N19 : Noctura: Predictive System for Sleep Onset Latency Using Integrated Physiological and Dietary Data


Students Jeffery Cai
Shaurya Sehgal
School HDSB - Abbey Park High School - Oakville
Level Intermediate 9/10 - Grade 10
Group Group 12 - Health Science IV
Abstract This project investigates whether integrating physiological sensors and nutritional analysis into a real-time predictive system can predict and reduce sleep onset latency through proactive pre-sleep optimization. Unlike passive sleep tracking systems, this approach enables early intervention to reduce sleep onset latency and improve sleep quality through accessible, low-cost monitoring.
Awards
Group Award Prize
Merit AwardsSilver Merit Award$ 80
The Research Institute of St. Joe's Hamilton Health Research AwardsThe Research Institute of St. Joe's Hamilton Health Research Intermediate Award$ 100