TinyML

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

AMLD Intelligence Summit 2026 – Pushing Biosignal FMs to the Edge

Poster presentation of our full-stack framework for deploying biosignal foundation models on ultra-low-power edge devices at AMLD 2026 in Lausanne.

10 Feb 2026 SwissTech Convention Center, EPFL, Lausanne, Switzerland

AMLD Intelligence Summit 2026 – Pushing Biosignal FMs to the Edge

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

BioFoundation: Foundation Models for Biosignals

Open-source framework powering LUNA, FEMBA, CEReBrO, and other EEG foundation models — including LUNA, accepted at NeurIPS 2025.

12 mJ per Class On-Device Online Few-Shot Class-Incremental Learning

On-device online few-shot class-incremental learning at 12 mJ per class for extreme-edge systems.

Yoga Esa Wibowo, Cristian Cioflan, Thorir Mar Ingolfsson, Michael Hersche, Leo Zhao, Abbas Rahimi, Luca Benini

IEEE BioCAS 2023

Oral presentation of EpiDeNet and poster presentation of SkiLog at IEEE BioCAS 2023.

19 Oct 2023 Beanfield Centre, Toronto, Canada

IEEE BioCAS 2023