The accelerated growth of ultra-low-power sensor electronics, low-power circuits and wireless communications, coupled with their integration on emerging systems on chip (SoC) for multimodal monitoring, has led to a new generation of evolving wearable devices and systems. Nowadays, wearable devices are mainly used to measure daily human activities and sports performance, i.e., heart rate, steps, distance, sleep pattern, etc. However, they continue evolving towards health and wellness monitoring, enabling preventive and personalised healthcare.
At the ESL we are focused on designing wearable systems and methods that provide meaningful accuracy, robustness, and little obtrusiveness while delivering data quality and integrity with low energy consumption and memory footprints. Mainly, we develop personalized algorithms (i.e., person-specify), multimodal (i.e., using multiple information sources) and context-aware methods to accurately monitor the targeted outcomes in uncontrolled environments and dealing with the variety of situations imposed by daily monitoring.
Related Publications
CAFS: Cost-Aware Features Selection Method for Multimodal Stress Monitoring on Wearable Devices | ||||
Momeni, Niloofar; Arza Valdes, Adriana; Rodrigues, João; Sandi, Carmen; Atienza Alonso, David | ||||
2021-09-16 | IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING | |||
MBioTracker: Multimodal Self-Aware Bio-Monitoring Wearable System for Online Workload Detection | ||||
Dell'Agnola, Fabio Isidoro Tiberio; Pale, Una; Marino, Rodrigo; Arza Valdes, Adriana; Atienza Alonso, David | ||||
2021-09-08 | IEEE Transactions on Biomedical Circuits and Systems | |||
Wearable and Continuous Prediction of Passage of Time Perception for Monitoring Mental Health | ||||
Orlandic, Lara; Arza Valdes, Adriana; Atienza Alonso, David | ||||
2021-06-07 | Conference Paper | |||
ReLearn: A Robust Machine Learning Framework in Presence of Missing Data for Multimodal Stress Detection from Physiological Signals | ||||
Iranfar, Arman; Arza Valdes, Adriana; Atienza Alonso, David | ||||
2021 | Conference Paper | |||
EEG Correlates of Difficulty Levels in Dynamical Transitions of Simulated Flying and Mapping Tasks | ||||
Jao, Ping-Keng; Chavarriaga, Ricardo; Dell'Agnola, Fabio; Arza, Adriana; Atienza, David; Millan, Jose del R. | ||||
2020-12-09 | IEEE Transactions on Human-Machine Systems | |||
Self-Aware Machine Learning for Multimodal Workload Monitoring During Manual Labor on Edge Wearable Sensors | ||||
Masinelli, Giulio; Forooghifar, Farnaz; Arza, Adriana; Aminifar, Amir; Atienza, David | ||||
2020-02-21 | IEEE Design & Test | |||
Cognitive workload monitoring in virtual reality based rescue missions with drones | ||||
Dell'Agnola, Fabio Isidoro Tiberio; Momeni, Niloofar; Arza Valdes, Adriana; Atienza, David | ||||
2020-02-21 | Conference Paper | |||
Robust Epileptic Seizure Detection on Wearable Systems with Reduced False-Alarm Rate | ||||
Zanetti, Renato; Aminifar, Amir; Atienza Alonso, David | ||||
2020 | ||||
Real-Time Personalized Atrial Fibrillation Prediction on Multi-Core Wearable Sensors | ||||
De Giovanni, Elisabetta; Arza Valdes, Adriana; Peon Quiros, Miguel; Aminifar, Amir; Atienza Alonso, David | ||||
2020 | IEEE Transactions on Emerging Topics in Computing | |||
Multi-Modal Acute Stress Recognition Using Off-the-Shelf Wearable Devices | ||||
Montesinos, Victoriano; Dell'Agnola, Fabio; Arza, Adriana; Aminifar, Amir; Atienza, David | ||||
2019-01-01 | 2019 41St Annual International Conference Of The Ieee Engineering In Medicine And Biology Society (Embc) | |||
Online Obstructive Sleep Apnea Detection on Medical Wearable Sensors | ||||
Surrel, Grégoire; Aminifar, Amir; Rincon Vallejos, Francisco Javier; Murali, Srinivasan; Atienza Alonso, David | ||||
2018-08 | IEEE Transactions on Biomedical Circuits and Systems | |||
Real-Time Event-Driven Classification Technique for Early Detection and Prevention of Myocardial Infarction on Wearable Systems | ||||
Sopic, Dionisije; Aminifar, Amin; Aminifar, Amir; Atienza Alonso, David | ||||
2018 | IEEE Transactions on Biomedical Circuits and Systems |