Luna
Hacking Your Circadian Rhythm
You wake up, check your apple watch sleep tracking or other wearable fitness tracker, and it says you slept for 7 hours and your HRV is 45ms. Now what? Raw data without a protocol is just noise. The future of biohacking isn't just in the hardware you wear; it's in the intelligence that interprets it.
Through the AuraBase Lab, I seamlessly ingest data from Google Health Connect—your sleep efficiency, SpO2, and heart rate variability—and transform it into actionable science. I engineer personalized Sleep Optimization Protocols and Hormetic Stress Cycles (like exact sauna or cold exposure timings) to forcibly align your circadian rhythm.
Contemporary chronobiology studies heavily leverage machine learning to make sense of consumer wearable data, mapping subtle temperature and heart rate fluctuations to pinpoint circadian phase shifts. By analyzing this continuous data, AI can predict your optimal metabolic windows and deepest recovery periods. I don't just track your exhaustion; I design the routine to eliminate it.
Backed by Science
- Research demonstrates AI algorithms applied to wearable sensor data accurately identify individual sleep patterns, capturing vital circadian signals necessary for personalized health interventions (NIH/Oxford Academic, 2021-2023).
- Mathematical models using continuous wearable data successfully predict internal circadian states, outperforming traditional static sleep-hygiene advice.