Imagine a smart watch that doesn't just track your heart, but can predict a brain storm like a seizure before it happens. Once it detects a problem, it uses a tiny ultrasound patch to gently nudge a nerve in your neck to stop the seizure. It's like having a tiny, automatic doctor on your skin that learns your body's unique patterns to get better over time.
Current brain-disorder interventions often require invasive implants or lack real-time responsiveness. There is a gap for a non-invasive, wearable solution that can both predict and treat anomalies like seizures automatically.
A three-generation development path for a closed-loop system including a low-power AI for EEG monitoring and a wearable ultrasound vagus nerve stimulation (WU-VNS) patch.
If you are a wearable manufacturer dealing with the lack of non-invasive seizure intervention — this project developed a closed-loop system that monitors EEG and triggers ultrasound stimulation. This allows for a product that prevents episodes without needing brain implants.
If you are an AI developer dealing with high power consumption for real-time brain monitoring — this project developed low-computation algorithms that run on ordinary wearable devices. This enables real-time personalization of brain data monitoring without needing expensive hardware.
If you are a clinic dealing with chronic management of dementia or depression — this project developed the WU-VNS ultrasound patch. This provides a non-invasive way to interact with the vagus nerve to manage neurological disorders.
Based on available project data, there is no specific unit price or cost mentioned; however, the EU contribution for development is EUR 2,809,260.
The project aims to create a wearable patch and use ordinary wearable devices for AI, suggesting a design intended for mass-market scalability.
Based on available project data, specific patent or licensing details are not provided, though the project involves 9 partners across 6 countries developing new algorithmic tools and hardware.
The project period is from 2023-04-01 to 2026-09-30, spanning approximately 3.5 years.
The AI is designed to be runnable on ordinary wearable devices using EEG, heart rate, and motion data.
The consortium is heavily research-driven, consisting of 6 universities and 1 research organization, with only 1 industry partner (SME), resulting in an industry ratio of 11%. This suggests the project is focused on high-risk technological breakthroughs rather than immediate commercial rollout, though the inclusion of an SME indicates a path toward productization.
Masarykova univerzita (CZ)
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