RPI ID: 2012-068-401 & 2012-068-601
Innovation Summary:
This dual-invention system presents a comprehensive framework for estimating, modeling, and controlling human circadian rhythms using personalized, data-driven methods. It integrates real-time sensor data—such as light exposure and activity levels—with mathematical models of circadian biology to estimate an individual's internal clock. The system then applies model predictive control (MPC) to recommend optimized light exposure schedules or other interventions to shift or stabilize circadian phase. This enables non-invasive, adaptive circadian management for improved sleep, alertness, and overall health.
Challenges / Opportunities:
Circadian misalignment—caused by shift work, jet lag, or irregular sleep patterns—can lead to serious health and performance issues. Traditional methods for estimating circadian phase are often invasive, imprecise, or lack personalization. This invention addresses these limitations by offering a real-time, individualized solution that adapts to user behavior and environmental conditions. It opens new opportunities in healthcare, wearable technology, workplace wellness, and space travel, where circadian regulation is critical.
Key Benefits / Advantages:
✔ Accurate, real-time estimation of circadian phase using wearable data
✔ Predictive control for optimized light-based interventions
✔ Non-invasive and adaptable to individual lifestyle and environment
✔ Enhances sleep quality, alertness, and overall circadian health
Applications:
• Sleep and fatigue management for shift workers and frequent travelers
• Smart lighting systems for homes, offices, and healthcare settings
• Wearable health and wellness devices
• Clinical tools for circadian rhythm research and diagnostics
Keywords:
#CircadianRhythms #SleepHealth #WearableTech #LightTherapy #ModelPredictiveControl
Intellectual Property:
US Issued Patents 10,529,440 and 10,896,739
