ReflexDAO | Connected health & wellbeing

More than measurement: wearables help you live better.

Lehrer, P. My Life in HRV Biofeedback Research. Appl Psychophysiol Biofeedback 47, 289–298 (2022).

@ReflexDAO is building infrastructure where you own this kind of physiological data. Understanding your baroreflex resonance could enable proactive autonomic health management - moving from population averages to n-of-1 precision.

Breathing at your resonance frequency - typically 5-6 breaths/min - triggers massive oscillations in heart rate via the baroreflex. This 2022 review in Applied Psychophysiology and Biofeedback traces decades of HRV biofeedback research showing measurable effects on asthma and depression .

Researchers reviewed 11 studies on wearables for long COVID tracking. Smartwatches emerged as the most practical devices, monitoring heart rate variability, sleep, and activity - key markers of autonomic recovery. (Kukreti S, Lu M, Yeh C, Ko N Physiological Sensors Equipped in Wearable Devices for Management of Long COVID Persisting Symptoms: Scoping Review J Med Internet Res 2025)

Wang, X., Lamoth, C. J. C., & Wilhelm, E. (2026). AdaptStress: Online adaptive learning for interpretable and personalized stress prediction using multivariate and sparse physiological signals.

Watch for wearable companies racing to add 'AI stress coaching'. The question isn't whether they can predict stress—they can. It's whether you control the algorithm learning from your body, or whether you're just feeding someone else's prediction engine.

New research shows stress prediction from smartwatch data works best when models learn what's unique about you, not what's average across everyone. Sleep patterns matter most, but the same signal can mean opposite things for different people.

By 1957, cardiovascular disease caused 77% of deaths in diabetics—up from just 17% in 1914. Annals of Internal Medicine (Ostrander LD Jr, Francis T Jr, Hayner NS, Kjelsberg MO, Epstein FH. The relationship of cardiovascular disease to hyperglycemia. Ann Intern Med. 1965;62(6):1188-1198.) shows why continuous glucose monitoring paired with heart rate variability tracking matters for early intervention.

Your body is generating signals every second. We’re turning them into personalized insights - and a data commons you control.

Hao, Y., Tan, N.K.W., Gao, E.Y. et al. Electrocardiogram heart rate variability for machine learning diagnosis of obstructive sleep apnoea: A Bayesian meta-analysis. Sleep Breath 29, 303 (2025).

This is precisely why @ReflexDAO exists: to help you understand what your continuous physiological data reveals about your health, and to ensure you control that data. The future of preventive health starts with ownership.

Machine learning analysis of heart rate variability can detect obstructive sleep apnoea with 79% sensitivity and 75% specificity - better than questionnaire screening tools, using data your smartwatch already collects.