Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

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

IEEE transactions on bio-medical engineering·2026
Same author

Current Trends in Ultrasound Wearables: Spotlight on System Architecture.

IEEE reviews in biomedical engineering·2026
Same author

Inkube: an all-in-one solution for neuron culturing, electrophysiology, and fluidic exchange.

Lab on a chip·2026
Same author

Finetuning and Quantization of EEG-Based Foundational BioSignal Models on ECG and PPG Data for Blood Pressure Estimation.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2025
Same author

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

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2025
Same author

Neural Strategies for Upper Limb Movements: Motor Unit Control during Dynamic Contractions at Increasing Speeds.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2025
Same journal

A VPG-Based Adaptive Windowing PPG Sensor IC for Low-Power Wearable Monitoring.

IEEE transactions on biomedical circuits and systems·2026
Same journal

A Chopper Amplifier with Feedforward SAR ADC Assisted DC Servo Loop Achieving ±1V DC Offset Cancellation in 2.1s for Neural Signal Recordings.

IEEE transactions on biomedical circuits and systems·2026
Same journal

ANP-R: A 22nm 0.88pJ/SOP Asynchronous SNN-based Processor with Coarse-Grained Reconfigurable Architecture Enabling Multisensory On-chip Incremental Learning for Edge AI.

IEEE transactions on biomedical circuits and systems·2026
Same journal

A High-Efficiency Neural Processing SoC for Adaptive Closed-Loop Neuromodulation.

IEEE transactions on biomedical circuits and systems·2026
Same journal

DustNet: A Wireless Network of Ultrasonic Neural Implants.

IEEE transactions on biomedical circuits and systems·2026
Same journal

An 820uW Low Jitter Digital Injection-Locked PLL Using Differential Multi-Phase Injection and Self-Calibration for Biosensing Applications.

IEEE transactions on biomedical circuits and systems·2026
See all related articles

Related Experiment Video

Updated: Jan 14, 2026

Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface
11:54

Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface

Published on: May 8, 2021

5.1K

BioGAP-Ultra: A Modular Edge-AI Platform for Wearable Multimodal Biosignal Acquisition and Processing.

Sebastian Frey, Giusy Spacone, Andrea Cossettini

    IEEE Transactions on Biomedical Circuits and Systems
    |January 12, 2026
    PubMed
    Summary
    This summary is machine-generated.

    BioGAP-Ultra is an advanced wearable biosensing platform for continuous physiological monitoring. It enables on-device AI processing of electrophysiological and hemodynamic signals with state-of-the-art energy efficiency.

    More Related Videos

    A Novel Digital Platform for a Monitored Home-based Cardiac Rehabilitation Program
    04:24

    A Novel Digital Platform for a Monitored Home-based Cardiac Rehabilitation Program

    Published on: April 19, 2019

    12.2K
    A Single-Channel and Non-Invasive Wearable Brain-Computer Interface for Industry and Healthcare
    06:34

    A Single-Channel and Non-Invasive Wearable Brain-Computer Interface for Industry and Healthcare

    Published on: July 7, 2023

    3.1K

    Related Experiment Videos

    Last Updated: Jan 14, 2026

    Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface
    11:54

    Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface

    Published on: May 8, 2021

    5.1K
    A Novel Digital Platform for a Monitored Home-based Cardiac Rehabilitation Program
    04:24

    A Novel Digital Platform for a Monitored Home-based Cardiac Rehabilitation Program

    Published on: April 19, 2019

    12.2K
    A Single-Channel and Non-Invasive Wearable Brain-Computer Interface for Industry and Healthcare
    06:34

    A Single-Channel and Non-Invasive Wearable Brain-Computer Interface for Industry and Healthcare

    Published on: July 7, 2023

    3.1K

    Area of Science:

    • Wearable technology
    • Biomedical engineering
    • Artificial intelligence in healthcare

    Background:

    • Growing demand for continuous physiological monitoring and human-machine interaction in real-world settings.
    • Need for flexible, low-power wearable platforms with on-device intelligence.
    • Limitations of existing wearable biosensing platforms in terms of storage, connectivity, and signal modality.

    Purpose of the Study:

    • To present BioGAP-Ultra, an advanced multimodal biosensing platform.
    • To enable synchronized acquisition of diverse electrophysiological and hemodynamic signals.
    • To achieve state-of-the-art energy efficiency for embedded AI processing on wearable devices.

    Main Methods:

    • Developed BioGAP-Ultra, an extension of the BioGAP design with increased storage, improved wireless connectivity, and enhanced signal modalities.
    • Integrated BioGAP-Ultra into various wearable form factors (headband, sleeve, chestband).
    • Deployed on-device AI applications for photoplethysmography (PPG) and electromyography (EMG) signal analysis.

    Main Results:

    • BioGAP-Ultra supports synchronized acquisition of EEG, EMG, ECG, and PPG signals.
    • Demonstrated low power consumption for continuous monitoring and AI processing across different form factors (e.g., 9.3 mW for ECG-PPG chestband).
    • Achieved high accuracy for on-device AI applications, such as EMG-based motion phase classification (79.9% ± 5.7% at 23.6 mW).

    Conclusions:

    • BioGAP-Ultra is a versatile and energy-efficient multimodal biosensing platform for advanced wearable applications.
    • The platform enables on-device AI processing for real-time physiological monitoring and human-machine interaction.
    • Open-source release of hardware and software facilitates further research and development in wearable biosensing.