Glucose Sensor Accuracy Patents: Who Leads, Where the Gaps Are 2026
- Concentrated at the top. The five leading assignees hold 60.5% of all 4,839 records in scope, and the leader alone accounts for 1,531 filings.
- Filing has cooled from its 2019 peak. Volume ran from 376 filings in 2019 to a documented -38% drop between 2021 (255) and 2024 (159), the last complete filing year.
- Diagnosis and material-analysis classes dominate. A61B covers 56.7% of records and G01N 21.9%, while image processing (G06T, 3.6%) and navigation-adjacent sensing (G01C, 3.8%) remain comparatively thin.
Filing growth compares 2021 (255 records) with 2024 (159) — a three-year span. 2024 is the most recent year we treat as complete: publication lags filing by roughly 18 months, so 2025 onwards are still filling in and any growth rate that ends there would understate the field. Top-5 share is the combined record count of the five largest assignees divided by all 4,839 records in scope (CR5), not by the ranked leaders only.
What this landscape covers
This landscape tracks patent filings addressing glucose sensor accuracy and calibration — the methods used to align continuous glucose monitor readings with reference blood measurements, correct for physiological lag time, and manage compression artifacts and factory calibration schemes. The scope spans 4,839 patent families published between 2015 and mid-2026, drawn from filings that reference mean absolute difference, clinical accuracy studies, reference measurement protocols and related calibration mechanics.
Because publication lags filing by roughly 18 months, the most recent one to two years in any trend chart will understate true filing activity; 2024 is treated here as the last complete filing year for growth comparisons.
Filing trends and technology composition
Filing volume and IPC composition together show where claim density has built up and where it has not.
A cooling filing curve after a 2019 peak
Filings rose from 224 in 2017 to a peak of 376 in 2019, then eased; the documented complete-year comparison shows a -38% drop from 255 filings in 2021 to 159 in 2024. Figures for 2025 and 2026 are still filling in and should not be read as a continuing decline.
Diagnosis and material analysis lead the classification mix
A61B (diagnosis and surgery) appears on 56.7% of the 4,839 records and G01N (material analysis and testing) on 21.9%, reflecting the core sensor-and-reference-measurement work. Supporting classes — body-fluid devices, healthcare informatics and digital data processing — each sit between 9% and 13%, while image processing and navigation-adjacent sensing remain under 4%, since records can carry multiple classes these shares sum to more than 100%.
Shares are the percentage of the 4,839 records in scope. A patent can carry several IPC classes, so the shares add up to more than 100%.
Go deeper on Glucose Sensor Accuracy and Calibration with Eureka
This page is one run against one query. Ask Eureka your own question about glucose sensor accuracy and calibration and every answer comes back with the patent numbers behind it.
Try EurekaFoundational filings still shaping the field
Systems and methods for off-line and on-line sensor calibration
Systems and methods for off-line and on-line sensor calibration are provided. In certain embodiments, a method for calibrating a sensor comprises receiving at least one reference measurement describing a system state for a system, and receiving at least one sensor measurement acquired from an observation of the environment by the sensor. The method also calculates a model residual power spectral density based on the reference measurement and a sensor measurement model, and a measurement residual power spectral density based on the sensor measurement.Filed by Honeywell International, this filing frames calibration as a residual power-spectral-density comparison between a reference measurement and a sensor measurement model rather than a fixed offset correction.
| # | Publication no. | Patent title | Citations |
|---|---|---|---|
| 1 | US5497772A | Glucose monitoring system | 2,480 |
| 2 | US5791344A | Patient monitoring system | 1,984 |
| 3 | US6931327B2 | System and methods for processing analyte sensor data | 1,853 |
| 4 | US5660163A | Glucose sensor assembly | 1,818 |
| 5 | US20070016381A1 | Systems and methods for processing analyte sensor data | 1,796 |
| 6 | US20060020187A1 | Transcutaneous analyte sensor | 1,788 |
| 7 | US20080033254A1 | Systems and methods for replacing signal data artifacts in a glucose sensor data stream | 1,725 |
| 8 | US20060016700A1 | Transcutaneous analyte sensor | 1,715 |
| 9 | US7310544B2 | Methods and systems for inserting a transcutaneous analyte sensor | 1,640 |
| 10 | US20060020186A1 | Transcutaneous analyte sensor | 1,618 |
Citation counts inside this corpus favour older filings and should be read as a signal of influence on later work, not as a measure of current commercial importance.
Each row carries its publication number; clicking a row searches Eureka by that number.
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Three patterns stand out once filing counts, classification shares and momentum are read together.
The top of the field is crowded
The five leading assignees hold 2,929 of the 4,839 records in scope — 60.5% of the field. A new entrant filing in core calibration mechanics is filing against dense prior art from a small number of established sensor makers, not a fragmented field.
Volume has eased from its 2019 peak
Filings peaked at 376 in 2019 and the last complete-year comparison shows a documented drop from 255 in 2021 to 159 in 2024. Recent-year assignee momentum shows several leading filers down sharply year-on-year, though 2025-2026 figures are still incomplete due to publication lag.
Image processing and general measurement are thin
G06T (image data processing) sits at 3.6% of records and G01D (general measuring and recording) at 4.1%, well below the 56.7% carried by A61B. That gap suggests calibration approaches built around image-based or novel general-purpose measurement signals are less contested than core diagnostic-sensor claims.
