A5051286582- ECG Monitoring and Analysis
- Cardiac electrophysiology and arrhythmias
- Heart Rate Variability and Autonomic Control
- EEG and Brain-Computer Interfaces
- Cardiac Arrhythmias and Treatments
- Cardiovascular Function and Risk Factors
- Cardiac pacing and defibrillation studies
- Blind Source Separation Techniques
- Non-Invasive Vital Sign Monitoring
- Neural Networks and Applications
- Fault Detection and Control Systems
- Control Systems and Identification
- Consumer Market Behavior and Pricing
- Direction-of-Arrival Estimation Techniques
- Cardiac Imaging and Diagnostics
- Cardiovascular Syncope and Autonomic Disorders
- Image and Signal Denoising Methods
- Atrial Fibrillation Management and Outcomes
- Speech and Audio Processing
- Cardiovascular Health and Disease Prevention
- Antenna Design and Optimization
- Machine Learning in Healthcare
- Anomaly Detection Techniques and Applications
- Blood Pressure and Hypertension Studies
- Time Series Analysis and Forecasting
Universidad Rey Juan Carlos
2016-2025
Queen's Medical Center
2025
University of Hawaiʻi at Mānoa
2025
Stanford University
2025
Hospital Universitario de Fuenlabrada
2022-2024
Universidad Politécnica de Madrid
2002-2021
Universidad San Francisco de Quito
2020
University of Agder
2018
Escuela Politécnica del Ejército
2014-2016
Secretaría de Educación Superior, Ciencia, Tecnología e Innovación
2015
The multitemporal classification of remote sensing images is a challenging problem, in which the efficient combination different sources information (e.g., temporal, contextual, or multisensor) can improve results. In this paper, we present general framework based on kernel methods for integration heterogeneous information. Using theoretical principles framework, three main contributions are presented. First, novel family kernel-based second contribution development nonlinear classifiers...
This paper provides an overview of the support vector machine ( SVM ) methodology and its applicability to real‐world engineering problems. Specifically, aim this study is review current state technique, show some latest successful results in problems present different fields. The starts by reviewing main basic concepts SVMs kernel methods. Kernel theory, , regression SVR ), signal processing hybridization with meta‐heuristics are fully described first part paper. adoption nowadays a fact....
Early detection of ventricular fibrillation (VF) and rapid tachycardia (VT) is crucial for the success defibrillation therapy. A wide variety algorithms have been proposed based on temporal, spectral, or complexity parameters extracted from ECG. However, these are mostly constructed by considering each parameter individually. In this study, we present a novel life-threatening arrhythmias algorithm that combines number previously ECG using support vector machines classifiers. total 13 were...
Purpose This study aims to address the global food waste problem in restaurants by analyzing customer sales information provided restaurant tickets gain valuable insights into directing of perishable products and optimizing product purchases according demand. Design/methodology/approach A system based on unsupervised machine learning (ML) data models was created provide a simple interpretable management tool. performs analysis two elements: first, it consolidates visualizes mutual nontrivial...
Diastolic suction is a major determinant of early left ventricular filling in animal experiments. However, remains incompletely characterized the clinical setting.First, we validated method for measuring spatio-temporal distributions diastolic intraventricular pressure gradients and differences (DIVPDs) by digital processing color Doppler M-mode recordings. In 4 pigs, error peak DIVPD was 0.0+/-0.2 mm Hg (intraclass correlation coefficient, 0.95) compared with micromanometry. Forty patients...
This paper presents a new approach to auto-regressive and moving average (ARMA) modeling based on the support vector method (SVM) for identification applications. A statistical analysis of characteristics proposed is carried out. An analytical relationship between residuals SVM-ARMA coefficients allows linking fundamentals SVM with several classical system methods. Additionally, effect outliers can be cancelled. Application examples show performance algorithm when it compared other
The free text in electronic health records (EHRs) conveys a huge amount of clinical information about state and patient history. Despite rapidly growing literature on the use machine learning techniques for extracting this information, little effort has been invested toward feature selection features' corresponding medical interpretation. In study, we focus task early detection anastomosis leakage (AL), severe complication after elective surgery colorectal cancer (CRC) surgery, using...
Indoor location systems based on IEEE 802.11b (WiFi) mobile devices often rely the received signal strength indicator to estimate user position. Two key characteristics of these have not yet been fully analyzed, namely, temporal and spatial sampling process required adequately describe distribution electromagnetic field in indoor scenarios; device calibration, necessary for supporting different within same system. By using a previously proposed nonparametric methodology system comparison, we...
A volcanic eruption early warning has to be launched with effectiveness and within the shortest time possible, which imposes requirement of using real-time (RT) systems. In this setting, volcano-monitoring systems wireless sensor networks (WSNs) may play a key role. Previous work did not report detailed-enough performance evaluation, in order identify their main constraints as RT systems, either simulation tools or testbed scenarios. The aim paper was optimum number sensors deployed...
Artificial intelligence (AI) has recently intensified in the global economy due to great competence that it demonstrated for analysis and modeling many disciplines. This situation is accelerating shift towards a more automated society, where these new techniques can be consolidated as valid tool face difficult challenge of credit fraud detection (CFD). However, tight regulations do not make easy financial entities comply with them while using modern techniques. From methodological...
Ejection intraventricular pressure gradients are caused by the systolic force developed left ventricle (LV). By postprocessing color Doppler M-mode (CDMM) images, we can measure noninvasively ejection difference (EIVPD) between LV apex and outflow tract. This study was designed to assess value of Doppler-derived EIVPDs as noninvasive indices chamber function.CDMM images pressure-volume (conductance) signals were simultaneously acquired in 9 minipigs undergoing pharmacological interventions...