Proposed framework enables monitoring of canine hormonal levels to predict stress and cognitive decline, suggesting practical solutions for pet health.
While contemporary wearables provide high-fidelity data on where a dog moves, they remain biologically blind to the metabolic cost of that movement. This paper proposes the transition from 'Motion Intelligence' to 'Metabolic Intelligence' by integrating 4th-generation electrochemical biosensors and reverse iontophoresis into a framework for continuous, non-invasive hormonal monitoring in companion animals. By fusing circadian behavioral bins with real-time cortisol pulses, the paper introduces Predictive Metabolic Phenotyping — identifying early markers of chronic stress and cognitive decline (allostatic load) before they manifest as irreversible clinical pathology. The Co-Regulation Loop architecture correlates canine metabolic data with owner wearables to produce a 360-degree Symbiosis Map of the human-dog dyad. Barkley White Paper | Precision Metabolic Intelligence Series | No. 01.
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Elodie P. Remoissenet (2026) studied this question.
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