Enabling Unobtrusive Real-World Monitoring of Brain-Networks with Wearable Neurotechnology and Multimodal Machine Learning
The INTEGRAL project aims to develop a hybrid wearable platform combining HD-DOT and EEG for continuous brain network imaging in everyday environments, enhancing neurotechnology research and applications.
Projectdetails
Introduction
Measuring and linking brain network activity to human physiology and behavior in natural everyday situations promises profound new insights into healthy brain function and disorders. However, the absence of suitable mobile neurotechnology presents a significant roadblock.
Limitations of Current Technologies
Functional magnetic resonance imaging (fMRI) has greatly advanced our understanding of brain function and networks, but it is limited to single-snapshot experiments in constrained lab settings. Electroencephalography (EEG), while mobile, cannot directly be linked to brain networks captured by fMRI.
Need for a Hybrid Wearable Platform
To overcome these roadblocks and to advance neuro-inspired treatments and discoveries to natural environments, a hybrid wearable platform is required that combines innovations in hardware and analysis methods. This platform should enable continuous and stable measurements of brain network activity maps in the everyday world.
Advancing HD-DOT
Advancing high-density diffuse optical tomography (HD-DOT) can provide a suitable alternative to fMRI. With a unique systems engineering concept, INTEGRAL aims to miniaturize and integrate DOT, EEG, and physiological sensors with advanced multimodal machine learning to improve spatio-temporal contrast in mobile brain imaging.
Project Objectives
- Objective 1 (Instruments): Develop hardware for unobtrusive and continuous wearable brain-body imaging with HD-DOT-EEG.
- Objective 2 (Experiments): Collect extensive multimodal data for measuring brain networks while controlling for environmental and physiological artifacts.
- Objective 3 (Analysis): Enable estimation of brain network activity with multimodal sensor fusion and machine learning.
- Objective 4 (Integration): Provide validation of robust brain-networks imaging in ecologically valid everyday world environments.
Potential Impact
If successful, this new platform will provide unprecedented opportunities to study brain function with global impact on neurotechnology applications and research, ranging from the Neuroscience of the Everyday World to digital health.
Financiële details & Tijdlijn
Financiële details
Subsidiebedrag | € 1.654.850 |
Totale projectbegroting | € 1.654.850 |
Tijdlijn
Startdatum | 1-1-2025 |
Einddatum | 31-12-2029 |
Subsidiejaar | 2025 |
Partners & Locaties
Projectpartners
- TECHNISCHE UNIVERSITAT BERLINpenvoerder
Land(en)
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