52 citations · 267 across the 37 of their papers we have counts for
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EnhancePPG: Improving PPG-based Heart Rate Estimation with Self-Supervision and Augmentation
Luca Benfenati, Sofia Belloni, Alessio Burrello +6
Heart rate (HR) estimation from photoplethysmography (PPG) signals is a key feature of modern wearable devices for health and wellness monitoring. While deep learning models show p…
Optimization and Deployment of Deep Neural Networks for PPG-based Blood Pressure Estimation Targeting Low-power Wearables
Alessio Burrello, Francesco Carlucci, Giovanni Pollo +5
PPG-based Blood Pressure (BP) estimation is a challenging biosignal processing task for low-power devices such as wearables. State-of-the-art Deep Neural Networks (DNNs) trained fo…
Model-Driven Dataset Generation for Data-Driven Battery SOH Models
Khaled Sidahmed Sidahmed Alamin, Francesco Daghero, Giovanni Pollo +5
Estimating the State of Health (SOH) of batteries is crucial for ensuring the reliable operation of battery systems. Since there is no practical way to instantaneously measure it a…
Energy-efficient Wearable-to-Mobile Offload of ML Inference for PPG-based Heart-Rate Estimation
Alessio Burrello, Matteo Risso, Noemi Tomasello +5
Modern smartwatches often include photoplethysmographic (PPG) sensors to measure heartbeats or blood pressure through complex algorithms that fuse PPG data with other signals. In t…
Two-stage Human Activity Recognition on Microcontrollers with Decision Trees and CNNs
Francesco Daghero, Daniele Jahier Pagliari, Massimo Poncino
Human Activity Recognition (HAR) has become an increasingly popular task for embedded devices such as smartwatches. Most HAR systems for ultra-low power devices are based on classi…
Bioformers: Embedding Transformers for Ultra-Low Power sEMG-based Gesture Recognition
Alessio Burrello, Francesco Bianco Morghet, Moritz Scherer +5
Human-machine interaction is gaining traction in rehabilitation tasks, such as controlling prosthetic hands or robotic arms. Gesture recognition exploiting surface electromyographi…
Q-PPG: Energy-Efficient PPG-based Heart Rate Monitoring on Wearable Devices
Alessio Burrello, Daniele Jahier Pagliari, Matteo Risso +4
Hearth Rate (HR) monitoring is increasingly performed in wrist-worn devices using low-cost photoplethysmography (PPG) sensors. However, Motion Artifacts (MAs) caused by movements o…
Embedding Temporal Convolutional Networks for Energy-Efficient PPG-Based Heart Rate Monitoring
Alessio Burrello, Daniele Jahier Pagliari, Pierangelo Maria Rapa +6
Photoplethysmography (PPG) sensors allow for non-invasive and comfortable heart-rate (HR) monitoring, suitable for compact wrist-worn devices. Unfortunately, Motion Artifacts (MAs)…