activity
20242026
most citedAn Ultra-Low Power Wearable BMI System with Continual Learning Capabilities

5 citations · 6 across the 8 of their papers we have counts for

collaborators
Showing eess.SPShow all

6 papers · 1 filter

eess.SP2026

SilentWear: an Ultra-Low Power Wearable System for EMG-based Silent Speech Recognition

Giusy Spacone, Sebastian Frey, Giovanni Pollo +5

Detecting speech from biosignals is gaining increasing attention due to the potential to develop human-computer interfaces that are noise-robust, privacy-preserving, and scalable f…

eess.SP2025

Wearable and Ultra-Low-Power Fusion of EMG and A-Mode US for Hand-Wrist Kinematic Tracking

Giusy Spacone, Sebastian Frey, Mattia Orlandi +5

Hand gesture recognition based on biosignals has shown strong potential for developing intuitive human-machine interaction strategies that closely mimic natural human behavior. In…

eess.SP2025

Real-Time, Single-Ear, Wearable ECG Reconstruction, R-Peak Detection, and HR/HRV Monitoring

Carlos Santos, Sebastian Frey, Andrea Cossettini +2

Biosignal monitoring, in particular heart activity through heart rate (HR) and heart rate variability (HRV) tracking, is vital in enabling continuous, non-invasive tracking of phys…

eess.SP2024

Train-On-Request: An On-Device Continual Learning Workflow for Adaptive Real-World Brain Machine Interfaces

Lan Mei, Cristian Cioflan, Thorir Mar Ingolfsson +4

Brain-machine interfaces (BMIs) are expanding beyond clinical settings thanks to advances in hardware and algorithms. However, they still face challenges in user-friendliness and s…

eess.SP20245 cited

An Ultra-Low Power Wearable BMI System with Continual Learning Capabilities

Lan Mei, Thorir Mar Ingolfsson, Cristian Cioflan +4

Driven by the progress in efficient embedded processing, there is an accelerating trend toward running machine learning models directly on wearable Brain-Machine Interfaces (BMIs)…

eess.SP20241 cited

A Spiking Neural Network Decoder for Implantable Brain Machine Interfaces and its Sparsity-aware Deployment on RISC-V Microcontrollers

Jiawei Liao, Oscar Toomey, Xiaying Wang +4

Implantable Brain-machine interfaces (BMIs) are promising for motor rehabilitation and mobility augmentation, and they demand accurate and energy-efficient algorithms. In this pape…