
The Chubold v3439 “Urinal Spy‑2” (US‑2) is a compact, contact‑free sensor system designed to perform continuous, non‑invasive urinalysis in public and clinical restroom settings. Leveraging multi‑modal spectroscopy (near‑infrared, Raman, and fluorescence) combined with AI‑driven signal processing, US‑2 can detect a panel of clinically relevant biomarkers (e.g., glucose, nitrites, protein, specific gravity, pH) with laboratory‑grade accuracy while preserving user privacy. This paper presents the hardware architecture, calibration methodology, machine‑learning pipeline, and validation results from a multi‑site field trial involving 1,200 participants. US‑2 demonstrates detection limits comparable to standard dip‑stick assays (≤5 mg/dL for glucose) and a false‑positive rate below 2 % across all analytes. The system’s modular design enables rapid upgrades to the biomarker panel and integration with electronic health record (EHR) platforms, opening new avenues for population‑scale health surveillance and early disease detection.
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The Chubold v3439 “Urinal Spy‑2” (US‑2) is a compact, contact‑free sensor system designed to perform continuous, non‑invasive urinalysis in public and clinical restroom settings. Leveraging multi‑modal spectroscopy (near‑infrared, Raman, and fluorescence) combined with AI‑driven signal processing, US‑2 can detect a panel of clinically relevant biomarkers (e.g., glucose, nitrites, protein, specific gravity, pH) with laboratory‑grade accuracy while preserving user privacy. This paper presents the hardware architecture, calibration methodology, machine‑learning pipeline, and validation results from a multi‑site field trial involving 1,200 participants. US‑2 demonstrates detection limits comparable to standard dip‑stick assays (≤5 mg/dL for glucose) and a false‑positive rate below 2 % across all analytes. The system’s modular design enables rapid upgrades to the biomarker panel and integration with electronic health record (EHR) platforms, opening new avenues for population‑scale health surveillance and early disease detection.
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