Eureka can read the same corpus for gaps instead of for coverage: under-claimed branches adjacent to glucose sensor accuracy and calibration, with the prior art for and against each one.
Who holds the ground, and where filing has slowed
The ranked leaders account for two-thirds of all filings in scope, but recent-year momentum shows even the largest filers pulling back.
One assignee dominates the ranking
The leading assignee holds 1,531 records, more than five times the fifth-place total of 87. That gap is unusually wide even for a concentrated field and marks the calibration and sensor-data-processing claim space as heavily fenced.
Concentration extends past the top five
The top ten assignees combined hold 3,207 records, 66.3% of all records in scope, with the tenth-ranked filer at 40 records — a steep drop-off that marks a long tail of smaller filers below it.
Even the leaders are filing less
The top-ranked assignee filed 4 records in the latest year, down 73% year-on-year, and several other leading assignees show 0 filings in the latest year against prior activity. Read alongside the 18-month publication lag, this points to a maturing claim landscape rather than an active filing race.
| Assignee | Recent year | YoY |
|---|---|---|
| Dexcom, Inc. | 4 | -73% |
| Abbott Diabetes Care Inc. | 4 | -67% |
| Masimo Corporation | 2 | 0% |
| Medtronic MiniMed, Inc. | 0 | -100% |
| Gecko Robotics, Inc. | 0 | -100% |
| Qualcomm Incorporated | 0 | -100% |
| TRIFO INC | 0 | -100% |
| Senseonics, Inc. | 0 | -100% |
Where to take this next
The dataset points to specific next steps depending on whether the goal is freedom-to-operate, portfolio strategy or competitive tracking.
Map claim boundaries around the leading filer
With one assignee holding 1,531 records, a freedom-to-operate review should start by mapping which calibration mechanics its claims actually cover before assuming a broader block.
Explore assignee claims in EurekaTest white space in under-claimed branches
Image-based correction and cross-sensor fusion carry the thinnest IPC coverage in this dataset, making them a reasonable starting point for a first claim search.
Run a white space search in EurekaTrack momentum shifts, not just totals
Several leading assignees show sharp year-on-year declines in filing counts; monitoring whether that continues past the publication-lag window will matter more than the historical totals.
Set up momentum tracking in EurekaCommon questions on this landscape
The assignee ranking in this dataset is led by one company with 1,531 records, well ahead of the fifth-ranked filer at 87. The top five assignees combined hold 60.5% of all 4,839 records in scope, and the top ten hold 66.3%. This level of concentration means a competitive review of this space should focus first on the small number of leading filers rather than treating the field as fragmented.
Filing peaked at 376 records in 2019 and has since eased; the last complete-year comparison in this dataset shows a documented -38% drop, from 255 filings in 2021 to 159 in 2024. Because publication typically lags filing by around 18 months, the 2025 and 2026 figures in any trend chart are still incomplete and should not be read as confirming a continued decline. The honest read is that filing has cooled from its 2019 peak, not that it has stopped.
Mean absolute difference is a standard accuracy metric comparing a continuous glucose monitor's readings against a reference blood glucose measurement, and it appears throughout the calibration and clinical-accuracy filings in this dataset. Patents using this term typically claim a specific method for reducing that difference, whether through factory calibration, lag-time correction or compression-artifact handling. It is a search term used to scope this landscape rather than a category of technology on its own.
The classification data shows image data processing (G06T) at 3.6% of the 4,839 records and general measuring and recording (G01D) at 4.1%, both well below the 56.7% carried by the core diagnosis and surgery class A61B. That gap suggests calibration approaches built around image-based signals, cross-sensor fusion or general-purpose measurement standards carry comparatively less claim density than core sensor-hardware and reference-measurement claims, making them a reasonable starting point for a first-claim search.
The United States receives the largest share of filings in this dataset at 2,543 records, followed by the European Patent Office at 800 and WIPO PCT filings at 416. Australia, Canada and Germany each show smaller but active filing counts. This distribution reflects where the leading assignees pursue primary protection and where they extend coverage through PCT and regional filings.
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Disclaimer. This page is generated from Patsnap Eureka data drawn from a limited snapshot of global patent and scientific-literature records, and is provided for general information and reference only.
Patent data carries inherent limitations: recent filings (typically the most recent 18–24 months) are under-counted due to standard publication lag; counts may be reported at either a patent-family or a patent-record basis and are not always directly comparable; classification, applicant-name, and citation data may contain errors, duplicates, or omissions; and the underlying search query defines and constrains the scope shown. As a result, the analysis may be incomplete or inaccurate and may not reflect the full technology landscape.
Nothing on this page constitutes an exhaustive prior-art, novelty, freedom-to-operate, or validity search, nor does it constitute legal, financial, investment, or professional advice, and it should not be relied upon as such. Any patent, commercial, or strategic decision should be verified independently and reviewed with qualified patent, legal, and domain professionals. Patsnap makes no warranties, express or implied, as to the accuracy, completeness, or fitness for any particular purpose of the information presented.
Machine translation. Assignee and organisation names originally recorded in Chinese, Japanese or Korean have been rendered into English by an AI translation step so that the tables stay readable. These renderings are best-effort and may not match a company’s registered English name; the original name is what the underlying patent record carries, and it is what any Eureka query launched from this page uses.