RPI ID: 2019-052-401
Innovation Summary: This system introduces a sensor module for patient monitoring that uses time-of-flight (TOF) sensors to generate elevation maps of a patient room. These maps are analyzed to determine distance and velocity vectors of room occupants, enabling classification of activities as acceptable or unacceptable. The system can notify facility management or log activity based on classification outcomes. It supports multi-sensor configurations and incorporates machine learning for improved accuracy and adaptability.
Challenges / Opportunities: Camera-based monitoring systems raise privacy concerns in healthcare settings. This TOF-based system offers a privacy-preserving alternative while maintaining detailed tracking capabilities. The technology is well-suited for elder care, behavioral monitoring, and abuse prevention. Integration with facility management systems and AI-driven analytics presents opportunities for broader deployment and automation.
Key Benefits / Advantages: ✔ Preserves patient privacy ✔ Enables real-time activity classification ✔ Supports multi-sensor configurations ✔ Machine learning-enhanced monitoring ✔ Integrates with facility management systems
Applications: • Hospital and elder care monitoring • Behavioral health facilities • Abuse prevention and documentation • Smart room occupancy tracking
Keywords: patient monitoring, time-of-flight sensors, privacy-preserving surveillance, healthcare analytics, machine learning, elder care
Intellectual Property: Published US Patent Application 17/598986