Multi-Modal Approach for Fall Detection
This project aims to improve patient safety through a multi-modal fall detection system that integrates wearable sensors, camera-based monitoring, and large language models (LLMs). Designed to detect and prevent falls among older adults and individuals with mobility challenges, the system enhances accuracy while preserving privacy through selective camera activation and HIPAA-compliant safeguards. By combining real-time data, contextual analysis, and predictive insights, this innovative approach enables proactive fall prevention, reduces false alarms, and supports caregivers with timely, data-driven recommendations.
Pipelining future clinicians - An OR experience
This project will combine the talents of the Bradley Interactive Media faculty and students with the expertise of the OSF HealthCare STEAM team. The collaboration will result in an online platform designed to promote education and awareness about healthcare careers.
SurgiSense: Transforming OR Scheduling for Smarter Healthcare Delivery
This project aims to improve efficiency and patient outcomes across the OSF HealthCare network through an intelligent, data-driven operating room (OR) scheduling system. By aligning surgical urgency and complexity with facility capabilities, high-acuity cases will be prioritized at OSF HealthCare St. Francis Medical Center while lower-complexity procedures are redirected to other hospitals. The interactive scheduling model will leverage real-time data and predictive analytics to optimize OR use, reduce bottlenecks, and enhance access to timely, patient-centered care.