How a Sensor Checks Itself for Accuracy Using Other Body Data
This patent describes a smart system that uses additional body measurements or relationships between different body chemicals to figure out if an analyte sensor, like a glucose monitor, is giving wrong readings and then fixes it or tells you to replace it.
Original patent title: “Systems and methods for multi-analyte sensing”
This patent describes a smart system that uses additional body measurements or relationships between different body chemicals to figure out if an analyte sensor, like a glucose monitor, is giving wrong readings and then fixes it or tells you to replace it. Owned by Dexcom with 23 claims and 7 forward citations, and it is expected to expire in 2043.
Coverage
What does this patent actually cover?
The apparatus includes an analyte sensor, memory, and processor (ClaimclaimA numbered sentence at the end of a patent that legally defines what the inventor owns. The most important section.Read more → 1). The processor monitors a patient's analyte, such as glucose (Claim 2), and also gathers other measured sensor data indicative of the patient's physiological state, like oxygen levels or temperature (Claim 3). Based on this physiological state, the system determines what the analyte reading *should* be (expected analyte data), potentially using historical data mapping (Claim 4). If the measured analyte data deviates significantly from this expected data (Claim 5), the system calculates a 'correction factor' (Claim 1, 8) that indicates a calibration error. If recalibration is possible, the system adjusts the sensor, perhaps by changing its sensitivity (Claim 9). If recalibration is not possible, it recommends that the patient replace the sensor (Claim 1). Another approach involves using two different analyte sensors, for example, for glucose and lactate (Claim 10, 12). The system learns the usual relationship between these two analytes and then checks if their current relationship matches the historical one. A substantial mismatch indicates a calibration error in one of the sensors, prompting recalibration (Claim 10). For example, if a continuous glucose monitor (CGM) is showing unusually low glucose readings while the patient's body temperature is high, the system might detect a calibration error and adjust the CGM's readings.
The gap
What does this patent NOT cover?
- Does not cover simple recalibration based solely on a single reference measurement (e.g., a finger-prick blood test) without considering additional physiological data or relationships between analytes.
- Does not cover systems that only monitor a single analyte without cross-referencing with other measured sensor data indicative of a physiological state or a second analyte.
- Does not cover systems that detect sensor errors but do not attempt recalibration or recommend replacement to the patient.
- Does not cover determining expected analyte data based on user-inputted lifestyle factors (like diet or exercise) unless these are derived from 'other measured sensor data indicative of a physiological state'.
These exclusions are unique to PatentBrief — derived from the actual claim language, not patent-office boilerplate.
Key facts
What made this novel
The actual noveltynoveltyThe requirement that an invention be different from anything publicly known before its priority date.Read more → is using concurrently measured physiological data (like temperature or oxygen levels, or the relationship between two different analytes) to predict what the primary analyte reading *should* be, and then automatically correcting the sensor's calibration or recommending replacement if there's a significant difference.
The Patent Drawing
Schematic visualization of the patent's claim structure. Hand-drawn diagrams in progress for each landmark patent.
Where you've seen this
Real-world examples
Dexcom G-series continuous glucose monitors
Abbott FreeStyle Libre systems
Future multi-analyte wearable sensors
Integrated health monitoring systems
Why it matters
The bigger picture
This patent is significant for improving the reliability and accuracy of continuous monitoring devices, especially in healthcare. For patients relying on these devices, such as those with diabetes using continuous glucose monitors (CGMs), accurate readings are crucial for managing their health. By automatically detecting and correcting calibration errors, or prompting replacement, it reduces the risk of incorrect medical decisions based on faulty data. Dexcom, the assigneeassigneeThe entity that owns the patent — usually the inventor's employer or a company.Read more →, is a major player in the CGM market.
Filed
February 22, 2023
Market context
Who's building on this
Companies in this space
Dexcom, as the assigneeassigneeThe entity that owns the patent — usually the inventor's employer or a company.Read more →, is actively developing and integrating advanced sensor calibration and error detection into its continuous glucose monitoring products. Other major players in the continuous monitoring space, such as Abbott and Medtronic, are also investing heavily in improving sensor accuracy and reliability through various methods, including multi-analyte sensing and smart algorithms. Startups in the wearable health tech space are also exploring similar approaches for a wider range of biomarkers.
Market impact
This type of technology enhances trust and reliability in continuous monitoring devices, which is critical for their widespread adoption and for improving health outcomes. It helps reduce the burden on users for manual calibration and provides earlier detection of faulty sensors, potentially preventing health complications from inaccurate readings. This contributes to the expansion of the continuous monitoring market by making devices more user-friendly and dependable.
