5 documents found, page 1 of 1
Feature-Based Information Retrieval of Multimodal Biosignals with a Self-Simila...
Rodrigues, João; Liu, Hui; Folgado, Duarte; Belo, David; Schultz, Tanja; Gamboa, HugoThe APC was funded by the Open Access Initiative of the University of Bremen and the DFG via SuUB Bremen. Hanse Wissenschaftskolleg - Institute for Advanced Study: BRAIN Program. Publisher Copyright: © 2022 by the authors.; Biosignal-based technology has been increasingly available in our daily life, being a critical information source. Wearable biosensors have been widely applied in, among others, biometrics, ...
Ecg biometrics using deep learning and relative score threshold classification
Belo, David; Bento, Nuno; Silva, Hugo; Fred, Ana; Gamboa, HugoPD/BDE/130216/2017; The field of biometrics is a pattern recognition problem, where the individual traits are coded, registered, and compared with other database records. Due to the difficulties in reproducing Electrocardiograms (ECG), their usage has been emerging in the biometric field for more secure applications. Inspired by the high performance shown by Deep Neural Networks (DNN) and to mitigate the intra-...
SSTS: A syntactic tool for pattern search on time series
Rodrigues, João; Folgado, Duarte; Belo, David; Gamboa, HugoWe would like to acknowledge the financial support obtained from North Portugal Regional Operational Programme (NORTE 2020), Portugal 2020 and the European Regional Development Fund (ERDF) from European Union through the project Symbiotic technology for societal efficiency gains: Deus ex Machina (DEM), NORTE-01-0145-FEDER-000026. We would like to acknowledge as well the projects AHA CMUP-ERI/HCI/0046 and INSIDE...
Biosignals learning and synthesis using deep neural networks
Belo, David; Rodrigues, João; Vaz, João R.; Pezarat-Correia, Pedro; Gamboa, HugoBackground: Modeling physiological signals is a complex task both for understanding and synthesize biomedical signals. We propose a deep neural network model that learns and synthesizes biosignals, validated by the morphological equivalence of the original ones. This research could lead the creation of novel algorithms for signal reconstruction in heavily noisy data and source detection in biomedical engineerin...
Comparison of machine learning methods for the arterial hypertension diagnostics
Kublanov, Vladimir S.; Dolganov, Anton Yu; Belo, David; Gamboa, HugoAct 211 Government of the Russian Federation (02.A03.21.0006) FCT (AHA CMUP-ERI/HCI/0046/2013); The paper presents results of machine learning approach accuracy applied analysis of cardiac activity. The study evaluates the diagnostics possibilities of the arterial hypertension by means of the short-term heart rate variability signals. Two groups were studied: 30 relatively healthy volunteers and 40 patients suf...