From the 1 of 28 linked papers with an AI index.
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FEMBA on the Edge: Physiologically-Aware Pre-Training, Quantization, and Deployment of a Bidirectional Mamba EEG Foundation Model on an Ultra-low Power Microcontroller
Anna Tegon, Nicholas Lehmann, Yawei Li +3
Objective: To enable continuous, long-term neuro-monitoring on wearable devices by overcoming the computational bottlenecks of Transformer-based Electroencephalography (EEG) founda…
TinyMyo: a Tiny Foundation Model for Flexible EMG Signal Processing at the Edge
Matteo Fasulo, Giusy Spacone, Thorir Mar Ingolfsson +3
Objective: Surface electromyography (EMG) is a non-invasive sensing modality widely used in biomechanics, rehabilitation, prosthetic control, and human-machine interfaces. Despite…
A Compute&Memory Efficient Model-Driven Neural 5G Receiver for Edge AI-assisted RAN
Mahdi Abdollahpour, Marco Bertuletti, Yichao Zhang +3
Artificial intelligence approaches for base-band processing for radio receivers have demonstrated significant performance gains. Most of the proposed methods are characterized by h…
Finetuning and Quantization of EEG-Based Foundational BioSignal Models on ECG and PPG Data for Blood Pressure Estimation
Bálint Tóth, Dominik Senti, Thorir Mar Ingolfsson +4
Blood pressure (BP) is a key indicator of cardiovascular health. As hypertension remains a global cause of morbidity and mortality, accurate, continuous, and non-invasive BP monito…