42 citations · 49 across the 22 of their papers we have counts for
29 papers
Open-Source Multi-Wire SPI Readout for Wearable Ultrasound Probes
Federico Villani, Soumyo Bhattacharjee, Lisa Odermatt +3
Wearable ultrasound probes must transfer increasingly large acquisition payloads while maintaining compact, low-power electronics. In TinyProbe, the current bottleneck in data tran…
U-Sonic: An Open-Source 8-Channel Ultrasound Transmit IP in a 130 nm RISC-V SoC
Federico Villani, Nico Canzani, Marc-André Wessner +5
Miniaturized ultrasound (US) probes require programmable and synchronized transmit (TX) excitation across multiple elements, while existing compact platforms often rely on limited…
Open-Source Live-Reconfigurable Multi-Mode Wearable Ultrasound
Cédric Hirschi, Federico Villani, Luca Benini +1
Wearable ultrasound enables continuous deep-tissue monitoring, and a single programmable probe can operate in multiple complementary modes, such as structural A-mode and Doppler fl…
WULPUS PRO: Multi-mode Ultra-Low-Power Wearable Ultrasound and Array Imaging with CMUT Support
Sergei Vostrikov, Federico Villani, Cedric Hirschi +7
Wearable ultrasound enables continuous monitoring of physiological processes such as muscle dynamics, bladder volume, and cardiovascular activity. Existing fully wearable ultra-low…
Towards Whole Hand and Wrist Kinematic Tracking with a Wearable A-Mode Ultrasound Probe
Giusy Spacone, Luca Benini, Andrea Cossettini
A-mode ultrasound (US) has emerged as a promising modality for hand and wrist motion tracking. Prior works have mainly addressed static gesture classification or regression of a fe…
Evaluation of EEG Foundation Models for Event-Based Burst-Suppression Detection in ICU
Elisa Vasta, Thorir Mar Ingolfsson, Andrea Cossettini +4
Burst suppression (BS) is a clinically relevant electroencephalographic (EEG) pattern used to monitor sedation depth and brain activity in critically ill patients, particularly dur…
A Wearable Multimodal Ultrasound+Inertial System for Real-Time Virtual Reality Interaction
Giusy Spacone, Sebastian Frey, Enzo Baraldi +3
A-mode ultrasound (US) is a promising sensing modality for Virtual Reality (VR) interaction, as it enables the mapping of muscular activity into control commands while retaining th…
Polymer-based Capacitive Micromachined Transducer-Enabled Inline Monitoring of Ultrasonic Welding in Thermoplastic Carbon Fiber Composites
Jonas Welsch, Dominik Goerick, Martin Angerer +8
Thermoplastic composite structures enable lightweight, recyclable, and high-throughput aerospace manufacturing, but reliable quality assurance of advanced joining processes remains…
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…
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…
Validation of a Software-Defined 100-Gb/s RDMA Streaming Architecture for Ultrafast Optoacoustic and Ultrasound Imaging
Federico Villani, Christian Vogt, Luca Specht +5
Optoacoustic (OA) imaging has emerged as a powerful investigation tool, with demonstrated applicability in oncology, neuroscience, and cardiovascular biology. However, its clinical…
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…
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…
A Parallel Ultra-Low Power Silent Speech Interface based on a Wearable, Fully-dry EMG Neckband
Fiona Meier, Giusy Spacone, Sebastian Frey +2
We present a wearable, fully-dry, and ultra-low power EMG system for silent speech recognition, integrated into a textile neckband to enable comfortable, non-intrusive use. The sys…
ListenToJESD204B: A Lightweight Open-Source JESD204B IP Core for FPGA-Based Ultrasound Acquisition systems
Soumyo Bhattacharjee, Federico Villani, Christian Vogt +2
The demand for hundreds of tightly synchronized channels operating at tens of MSPS in ultrasound systems exceeds conventional low-voltage differential signaling links' bandwidth, p…
BioGAP-Ultra: A Modular Edge-AI Platform for Wearable Multimodal Biosignal Acquisition and Processing
Sebastian Frey, Giusy Spacone, Andrea Cossettini +4
The growing demand for continuous physiological monitoring and human-machine interaction in real-world settings calls for wearable platforms that are flexible, low-power, and capab…
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…
CEReBrO: Compact Encoder for Representations of Brain Oscillations Using Efficient Alternating Attention
Alexandru Dimofte, Glenn Anta Bucagu, Thorir Mar Ingolfsson +4
Electroencephalograph (EEG) is a crucial tool for studying brain activity. Recently, self-supervised learning methods leveraging large unlabeled datasets have emerged as a potentia…
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…
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)…
BISeizuRe: BERT-Inspired Seizure Data Representation to Improve Epilepsy Monitoring
Luca Benfenati, Thorir Mar Ingolfsson, Andrea Cossettini +3
This study presents a novel approach for EEG-based seizure detection leveraging a BERT-based model. The model, BENDR, undergoes a two-phase training process. Initially, it is pre-t…
GAPses: Versatile smart glasses for comfortable and fully-dry acquisition and parallel ultra-low-power processing of EEG and EOG
Sebastian Frey, Mattia Alberto Lucchini, Victor Kartsch +7
Recent advancements in head-mounted wearable technology are revolutionizing the field of biopotential measurement, but the integration of these technologies into practical, user-fr…
SzCORE: A Seizure Community Open-source Research Evaluation framework for the validation of EEG-based automated seizure detection algorithms
Jonathan Dan, Una Pale, Alireza Amirshahi +9
The need for high-quality automated seizure detection algorithms based on electroencephalography (EEG) becomes ever more pressing with the increasing use of ambulatory and long-ter…
A Wearable Ultra-Low-Power sEMG-Triggered Ultrasound System for Long-Term Muscle Activity Monitoring
Sebastian Frey, Victor Kartsch, Christoph Leitner +4
Surface electromyography (sEMG) is a well-established approach to monitor muscular activity on wearable and resource-constrained devices. However, when measuring deeper muscles, it…