harvested species is the European purple sea urchin Paracentrotus lividus, but there is a growing interest to explore other edible species like the blunt sea urchin Sphaerechinus granularis. The echinoderms biodiversity of Madeira archipelago was previously described, but their local habitat, population densities and size distribution, important to establish their harvest and aquaculture potential, are poorly known. The present study aimed to evaluate S. granularis population in the oligotrophic and narrow insular shelf of Madeira archipelago, mainly regarding its habitat, densities, reproduction season and roe marketable characteristics. Sphaerechinus granularis was found in low densities (0.01 ind./m2 ) from shallow to deep reefs (5–30 m). The highest densities occurred in shallow waters and breakwaters in association to encrusting algae, turf and erect brown macroalgae. Here, the low primary productivity ecosystem influenced the long reproductive season of the local population. This population showed a relatively high gonadosomatic index (maximum GI of 8), high gonad weight (5.00–12.19 g) with high proportion of bright yellow and orange gonads (37.5–60%) between February and November. Additionally, the high level of total carotenoids, the high PUFA (particularly EPA) content, and the ratio n-6/n-3 close to one support the high nutritional value of S. granularis roe. The trend of incremental GI between September and November and the increasing content of PUFA in autumn suggests this could be the preferential harvesting season. This information is key to evaluate a sustainable exploitation of this living marine resource.info:eu-repo/semantics/publishedVersio

Towards a continuous biometric system based on ECG signals acquired on the steering wheel

Electrocardiogram signals acquired through a steering wheel could be the key to seamless, highly comfortable, and continuous human recognition in driving settings. This paper focuses on the enhancement of the unprecedented lesser quality of such signals, through the combination of Savitzky-Golay and moving average filters, followed by outlier detection and removal based on normalised cross-correlation and clustering, which was able to render ensemble heartbeats of significantly higher quality. Discrete Cosine Transform (DCT) and Haar transform features were extracted and fed to decision methods based on Support Vector Machines (SVM), k-Nearest Neighbours (kNN), Multilayer Perceptrons (MLP), and Gaussian Mixture Models – Universal Background Models (GMM-UBM) classifiers, for both identification and authentication tasks. Additional techniques of user-tuned authentication and past score weighting were also studied. The method’s performance was comparable to some of the best recent state-of-the-art methods (94.9% identification rate (IDR) and 2.66% authentication equal error rate (EER)), despite lesser results with scarce train data (70.9% IDR and 11.8% EER). It was concluded that the method was suitable for biometric recognition with driving electrocardiogram signals, and could, with future developments, be used on a continuous system in seamless and highly noisy settings.info:eu-repo/semantics/publishedVersio

MAMMALS IN PORTUGAL : A data set of terrestrial, volant, and marine mammal occurrences in P ortugal

Mammals are threatened worldwide, with 26% of all species being includedin the IUCN threatened categories. This overall pattern is primarily associatedwith habitat loss or degradation, and human persecution for terrestrial mam-mals, and pollution, open net fishing, climate change, and prey depletion formarine mammals. Mammals play a key role in maintaining ecosystems func-tionality and resilience, and therefore information on their distribution is cru-cial to delineate and support conservation actions. MAMMALS INPORTUGAL is a publicly available data set compiling unpublishedgeoreferenced occurrence records of 92 terrestrial, volant, and marine mam-mals in mainland Portugal and archipelagos of the Azores and Madeira thatincludes 105,026 data entries between 1873 and 2021 (72% of the data occur-ring in 2000 and 2021). The methods used to collect the data were: live obser-vations/captures (43%), sign surveys (35%), camera trapping (16%),bioacoustics surveys (4%) and radiotracking, and inquiries that represent lessthan 1% of the records. The data set includes 13 types of records: (1) burrowsjsoil moundsjtunnel, (2) capture, (3) colony, (4) dead animaljhairjskullsjjaws, (5) genetic confirmation, (6) inquiries, (7) observation of live animal (8),observation in shelters, (9) photo trappingjvideo, (10) predators dietjpelletsjpine cones/nuts, (11) scatjtrackjditch, (12) telemetry and (13) vocalizationjecholocation. The spatial uncertainty of most records ranges between 0 and100 m (76%). Rodentia (n=31,573) has the highest number of records followedby Chiroptera (n=18,857), Carnivora (n=18,594), Lagomorpha (n=17,496),Cetartiodactyla (n=11,568) and Eulipotyphla (n=7008). The data setincludes records of species classified by the IUCN as threatened(e.g.,Oryctolagus cuniculus[n=12,159],Monachus monachus[n=1,512],andLynx pardinus[n=197]). We believe that this data set may stimulate thepublication of other European countries data sets that would certainly contrib-ute to ecology and conservation-related research, and therefore assisting onthe development of more accurate and tailored conservation managementstrategies for each species. There are no copyright restrictions; please cite thisdata paper when the data are used in publications.info:eu-repo/semantics/publishedVersio