24 citations · 74 across the 15 of their papers we have counts for
5 papers · 1 filter
Energy-Efficient Tree-Based EEG Artifact Detection
Thorir Mar Ingolfsson, Andrea Cossettini, Simone Benatti +1
In the context of epilepsy monitoring, EEG artifacts are often mistaken for seizures due to their morphological similarity in both amplitude and frequency, making seizure detection…
Robust and Energy-efficient PPG-based Heart-Rate Monitoring
Matteo Risso, Alessio Burrello, Daniele Jahier Pagliari +4
A wrist-worn PPG sensor coupled with a lightweight algorithm can run on a MCU to enable non-invasive and comfortable monitoring, but ensuring robust PPG-based heart-rate monitoring…
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)…