Uploaded July 2025 | Updated September 2026, 1 day ago
Can EEG and artificial intelligence help detect dementia before symptoms become severe?
In this MindCare project webinar, experts from the Austrian Institute of Technology, Symptoma, and g.tec medical engineering present a European Union-funded approach for early dementia detection using EEG, artificial intelligence, decision support software, and clinical neurotechnology.
The session explains how dementia and mild cognitive impairment affect brain activity, including changes in alpha rhythm, increased theta and delta activity, altered functional connectivity, and general slowing of the EEG. These neural patterns are difficult to interpret on an individual level, which is why the project uses AI-driven EEG analysis, deep learning, transfer learning, explainable AI, and automated biomarker detection.
The MindCare algorithm analyzes resting-state EEG data to identify signs of cognitive decline and dementia risk. By using transfer learning from large sleep EEG datasets, the system can improve model training despite the limited availability of clinically labeled dementia EEG data. Explainable AI methods are used to highlight EEG regions and patterns that may represent new biomarkers for early-stage dementia and mild cognitive impairment.
The webinar also presents a clinical decision support workflow developed with Symptoma. By combining EEG biomarkers, cognitive testing, patient symptoms, risk factors, and medical knowledge from thousands of diseases, the system supports clinicians in identifying patients who may benefit from further dementia assessment.
g.tec contributes the EEG hardware platform for the MindCare project, including a wearable headset designed for long-term EEG acquisition, clinical usability, home-based measurements, sleep recordings, and high-quality brain signal analysis. The hardware includes long battery life, exchangeable electrodes, plug-and-play amplifier modules, active electrode technology, and signal quality monitoring for reliable EEG recordings outside traditional laboratory settings.
This project demonstrates how g.tec neurotechnology supports the complete workflow from EEG acquisition and real-time brain signal processing to AI-based neural decoding, clinical decision support, biomarker discovery, and translational neuroscience. It highlights the potential of EEG, Brain-Computer Interfaces, artificial intelligence, machine learning, dementia diagnostics, cognitive assessment, clinical neuroscience, digital health, precision medicine, and home-based neurotechnology for the future of early dementia detection.
More about g.tec Neurotechnology: https://www.gtec.at/
Can EEG and artificial intelligence help detect dementia before symptoms become severe?
In this MindCare project webinar, experts from the Austrian Institute of Technology, Symptoma, and g.tec medical engineering present a European Union-funded approach for early dementia detection using EEG, artificial intelligence, decision support software, and clinical neurotechnology.
The session explains how dementia and mild cognitive impairment affect brain activity, including changes in alpha rhythm, increased theta and delta activity, altered functional connectivity, and general slowing of the EEG. These neural patterns are difficult to interpret on an individual level, which is why the project uses AI-driven EEG analysis, deep learning, transfer learning, explainable AI, and automated biomarker detection.
The MindCare algorithm analyzes resting-state EEG data to identify signs of cognitive decline and dementia risk. By using transfer learning from large sleep EEG datasets, the system can improve model training despite the limited availability of clinically labeled dementia EEG data. Explainable AI methods are used to highlight EEG regions and patterns that may represent new biomarkers for early-stage dementia and mild cognitive impairment.
The webinar also presents a clinical decision support workflow developed with Symptoma. By combining EEG biomarkers, cognitive testing, patient symptoms, risk factors, and medical knowledge from thousands of diseases, the system supports clinicians in identifying patients who may benefit from further dementia assessment.
g.tec contributes the EEG hardware platform for the MindCare project, including a wearable headset designed for long-term EEG acquisition, clinical usability, home-based measurements, sleep recordings, and high-quality brain signal analysis. The hardware includes long battery life, exchangeable electrodes, plug-and-play amplifier modules, active electrode technology, and signal quality monitoring for reliable EEG recordings outside traditional laboratory settings.
This project demonstrates how g.tec neurotechnology supports the complete workflow from EEG acquisition and real-time brain signal processing to AI-based neural decoding, clinical decision support, biomarker discovery, and translational neuroscience. It highlights the potential of EEG, Brain-Computer Interfaces, artificial intelligence, machine learning, dementia diagnostics, cognitive assessment, clinical neuroscience, digital health, precision medicine, and home-based neurotechnology for the future of early dementia detection.
More about g.tec Neurotechnology: https://www.gtec.at/
