Multimodal and personalised methods for health and wellness monitoring

Research Partners

SchindlerSchindler Group

Sources of Funding

Hasler MyPreHealth


Description

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

Wearable and Continuous Prediction of Passage of Time Perception for Monitoring Mental Health
Orlandic, Lara; Arza Valdes, Adriana; Atienza Alonso, David
2021-06-07Conference PaperPublication funded by SNF ML-edge (ML-edge: Enabling Machine-Learning-Based Health Monitoring in Edge Sensors via Architectural Customization)Publication funded by Hasler MyPreHealth (Predicting Episodic Disorders with Health Companions)
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
2021Conference PaperPublication funded by DeepHealth H2020 (Deep-Learning and HPC to Boost Biomedical Applications for Health)Publication funded by SNF ML-edge (ML-edge: Enabling Machine-Learning-Based Health Monitoring in Edge Sensors via Architectural Customization)
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.
2020-12-09IEEE 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
2020-02-21IEEE Design & TestPublication funded by Hasler MyPreHealth (Predicting Episodic Disorders with Health Companions)Publication funded by Schindler (Schindler-Invention AG)
Cognitive workload monitoring in virtual reality based rescue missions with drones
Dell'Agnola, Fabio Isidoro Tiberio; Momeni, Niloofar; Arza Valdes, Adriana; Atienza, David
2020-02-21Conference Paper
Robust Epileptic Seizure Detection on Wearable Systems with Reduced False-Alarm Rate
Zanetti, Renato; Aminifar, Amir; Atienza Alonso, David
2020Publication funded by Hasler MyPreHealth (Predicting Episodic Disorders with Health Companions)
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
2020IEEE Transactions on Emerging Topics in ComputingPublication funded by Hasler MyPreHealth (Predicting Episodic Disorders with Health Companions)Publication funded by SNF ML-edge (ML-edge: Enabling Machine-Learning-Based Health Monitoring in Edge Sensors via Architectural Customization)
Multi-Modal Acute Stress Recognition Using Off-the-Shelf Wearable Devices
Montesinos, Victoriano; Dell'Agnola, Fabio; Arza, Adriana; Aminifar, Amir; Atienza, David
2019-01-012019 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
2018-08IEEE Transactions on Biomedical Circuits and SystemsPublication funded by Nano-Tera ()Publication funded by Hasler MyPreHealth (Predicting Episodic Disorders with Health Companions)
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
2018IEEE Transactions on Biomedical Circuits and SystemsPublication funded by Hasler MyPreHealth (Predicting Episodic Disorders with Health Companions)