1

Minimizing artifact-induced false-alarms for seizure detection in wearable EEG devices with gradient-boosted tree classifiers
The paper presents a combined seizure and artifact detection framework based on Gradient Boosted Trees. The framework achieves high accuracy in detecting seizures and artifacts, reducing false alarms. The algorithms are optimized for a Parallel Ultra-Low Power platform, enabling extended monitoring with a long battery lifespan. The paper highlights the benefits of integrating artifact detection in wearable epilepsy monitoring devices.
Thorir Mar Ingolfsson, Simone Benatti, Xiaying Wang, Adriano Bernini, Pauline Ducouret, Philippe Ryvlin, Sandor Beniczky, Luca Benini, Andrea Cossettini
PDF Cite
Minimizing artifact-induced false-alarms for seizure detection in wearable EEG devices with gradient-boosted tree classifiers
Energy-Efficient Tree-Based EEG Artifact Detection
In this paper, we present implementations of energy-efficient artifact detection algorithms on a parallel ultra-low power platform.
Thorir Mar Ingolfsson, Andrea Cossettini, Simone Benatti, Luca Benini
PDF Cite
Energy-Efficient Tree-Based EEG Artifact Detection
Reducing Neural Architecture Search Spaces with Training-Free Statistics and Computational Graph Clustering
In this paper, we present Clustering-Based REDuction (C-BRED), a new technique to reduce the size of NAS search spaces.
Thorir Mar Ingolfsson, Mark Vero, Xiaying Wang, Lorenzo Lamberti, Luca Benini, Matteo Spallanzani
PDF Cite
Reducing Neural Architecture Search Spaces with Training-Free Statistics and Computational Graph Clustering
Towards Long-term Non-invasive Monitoring for Epilepsy via Wearable EEG Devices
In this paper, we present implementations of seizure detection algorithms on a parallel ultra-low power platform.
Thorir Mar Ingolfsson, Andrea Cossettini, Xiaying Wang, Enrico Tabanelli, Giuseppe Tagliavini, Philippe Ryvlin, Luca Benini, Simone Benatti
PDF Cite
Towards Long-term Non-invasive Monitoring for Epilepsy via Wearable EEG Devices
ECG-TCN: Wearable Cardiac Arrhythmia Detection with a Temporal Convolutional Network
In this paper, we propose ECG-TCN, a novel temporal convolutional network (TCN) that achieves outstanding accuracy while requiring few trainable parameters.
Thorir Mar Ingolfsson, Xiaying Wang, Michael Hersche, Alessio Burrello, Lukas Cavigelli, Luca Benini
PDF Cite DOI
ECG-TCN: Wearable Cardiac Arrhythmia Detection with a Temporal Convolutional Network
EEG-TCNet: An Accurate Temporal Convolutional Network for Embedded Motor-Imagery Brain–Machine Interfaces
In this paper, we propose EEG-TCNet, a novel temporal convolutional network (TCN) that achieves outstanding accuracy while requiring few trainable parameters.
Thorir Mar Ingolfsson, Michael Hersche, Xiaying Wang, Nobuaki Kobayashi, Lukas Cavigelli, Luca Benini
PDF Cite DOI
EEG-TCNet: An Accurate Temporal Convolutional Network for Embedded Motor-Imagery Brain–Machine Interfaces