Health and wellness monitoring

In the last decade, remote health monitoring is becoming an essential branch of healthcare with the rapid development of wearable platforms thanks to the progress of manufacturing process technology. Wearable architectures are rapidly evolving into multicore systems with advanced power-saving capabilities and additional heterogeneous components to meet the demand for new and more complex applications. They currently include multiple machine learning algorithms in the edge artificial intelligence (AI) context. Still, their designs need to ensure a good battery life to be relevant in the Internet of Things (IoT) context.

In this project, we are developing new approaches to design the next generation of ultra-low power (ULP) wearable architectures for personalized health and wellness monitoring. This research includes the design of new ULP multicore architectures, and related power management approaches at the system level. Also, we study how to apply optimization techniques in the software layers of biomedical applications to improve performance and reducing system energy consumption.

Finally, we also investigate in collaboration with industrial partners the benefits of integrating domain-specific accelerators and designing new memory hierarchies in the latest technology nodes. These optimizations aim to reduce the energy consumption of the most computationally expensive kernels in the latest AI-based biomedical algorithms and healthcare applications in the IoT context.

Related Publications

An Open-Hardware Coarse-Grained Reconfigurable Array for Edge Computing
Rodríguez Álvarez, Rubén; Denkinger, Benoît Walter; Sapriza, Juan; Miranda Calero, José Angel; Ansaloni, Giovanni; Atienza Alonso, David
2023-04-25	Conference Paper
Acceleration of Control Intensive Applications on Coarse-Grained Reconfigurable Arrays for Embedded Systems
Denkinger, Benoît Walter; Peon Quiros, Miguel; Konijnenburg, Mario; Atienza Alonso, David; Catthoor, Francky
2023-03-17	Transactions on Computers
ExG Signal Feature Selection Using Hyperdimensional Computing Encoding
Pale, Una; Teijeiro, Tomas; Atienza, David
2022-12-08	2022 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)
Approximate Zero-Crossing: A new interpretable, highly discriminative and low-complexity feature for EEG and iEEG seizure detection
Zanetti, R; Pale, U; Teijeiro, T; Atienza Alonso, David
2022-11-10	Journal of Neural Engineering
VWR2A: A Very-Wide-Register Reconfigurable-Array Architecture for Low-Power Embedded Devices
Denkinger, Benoît Walter; Peon Quiros, Miguel; Konijnenburg, Mario; Atienza Alonso, David; Catthoor, Francky
2022	Conference Paper
SPARE: A Spectral Peak Recovery Algorithm for PPG Signals Pulsewave Reconstruction in Multimodal Wearable Devices
Masinelli, Giulio; Dell'Agnola, Fabio Isidoro Tiberio; Arza Valdes, Adriana; Atienza Alonso, David
2021-04-13	Conference Paper
Real-Time EEG-Based Cognitive Workload Monitoring on Wearable Devices
Zanetti, Renato; Arza Valdes, Adriana; Aminifar, Amir; Atienza Alonso, David
2021	IEEE Transactions on Biomedical Engineering (TBME)
Towards Continuous and Ambulatory Blood Pressure Monitoring: Methods for Efficient Data Acquisition for Pulse Transit Time Estimation
Ode, Oludotun; Orlandic, Lara; Inan, Omer T.
2020-12-11	Sensors
Analysis of Functional Errors Produced by Long-Term Workload-Dependent BTI Degradation in Ultra-Low Power Processors
Duch, Loris; Peón-Quirós, Miguel; Weckx, Pieter; Levisse, Alexandre Sébastien Julien; Braojos Lopez, Ruben; Catthoor, Francky; Atienza Alonso, David
2020-06-09	IEEE Transactions on Very Large Scale Integration Systems
Robust Epileptic Seizure Detection on Wearable Systems with Reduced False-Alarm Rate
Zanetti, Renato; Aminifar, Amir; Atienza Alonso, David
2020
Modular Design and Optimization of Biomedical Applications for Ultra-Low Power Heterogeneous Platforms
De Giovanni, Elisabetta; Montagna, Fabio; Denkinger, Benoît Walter; Machetti, Simone; Peon Quiros, Miguel; Benatti, Simone; Rossi, Davide; Benini, Luca; Atienza Alonso, David
2020	[Proceedings of CODES+ISSS 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
Pattern recognition in non-uniformly sampled electrocardiogram signal for wearable sensors
Silvio Zanolli, sup. Tomas Teijeiro, David Atienza
2019-07-10	Masters Thesis