Publications by Adriana Arza Valdes

Psychosomatic response to acute emotional stress in healthy students

The multidimensionality of the stress response has shown the complexity of this phenomenon and therefore the impossibility of finding a unique biomarker among the physiological variables related to stress. An experimental study was designed and performed t ...

FRONTIERS MEDIA SA2023

Machine-Learning Based Monitoring of Cognitive Workload in Rescue Missions with Drones

Dario Floreano, Ricardo Andres Chavarriaga Lozano, David Atienza Alonso, Fabio Isidoro Tiberio Dell'Agnola, Ping-Keng Jao, Adriana Arza Valdes

In search and rescue missions, drone operations are challenging and cognitively demanding. High levels of cognitive workload can affect rescuers’ performance, leading to failure with catastrophic outcomes. To face this problem, we propose a machine learnin ...

2022

CAFS: Cost-Aware Features Selection Method for Multimodal Stress Monitoring on Wearable Devices

Maria del Carmen Sandi Perez, David Atienza Alonso, Adriana Arza Valdes, João Pedro de Matos Rodrigues, Niloofar Momeni

Objective: Today, stress monitoring on wearable devices is challenged by the tension between high-detection accuracy and battery lifetime driven by multimodal data acquisition and processing. Limited research has addressed the classification cost on multim ...

2022

Real-Time EEG-Based Cognitive Workload Monitoring on Wearable Devices

David Atienza Alonso, Amir Aminifar, Adriana Arza Valdes, Renato Zanetti

Objective: Cognitive workload monitoring (CWM) can enhance human-machine interaction by supporting task execution assistance considering the operator’s cognitive state. Therefore, we propose a machine learning design methodology and a data processing strat ...

2022

Wearable and Continuous Prediction of Passage of Time Perception for Monitoring Mental Health

David Atienza Alonso, Adriana Arza Valdes, Lara Orlandic

A person’s passage of time perception (POTP) is strongly linked to their mental state and stress response, and can therefore provide an easily quantifiable means of continuous mental health monitoring. In this work, we develop a custom experiment and Machi ...

2021

ReBeatICG database

David Atienza Alonso, David Meier, Adriana Arza Valdes, Una Pale, Olivier Muller

ReBeatICG database contains ICG (impedance cardiography) signals recorded during an experimental session of a virtual search and rescue mission with drones. It includes beat-to-beat annotations of the ICG characteristic points, made by a cardiologist, with ...

2021

Synthetic realistic noise-corrupted PPG database and noise generator for the evaluation of PPG denoising and delineation algorithms

David Atienza Alonso, Fabio Isidoro Tiberio Dell'Agnola, Adriana Arza Valdes, Giulio Masinelli

This database is meant to evaluate the performance of denoising and delineation algorithms for PPG signals affected by noise. The noise generator allows applying the algorithms under test to an artificially corrupted reference PPG signal and comparing its ...

2021

MBioTracker: Multimodal Self-Aware Bio-Monitoring Wearable System for Online Workload Detection

David Atienza Alonso, Fabio Isidoro Tiberio Dell'Agnola, Adriana Arza Valdes, Una Pale, Rodrigo Mariño Andrés

Cognitive workload affects operators' performance principally in high-risk or time-demanding situations and when multitasking is required. An online cognitive workload monitoring system can provide valuable inputs to decision-making instances, such as the ...

2021

ReLearn: A Robust Machine Learning Framework in Presence of Missing Data for Multimodal Stress Detection from Physiological Signals

David Atienza Alonso, Adriana Arza Valdes, Arman Iranfar

2021

ReBeatICG: Real-time Low-Complexity Beat-to-beat Impedance Cardiogram Delineation Algorithm

David Atienza Alonso, Adriana Arza Valdes, Una Pale

This work presents ReBeatICG, a real-time, low-complexity beat-to-beat impedance cardiography (ICG) delineation algorithm that allows hemodynamic parameters monitoring. The proposed procedure relies only on the ICG signal compared to most algorithms found ...

