# US 2010/0168542 A1 · System and methods for processing analyte sensor data > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 2010/0168542 A1 - Document ID: US20100168542A1 - Status: Published application - Kind: A1 - Application number: 12/636,551 - Filed: 2009-12-11 - Published: 2010-07-01 - Earliest claimed: 2003-08-01 - Assignees: DexCom, Inc. - Inventors: Apurv Ullas Kamath; Paul V. Goode, JR.; James H. Brauker - Web page: https://patentgrep.com/patent/US20100168542A1 ## CPC - A61B 5/1495: Calibrating or testing of in-vivo probes - A61B 5/14532: {for measuring glucose, e.g. by tissue impedance measurement} - A61B 2560/0223: of calibration, e.g. protocols for calibrating sensors - A61B: DIAGNOSIS; SURGERY; IDENTIFICATION (usefulness limited to only animals A61D) ## Abstract Systems and methods for processing sensor analyte data, including initiating calibration, updating calibration, evaluating clinical acceptability of reference and sensor analyte data, and evaluating the quality of sensor calibration. During initial calibration, the analyte sensor data is evaluated over a period of time to determine stability of the sensor. The sensor may be calibrated using a calibration set of one or more matched sensor and reference analyte data pairs. The calibration may be updated after evaluating the calibration set for best calibration based on inclusion criteria with newly received reference analyte data. Fail-safe mechanisms are provided based on clinical acceptability of reference and analyte data and quality of sensor calibration. Algorithms provide for optimized prospective and retrospective analysis of estimated blood analyte data from an analyte sensor. ## Claims ### Claim 1 A method for calibrating a continuous analyte sensor data, the method comprising: receiving, with an electronic device, sensor data from a continuous analyte sensor, wherein the sensor data comprises one or more sensor data points; receiving reference data from a reference analyte monitor, wherein the reference data comprises one or more reference data points; forming at least one matched pair by pairing one or more sensor data points with one or more reference data points; forming two calibration lines; and calibrating the one or more sensor data points in real-time, wherein a first line of the two calibration lines is applied when a blood analyte concentration is at or below a predetermined threshold, and wherein a second line of the two calibration lines is applied when a blood analyte concentration is at or above the predetermined threshold. ### Claim 2 (depends on 1) The method of claim 1, wherein the two calibration lines comprise a first regression line based, at least in part, on a matched pair, and a second regression line obtained by applying a predetermined pivot about a point to the first regression line. ### Claim 3 (depends on 2) The method of claim 2, wherein the pivot is determined from a retrospective analysis of analyte sensor data. ### Claim 4 (depends on 2) The method of claim 2, wherein the pivot is selected such that a calibration line complies with a clinical acceptability standard. ### Claim 5 (depends on 4) The method of claim 4, wherein the clinical acceptability standard is at least one of a standard selected from the group consisting of Clarke Error Grid, Consensus Grid, mean absolute relative difference, and other clinical cost function. ### Claim 6 (depends on 2) The method of claim 2, wherein the continuous analyte sensor is a continuous glucose sensor. ### Claim 7 (depends on 6) The method of claim 6, wherein the calibration lines have different slopes. ### Claim 8 A system for calibrating a continuous analyte sensor data, the system comprising: a sensor data module configured to receive sensor data from a continuous analyte sensor, wherein the sensor data comprises one or more sensor data points; a reference input module configured to receive reference data from a reference analyte monitor, wherein the reference data comprises one or more reference data points; and a processor module configured to: form at least one matched pair by pairing one or more sensor data points with one or more reference data points; form two calibration lines, wherein at least one of the two calibration lines is based at least in part on the at least one matched pair; and calibrate the one or more sensor data points in real-time by applying a first line of the two calibration lines when a blood analyte concentration is at or below a predetermined threshold and by applying a second line of the two calibration lines when the blood analyte concentration is at or above the predetermined threshold. ### Claim 9 (depends on 8) The system of claim 8, wherein the two calibration lines comprise a first regression line based, at least in part, on a matched pair, and a second regression line obtained by applying a predetermined pivot about a point to the first regression line. ### Claim 10 (depends on 9) The system of claim 9, wherein the pivot is determined from a retrospective analysis of analyte sensor data. ### Claim 11 (depends on 8) The system of claim 8, wherein the pivot is selected such that a calibration line complies with a clinical acceptability standard. ### Claim 12 (depends on 11) The system of claim 11, wherein the clinical acceptability standard is at least one standard selected from group consisting of Clarke Error Grid, Consensus Grid, mean absolute relative difference, and other clinical cost function. ### Claim 13 (depends on 8) The system of claim 8, wherein the continuous analyte sensor is a continuous glucose sensor. ### Claim 14 (depends on 13) The system of claim 13, wherein the calibration lines have different slopes.