Sensor Diagnostics Patents: Who Leads, Where the Gaps Are 2026
- 96.8% concentration. The top five assignees hold 358 of the 370 records in scope, leaving a long tail of single-digit filers with little room at the top.
- One record at 1,517 citations. US20120078071A1's continuous analyte monitoring claims dwarf every other record in the corpus, marking where the field's real prior-art density sits.
- Filings down 44% from 2021 to 2024. The last fully-published years show a clear pull-back from 16 to 9 filings, though 2025-2026 figures are still incomplete.
Filing growth compares 2021 (16 records) with 2024 (9) — 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 370 records in scope (CR5), not by the ranked leaders only.
What this landscape covers
This landscape covers 370 published records filed between 2015 and the 2026 data cut-off, drawn from filings that combine sensor diagnostics or health-monitoring language with plausibility-check, redundancy-voting, drift-detection or predictive-replacement claims. The field is dominated by continuous analyte monitoring and IC-level redundant sensor diagnostics, with diagnosis-and-surgery classification (A61B) present in 91.1% of records.
Filing activity peaked in 2018 and has since pulled back, with the most recent complete comparison showing a decline into 2024. A small number of assignees account for nearly all of the filing volume, so the competitive picture here is less about a crowded field and more about one dominant portfolio and a scattered set of smaller filers.
Let an AI agent run this analysis on your own technology
Pick a task. Every answer cites the patents behind it.
How filings and technology classes break down
The dataset spans 370 published records from 2015 through the 2026 cut-off, with concentration and technology-class figures drawn directly from the same record base.
Filing trend, 2017-2026
Filings ran from 37 in 2017 to a peak of 51 in 2018, then eased across the following years; 2021 to 2024, the last year treatable as complete, fell from 16 to 9, a 44% decline over that span. 2025 and 2026 figures are still filling in given the roughly 18-month publication lag and should not be read as a continued drop.
Technology composition by IPC subclass
A61B (diagnosis and surgery) covers 91.1% of the 370 records, with G01N (material analysis and testing) at 37.6% and A61M (devices for body fluids) at 28.6% forming the next tier. Because records can carry several IPC classes, these shares add up to more than 100% of the record base.
Shares are the percentage of the 370 records in scope. A patent can carry several IPC classes, so the shares add up to more than 100%.
Go deeper on Sensor Diagnostics and Self-Validation with Eureka
This page is one run against one query. Ask Eureka your own question about sensor diagnostics and self-validation and every answer comes back with the patent numbers behind it.
Try EurekaThe most-cited and most representative filings
Highly efficient diagnostic methods for monolithic sensor systems
Embodiments relate to integrated circuit (IC) sensors and more particularly to IC sensor diagnostics using multiple (e.g., redundant) communication signal paths, wherein one or more of the communication signal paths can be diverse (e.g., in hardware, software or processing, an operating principle, or in some other way) from at least one other of the multiple communication signal paths. Embodiments can relate to a variety of sensor types, implementations and applications, including 3D magnetic field and other sensors.Granted to Infineon Technologies AG, 2019-07-16 (US10353018B2)
| # | Publication no. | Patent title | Citations |
|---|---|---|---|
| 1 | US20120078071A1 | Advanced continuous analyte monitoring system | 1,517 |
| 2 | US10231653B2 | Advanced continuous analyte monitoring system | 825 |
| 3 | US20130060105A1 | Orthogonally Redundant Sensor Systems and Methods | 232 |
| 4 | US20190049958A1 | Method and system for multiple sensor correlation diagnostic and sensor fusion/DNN monitor for autonomous dri… | 183 |
| 5 | US20130328572A1 | Application of electrochemical impedance spectroscopy in sensor systems, devices, and related methods | 92 |
| 6 | US20170181677A1 | Methods, systems, and devices for sensor fusion | 67 |
| 7 | US20190076070A1 | Methods, systems, and devices for calibration and optimization of glucose sensors and sensor output | 61 |
| 8 | WO2013184416A2 | Application of electrochemical impedance spectroscopy in sensor systems, devices, and related methods | 58 |
| 9 | US20150164371A1 | Use of electrochemical impedance spectroscopy (EIS) in gross failure analysis | 57 |
| 10 | US20130328573A1 | Application of electrochemical impedance spectroscopy in sensor systems, devices, and related methods | 57 |
Citation counts reflect influence within the searched corpus and favour older, earlier-filed records; treat them as a signal of downstream engineering interest rather than current commercial importance.
Each row carries its publication number; clicking a row searches Eureka by that number.
Put your own technology through the same analysis
Eureka on the web
When you want the answer in the next five minutes.
The agent works the prompt against patents and technical literature, citing every source.
Run your analysis now →MCP server & REST API
When it has to run inside your own pipeline.
Patent search, landscape analysis and assignee resolution as MCP tools. Drop them into any agent framework, or call REST directly.
Browse MCP servers →What the filing pattern signals
Three patterns stand out once the record set is broken down by concentration, technology class and filing trend.
One assignee dominates the ranking
The leading assignee alone accounts for 314 of the 370 records, and the top five together hold 358, or 96.8% of the field. Competitive tracking here means watching one portfolio closely, not scanning a broad field of comparable filers.
Diagnosis-and-surgery claims dominate the class mix
A61B covers 91.1% of the 370 records, with G01N material-analysis claims a distant second at 37.6%. Smaller classes like G16H and G06N show where informatics and AI-driven diagnostic logic remain lightly claimed relative to the hardware-heavy core.
