Bayesian Denoising for Retrospective PISA Detection in Analyte Traces
Summary
The USPTO published patent application US20260096780A1 for a Bayesian denoising method to detect pressure-induced sensor artifacts (PISA) in analyte traces. The method receives measured analyte data samples from a sensor, generates a reconstructed trace with confidence windows using a Bayesian algorithm, and compares the two to identify artifacts outside the confidence interval. Inventors include Andrea Facchinetti, Simone Del Favero, Giovanni Sparacino, Elena Idi, Eleonora Manzoni, and Nunzio Camerlingo. The application (No. 18908001) was filed October 7, 2024 and published April 9, 2026.
“In accordance with a method of detecting a pressure induced sensor artifact (PISA) in an analyte trace, a measured analyte trace having a plurality of data samples obtained over a period of time from an analyte sensor is received.”
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GovPing monitors USPTO Patent Applications - Health Informatics (G16H) for new healthcare & life sciences regulatory changes. Every update since tracking began is archived, classified, and available as free RSS or email alerts — 146 changes logged to date.
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The USPTO published patent application US20260096780A1 for a method of detecting pressure-induced sensor artifacts (PISA) in analyte traces using Bayesian denoising. The method involves receiving measured analyte data from a sensor, generating a reconstructed trace with confidence windows using a model that separates true analyte values from measurement error, and comparing the two to identify samples outside the confidence window as PISA. The CPC classifications (A61B 5/7203, A61B 5/14532, A61B 5/7267, G16H 10/40) indicate applicability to continuous analyte monitoring systems such as continuous glucose monitors. The publication makes the technical disclosure publicly available for prior art searches, freedom-to-operate analyses, and competitive intelligence in health informatics and medical device development.
Archived snapshot
Apr 23, 2026GovPing captured this document from the original source. If the source has since changed or been removed, this is the text as it existed at that time.
BAYESIAN DENOISING FOR RETROSPECTIVE DETECTION
Application US20260096780A1 Kind: A1 Apr 09, 2026
Inventors
Andrea Facchinetti, Simone Del Favero, Giovanni Sparacino, Elena Idi, Eleonora Manzoni, Nunzio Camerlingo
Abstract
In accordance with a method of detecting a pressure induced sensor artifact (PISA) in an analyte trace, a measured analyte trace having a plurality of data samples obtained over a period of time from an analyte sensor is received. A reconstructed analyte trace and an associated confidence window is generated from the measured analyte trace using a Bayesian denoising algorithm that includes a model that models the measured analyte trace as a sum of an unknown true analyte trace and a measurement error. The measured analyte trace is compared to the reconstructed analyte trace to identify data samples in the measured analyte trace that are located outside of the confidence window as being associated with a PISA.
CPC Classifications
A61B 5/7203 A61B 5/14532 A61B 5/7267 G16H 10/40
Filing Date
2024-10-07
Application No.
18908001
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