Advancing Neurological Care Through Novel Sensing Pipelines for Detection and Intervention
Published:
Abstract
This presentation provides an overview of my research program focused on developing novel sensing technologies and AI-driven analytics for neurological and developmental disorders. I discuss our multi-modal approach to biomarker discovery that combines wearable sensors, environmental monitoring, and privacy-preserving edge computing to identify early indicators of cognitive decline and behavioral challenges. The talk emphasizes the translation of these technologies into practical clinical applications that can improve patient outcomes through early detection and personalized intervention strategies.
Research Areas Highlighted
- In-ear EEG and multimodal sensing for cognitive impairment detection
- Privacy-preserving computing architectures for vulnerable populations
- Explainable AI approaches for clinical decision support
- Implementation challenges and solutions in real-world healthcare settings
- Ethical considerations in AI-driven healthcare technologies
Future Directions
The presentation concludes with a discussion of future research directions, including the development of closed-loop intervention systems that can adapt to individual patient needs in real-time, expansion of sensing modalities, and broader applications across different neurological conditions.