Signal processing, machine learning and physiological modeling to reduce costs, increase accuracy and improve access in healthcare using enormous high frequency, multivariate data streams. Theoretical techniques focus on building confidence intervals and trust metrics for predictive algorithms and scaling analysis of medical data beyond conventional clinical capacity.
Main application areas include:
- Critical Care
- Sleep & Circadian Rhythms
- Perinatal Monitoring
- Resource-Constrained Environments (such as developing countries)