2021

SPARE: A Spectral Peak Recovery Algorithm for PPG Signals Pulsewave Reconstruction in Multimodal Wearable Devices

David Atienza Alonso, Fabio Isidoro Tiberio Dell'Agnola, Adriana Arza Valdes, Giulio Masinelli

The photoplethysmographic (PPG) signal is an unobtrusive blood pulsewave measure that has recently gained popularity in the context of the Internet of Things. Even though it is commonly used for heart rate detection, it has been lately employed on multimod ...

2021

Real-Time Personalized Atrial Fibrillation Prediction on Multi-Core Wearable Sensors

David Atienza Alonso, Amir Aminifar, Adriana Arza Valdes, Elisabetta De Giovanni, Miguel Peon Quiros

In the recent Internet-of-Things (IoT) era where biomedical applications require continuous monitoring of relevant data, edge computing keeps gaining more and more importance. These new architectures for edge computing include multi-core and parallel compu ...

2021

Self-Aware Machine Learning for Multimodal Workload Monitoring During Manual Labor on Edge Wearable Sensors

David Atienza Alonso, Amir Aminifar, Adriana Arza Valdes, Farnaz Forooghifar, Giulio Masinelli

The design of reliable wearable technologies for real-time and long-term monitoring presents a major challenge. Self-awareness is a promising solution that enables the system to monitor itself in interaction with the environment and to manage its resources ...

2020

Cognitive workload monitoring in virtual reality based rescue missions with drones

David Atienza Alonso, Fabio Isidoro Tiberio Dell'Agnola, Adriana Arza Valdes, Niloofar Momeni

The use of drones in search and rescue (SAR) missions can be very cognitively demanding. Since high levels of cognitive workload can negatively affect human performance, there is a risk of compromising the mission and leading to failure with catastrophic o ...

2020

EEG Correlates of Difficulty Levels in Dynamical Transitions of Simulated Flying and Mapping Tasks

Ricardo Andres Chavarriaga Lozano, José del Rocio Millán Ruiz, David Atienza Alonso, Fabio Isidoro Tiberio Dell'Agnola, Ping-Keng Jao, Adriana Arza Valdes

Decoding the subjective perception of task difficulty may help improve operator performance, i.e., automatically optimize the task difficulty level. Here, we aim to decode a compound of cognitive states that covaries with the task difficulty level. We desi ...

2020

Real-Time Cognitive Workload Monitoring Based on Machine Learning Using Physiological Signals in Rescue Missions

David Atienza Alonso, Fabio Isidoro Tiberio Dell'Agnola, Adriana Arza Valdes, Niloofar Momeni

High levels of cognitive workload decreases human's performance and leads to failures with catastrophic outcomes in risky missions. Today, reliable cognitive workload detection presents a common major challenge, since the workload is not directly observabl ...

IEEE2019

REWARD: Design, Optimization, and Evaluation of a Real-Time Relative-Energy Wearable R-Peak Detection Algorithm *

Jean-Marc Vesin, David Atienza Alonso, Sasan Yazdani, Adriana Arza Valdes, Elisabetta De Giovanni, Lara Orlandic

Wearable devices are an unobtrusive, cost-effective means of continuous ambulatory monitoring of chronic cardiovascular diseases. However, on these resource-constrained systems, electrocardiogram (ECG) processing algorithms must consume minimal power and m ...

2019

Multi-Modal Acute Stress Recognition Using Off-the-Shelf Wearable Devices

David Atienza Alonso, Amir Aminifar, Fabio Isidoro Tiberio Dell'Agnola, Adriana Arza Valdes, Victoriano Montesinos Canovas

Monitoring stress and, in general, emotions has attracted a lot of attention over the past few decades. Stress monitoring has many applications, including high-risk missions and surgical procedures as well as mental/emotional health monitoring. In this pap ...

IEEE2019

Measuring acute stress response through physiological signals: towards a quantitative assessment of stress

Adriana Arza Valdes

2019