Volume has pulled back from its 2018 peak
Filings peaked at 51 in 2018 and have since declined; the 2021-to-2024 window, the most recent comparison unaffected by publication lag, shows a drop from 16 to 9. Later years in the dataset are still filling in and should not be read as confirming a continued slide.
Eureka can read the same corpus for gaps instead of for coverage: under-claimed branches adjacent to sensor diagnostics and self-validation, with the prior art for and against each one.
| Assignee | Co-assignee | Shared families |
|---|---|---|
| WOLFE KATHERINE T | SHAH RAJIV | 3 |
| WOLFE KATHERINE T | KRISTENSEN JESPER SVENNING | 3 |
| WOLFE KATHERINE T | BANSAL ANUBHUTI | 3 |
| WOLFE KATHERINE T | AASMUL SOREN | 3 |
| SHAH RAJIV | KRISTENSEN JESPER SVENNING | 3 |
| SHAH RAJIV | BANSAL ANUBHUTI | 3 |
| SHAH RAJIV | AASMUL SOREN | 3 |
| KRISTENSEN JESPER SVENNING | BANSAL ANUBHUTI | 3 |
Co-assignee pairings in this dataset are sparse and concentrated among individual inventors rather than corporate joint filings, with the strongest pairs appearing three times each.
Who is filing, and where the field is still open
The ranked field covers 44 companies, but nearly all of the filing volume sits with a handful of them, leaving both a dominant portfolio to watch and open technology branches with little competing art.
One assignee drives the field
The leading assignee's 314 records out of 370 in scope make its portfolio the single most important reference point for freedom-to-operate work in this space, well ahead of any other filer in the ranking.
A wide but thin remainder
Beyond the top five, the ranking thins out quickly to single- and low double-digit filers, with the tenth-place assignee holding just 2 records. Most of this tail reflects individual inventors and smaller entities rather than sustained corporate filing programs.
One filing anchors the prior art
US20120078071A1's continuous analyte monitoring claims carry far more citations than any other record in this dataset, making it the reference point most likely to surface in any prior-art search touching sensor health monitoring.
| Assignee | Recent year | YoY |
|---|---|---|
| Medtronic MiniMed Inc. | 0 | -100% |
| Dexcom Inc. | 0 | -100% |
| Melexis Technologies NV | 0 | — |
| Infineon Technologies AG | 0 | — |
| WOLFE KATHERINE T | 0 | — |
| SHAH RAJIV | 0 | — |
| KRISTENSEN JESPER SVENNING | 0 | — |
| BANSAL ANUBHUTI | 0 | — |
Where to take this analysis
The dataset points to a few concrete next steps for teams deciding where to file or where to watch.
Check freedom-to-operate against the leader's portfolio
With one assignee holding 314 of the 370 records in scope, any new filing in continuous analyte monitoring or IC-level redundant diagnostics should be checked against that portfolio first.
Run a claim comparison in EurekaExplore the under-claimed informatics layer
G16H and G06N together cover a small share of the record base compared to the hardware-heavy core, suggesting room to file around predictive-replacement logic and drift classification software.
Explore white space in EurekaTrack the post-2024 filing trend as it fills in
Because publication lags filing by about 18 months, 2025 and 2026 figures will keep updating; revisit the trend once those years are closer to complete before concluding the field is still contracting.
Set a monitoring alert in EurekaCommon questions on this landscape
The ranked field of 44 companies is heavily concentrated at the top: the leading assignee alone accounts for 314 of the 370 records in scope, and the top five combined hold 96.8% of all records. That leaves a long tail of single- or double-digit filers, so due diligence should focus most attention on the leader's portfolio rather than spreading evenly across the ranking.
Filings peaked in 2018 at 51 and eased afterwards; the most recent complete comparison, 2021 to 2024, shows a drop from 16 to 9 filings, a 44% decline. Figures for 2025 and 2026 are still incomplete because publication typically lags filing by about 18 months, so it is not yet possible to say whether the field is still contracting or simply under-reported for those years.
US10353018B2, granted to Infineon Technologies AG in 2019, covers integrated-circuit sensor diagnostics that use multiple communication signal paths where at least one path is diverse from the others in hardware, software, processing or operating principle. It is not limited to a single sensor type; the abstract explicitly extends to a variety of sensor implementations and applications. Anyone designing on-chip redundant diagnostics should check whether their path diversity clears this claim before assuming simple duplication is safe.
The smaller IPC clusters in this dataset point to the gaps: healthcare informatics (G16H) sits at 6.8% of the 370 records, AI-based computing (G06N) at 5.7%, and transmission (H04B) at 5.1%, all well below the dominant A61B and G01N clusters. That suggests the software and connectivity layers around sensor validation, such as predictive-replacement scoring and wireless health-state reporting, are claimed far less densely than the core hardware redundancy and impedance-based diagnostic methods.
A61B (diagnosis and surgery) dominates at 91.1% of the 370 records, followed by G01N (material analysis and testing) at 37.6% and A61M (devices for body fluids) at 28.6%. G01R (electric and magnetic measurement) covers 14.6%. Because a single record can carry multiple IPC codes, these figures overlap rather than sum to 100%, and a freedom-to-operate search in this space should check all four classes together rather than relying on any one of them alone.
Research Sensor Diagnostics and Self-Validation in depth with Eureka
Go past this page: query the whole sensor diagnostics and self-validation corpus yourself, in your own scope.
Every answer comes back with patent numbers you can open.
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.