Claim 1 — Plain English
What this patent covers
The apparatus includes an analyte sensor, memory, and processor (Claim 1). The processor monitors a patient's analyte, such as glucose (Claim 2), and also gathers other measured sensor data indicative of the patient's physiological state, like oxygen levels or temperature (Claim 3). Based on this physiological state, the system determines what the analyte reading *should* be (expected analyte data), potentially using historical data mapping (Claim 4). If the measured analyte data deviates significantly from this expected data (Claim 5), the system calculates a 'correction factor' (Claim 1, 8) that indicates a calibration error. If recalibration is possible, the system adjusts the sensor, perhaps by changing its sensitivity (Claim 9). If recalibration is not possible, it recommends that the patient replace the sensor (Claim 1). Another approach involves using two different analyte sensors, for example, for glucose and lactate (Claim 10, 12). The system learns the usual relationship between these two analytes and then checks if their current relationship matches the historical one. A substantial mismatch indicates a calibration error in one of the sensors, prompting recalibration (Claim 10). For example, if a continuous glucose monitor (CGM) is showing unusually low glucose readings while the patient's body temperature is high, the system might detect a calibration error and adjust the CGM's readings.
The clever bit
The actual novelty is using concurrently measured physiological data (like temperature or oxygen levels, or the relationship between two different analytes) to predict what the primary analyte reading *should* be, and then automatically correcting the sensor's calibration or recommending replacement if there's a significant difference.
What it does not cover
- Does not cover simple recalibration based solely on a single reference measurement (e.g., a finger-prick blood test) without considering additional physiological data or relationships between analytes.
- Does not cover systems that only monitor a single analyte without cross-referencing with other measured sensor data indicative of a physiological state or a second analyte.
- Does not cover systems that detect sensor errors but do not attempt recalibration or recommend replacement to the patient.
- Does not cover determining expected analyte data based on user-inputted lifestyle factors (like diet or exercise) unless these are derived from 'other measured sensor data indicative of a physiological state'.
Patent timeline
Application submitted to the patent office
Patent enters public domain
PatentBrief Score
Impact Score
Early stage
Citation count
18/40
Early citations
Claim breadth
15/20
Broad claimsclaimsThe numbered statements at the end of a patent that legally define what the inventor owns.Read more →
Recency
0/20
Older than 20 years
Assignee scale
0/20
Independent or smaller assigneeassigneeThe entity that owns the patent — usually the inventor's employer or a company.Read more →
PatentBrief Impact Score — based on citation count, claim breadth, recency, and assignee scale. Not a legal assessment.
Heuristic Value Estimate
What this patent might be worth
$137K – $439K
Midpoint $275K · 16.4 yr remaining · industry ×2.2
Heuristic only — blends forward/backward citation counts, claim scope, time remaining, litigation history, and CPC-derived industry baseline. Real valuations need a professional appraisal.
Claim text not yet imported for this patent
The original legal language
Original claims
23 claims as filed with the patent office.
Concepts involved
Citations
Patent lineage
Cite this patent
CHENG, K. K. W., Headen, D. M., LIONG, S., HELAYHEL, M. R., Simpson, P. C., DAMLE, S. S., Frank, S. T., Apollo, N. V., VANRENTERGHEM, H. F., & An, Q. How a Sensor Checks Itself for Accuracy Using Other Body Data (U.S. Patent No. 20,230,263,439). U.S. Patent and Trademark Office. https://patentbrief.org/patent/us/20230263439/systems-and-methods-for-multi-analyte-sensing
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Common Questions
Frequently Asked Questions
What does How a Sensor Checks Itself for Accuracy Using Other Body Data cover?
This patent describes a smart system that uses additional body measurements or relationships between different body chemicals to figure out if an analyte sensor, like a glucose monitor, is giving wrong readings and then fixes it or tells you to replace it.
Who owns patent US 20230263439?
This patent is owned by Dexcom.
When does this patent expire?
This patent is expected to expire on February 22, 2043, when the invention enters the public domain.
What is patent US 20230263439 cited by?
This patent has been cited by 7 later patents that build on its ideas.
What problem does this patent solve?
This patent is significant for improving the reliability and accuracy of continuous monitoring devices, especially in healthcare. For patients relying on these devices, such as those with diabetes using continuous glucose monitors (CGMs), accurate readings are crucial for managing their health. By automatically detecting and correcting calibration errors, or prompting replacement, it reduces the risk of incorrect medical decisions based on faulty data. Dexcom, the assignee, is a major player in the CGM market.
What does this patent NOT cover?
Does not cover simple recalibration based solely on a single reference measurement (e.g., a finger-prick blood test) without considering additional physiological data or relationships between analytes.
Same assignee
More from Dexcom
Patent monitoring