foundation model

Evaluation of EEG Foundation Models for Event-Based Burst-Suppression Detection in ICU

First evaluation of EEG foundation models for burst-suppression detection in ICU monitoring.

Elisa Vasta, Thorir Mar Ingolfsson, Andrea Cossettini, Luca Benini, Tilman Beck, Emanuela Keller, Una Pale

PanLUNA: An Efficient and Robust Query-Unified Multimodal Model for Edge Biosignal Intelligence

5.4M-parameter multimodal biosignal foundation model (EEG/ECG/PPG) deployable on a RISC-V microcontroller.

Marija Zelic, Anna Tegon, Yawei Li, Thorir Mar Ingolfsson, Luca Benini

PanLUNA: An Efficient and Robust Query-Unified Multimodal Model for Edge Biosignal Intelligence

LuMamba: Latent Unified Mamba for Electrode Topology-Invariant and Efficient EEG Modeling

Topology-invariant, linear-complexity EEG foundation model; first systematic study of LeJEPA for biosignals.

Danaé Broustail, Anna Tegon, Thorir Mar Ingolfsson, Yawei Li, Luca Benini

LuMamba: Latent Unified Mamba for Electrode Topology-Invariant and Efficient EEG Modeling

FEMBA on the Edge: Physiologically-Aware Pre-Training, Quantization, and Deployment of a Bidirectional Mamba EEG Foundation Model on an Ultra-Low Power Microcontroller

Physiologically-aware pre-training and INT8 deployment of a bidirectional Mamba EEG foundation model on a microcontroller.

Anna Tegon, Nicholas Lehmann, Yawei Li, Andrea Cossettini, Luca Benini, Thorir Mar Ingolfsson

FEMBA on the Edge: Physiologically-Aware Pre-Training, Quantization, and Deployment of a Bidirectional Mamba EEG Foundation Model on an Ultra-Low Power Microcontroller

TinyMyo: A Tiny Foundation Model for Flexible EMG Signal Processing at the Edge

3.6M-parameter EMG foundation model, first of its kind deployed on an ultra-low-power microcontroller.

Matteo Fasulo, Giusy Spacone, Thorir Mar Ingolfsson, Yawei Li, Luca Benini, Andrea Cossettini

TinyMyo: A Tiny Foundation Model for Flexible EMG Signal Processing at the Edge

LUNA: Efficient and Topology-Agnostic Foundation Model for EEG Signal Analysis

Topology-agnostic EEG foundation model that delivers state-of-the-art performance with 300× fewer FLOPs and 10× lower memory usage.

Berkay Döner, Thorir Mar Ingolfsson, Luca Benini, Yawei Li

LUNA: Efficient and Topology-Agnostic Foundation Model for EEG Signal Analysis

FEMBA: Efficient and Scalable EEG Analysis with a Bidirectional Mamba Foundation Model

Bidirectional Mamba EEG foundation model that matches transformer accuracy while scaling linearly with sequence length.

Anna Tegon, Thorir Mar Ingolfsson, Xiaying Wang, Luca Benini, Yawei Li

FEMBA: Efficient and Scalable EEG Analysis with a Bidirectional Mamba Foundation Model

CEReBrO: Compact Encoder for Representations of Brain Oscillations Using Efficient Alternating Attention

Alternating-attention EEG foundation model pre-trained on 20k+ hours that doubles speed and cuts memory by 6× versus standard transformers.

Alexandru Dimofte, Glenn Anta Bucagu, Thorir Mar Ingolfsson, Xiaying Wang, Andrea Cossettini, Luca Benini, Yawei Li

BISeizuRe: BERT-Inspired Seizure Data Representation to Improve Epilepsy Monitoring

BERT-inspired EEG encoder that cuts seizure-detection false positives to 0.23 FP/h after subject-specific tuning.

Luca Benfenati, Thorir Mar Ingolfsson, Andrea Cossettini, Daniele Jahier Pagliari, Alessio Burrello, Luca Benini