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Closed-loop noninvasive brain stimulation as a treatment for Alzheimer's Disease
PD Dr. Julian KeilDone
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Decoding Social Touch: EEG Signals Reveal Interdependent Somatosensory Pathways Relevant to Human Affect
Prof. Dr. Annett SchirmerDone
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Pushing the Boundaries of Human Space Exploration: Implications for Brain and Behavioral Adaptations
Prof. Dr. Alexander StahnDone
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📣
Done
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🚀✨🎉
Done
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EEG Cloud Clinical Service to proactively objectify diagnoses for Neurodegenerative Pathologies and Disorders Therapy
MSc. Daniel MoreraDone
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✅
Done
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Functional connectivity analysis using dry electrodes
Prof. Dr. Patrique FiedlerDone
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🥗
Done
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📣
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Jurij Dreo is a neuroscientist and entrepreneur, specializing in electrophysiological markers of cognitive decline and neurodegenerative diseases. After studying medicine at the University of Ljubljana, Slovenia, he developed extensive expertise in neurophysiological data acquisition and analysis, focusing on EEG, EMG, and TMS. His research work at the Clinical Institute for Clinical Neurophysiology and later the Laboratory for Cognitive Neuroscience in Ljubljana provided a foundation for his innovative work in EEG analysis.
In 2019, he co-founded BrainTrip Limited, where he serves as Chief Technology Officer. BrainTrip has developed a pioneering, non-invasive EEG-based dementia screening tool, blending years of research with advanced technology to address critical challenges in healthcare. He has authored several peer-reviewed publications, contributed to multimodal research projects, and presented scientific findings at leading international conferences, including the Society for Neuroscience. His work bridges academic rigor and applied science, demonstrating a commitment to transforming neuroscience into practical solutions.
EEG is poised to transform clinical brain diagnostics by offering a reliable, affordable, and portable alternative to traditional methods. While advancements in EEG technology have addressed hardware limitations, enabling high-quality recordings at reduced costs, three critical barriers remain: 1) scalable recording, 2) cleaning/processing, and 3) interpretation of EEG data. This talk introduces the NeuroAI platform, a cloud-enabled software solution designed to overcome these challenges and help expand EEG’s role in brain diagnostics.
The NeuroAI platform vertically integrates with existing EEG hardware to ensure seamless application in diverse environments. It features machine-assisted EEG recording, which requires only 4 hours of user training, significantly reducing the steep learning curve associated with traditional EEG methods. The automated preprocessing pipeline (APE) eliminates the need for manual intervention by utilizing state-of-the-art algorithms to identify and clean common artifacts. This cloud-based system ensures scalability without dependence on local computational resources.
Additionally, the NeuroAI platform revolutionizes EEG interpretation through an advanced inference engine. It analyzes millions of potential biomarkers, selecting and synthesizing the most predictive ones for specific diseases using robust statistics paired with artificial intelligence. By combining hundreds of biomarkers into a single metric, this approach enhances diagnostic accuracy and facilitates easy result interpretation. Unlike traditional EEG methods, which rely on visual inspection and are effective for only a narrow range of brain disorders, this automated system expands the diagnostic scope to a broader spectrum of brain diseases. This innovative integration of EEG and NeuroAI software enables rapid, scalable, and automated brain diagnostics, addressing critical barriers to widespread adoption. With its potential to improve human health and well-being, this technology represents a significant advancement in point-of-care neurological assessments.