User profiles for "author:Antonio Artes"
Antonio Artés RodríguezProfessor, Dept. of Signal Theory and Communications, Universidad Carlos III de Madrid Verified email at tsc.uc3m.es Cited by 4489 |
A configurable and low-power mixed signal SoC for portable ECG monitoring applications
H Kim, S Kim, N Van Helleputte, A Artes… - IEEE transactions on …, 2013 - ieeexplore.ieee.org
This paper describes a mixed-signal ECG System-on-Chip (SoC) that is capable of
implementing configurable functionality with low-power consumption for portable ECG …
implementing configurable functionality with low-power consumption for portable ECG …
Heterogeneous multi-output Gaussian process prediction
P Moreno-Muńoz, A Artés… - Advances in neural …, 2018 - proceedings.neurips.cc
We present a novel extension of multi-output Gaussian processes for handling
heterogeneous outputs. We assume that each output has its own likelihood function and use …
heterogeneous outputs. We assume that each output has its own likelihood function and use …
Validation of Fitbit Charge 2 and Fitbit Alta HR against polysomnography for assessing sleep in adults with obstructive sleep apnea
F Moreno-Pino, A Porras-Segovia… - Journal of Clinical …, 2019 - jcsm.aasm.org
Study Objectives: Consumer wearable devices may be a helpful method of assessing sleep,
but validation is required for their use in clinical practice. Our aim was to validate two models …
but validation is required for their use in clinical practice. Our aim was to validate two models …
[HTML][HTML] Predicting emotional states using behavioral markers derived from passively sensed data: data-driven machine learning approach
Background Mental health disorders affect multiple aspects of patients' lives, including
mood, cognition, and behavior. eHealth and mobile health (mHealth) technologies enable …
mood, cognition, and behavior. eHealth and mobile health (mHealth) technologies enable …
Modular gaussian processes for transfer learning
P Moreno-Muńoz, A Artés… - Advances in Neural …, 2021 - proceedings.neurips.cc
We present a framework for transfer learning based on modular variational Gaussian
processes (GP). We develop a module-based method that having a dictionary of well fitted …
processes (GP). We develop a module-based method that having a dictionary of well fitted …
[HTML][HTML] Shift in social media app usage during COVID-19 lockdown and clinical anxiety symptoms: machine learning–based ecological momentary assessment study
Background Anxiety symptoms during public health crises are associated with adverse
psychiatric outcomes and impaired health decision-making. The interaction between real …
psychiatric outcomes and impaired health decision-making. The interaction between real …
Smartphone-based Ecological Momentary Intervention for secondary prevention of suicidal thoughts and behaviour: protocol for the SmartCrisis V. 2.0 randomised …
ML Barrigon, A Porras-Segovia, P Courtet… - BMJ open, 2022 - bmjopen.bmj.com
Introduction Suicide is one of the leading public health issues worldwide. Mobile health can
help us to combat suicide through monitoring and treatment. The SmartCrisis V. 2.0 …
help us to combat suicide through monitoring and treatment. The SmartCrisis V. 2.0 …
Universal mental health screening with a focus on suicidal behaviour using smartphones in a Mexican rural community: protocol for the SMART-SCREEN population …
PE Arenas-Castańeda, FA Bisquert… - BMJ open, 2020 - bmjopen.bmj.com
Introduction Mental disorders represent the second cause of years lived with disability
worldwide. Suicide mortality has been targeted as a key public health concern by the WHO …
worldwide. Suicide mortality has been targeted as a key public health concern by the WHO …
Support vector method for robust ARMA system identification
JL Rojo-Álvarez, M Martínez-Ramón… - IEEE transactions on …, 2004 - ieeexplore.ieee.org
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 …
modeling based on the support vector method (SVM) for identification applications. A …
Multi-dimensional function approximation and regression estimation
In this communication, we generalize the Support Vector Machines (SVM) for regression
estimation and function approximation to multi-dimensional problems. We propose a multi …
estimation and function approximation to multi-dimensional problems. We propose a multi …