최소 단어 이상 선택하여야 합니다.
최대 10 단어까지만 선택 가능합니다.
다음과 같은 기능을 한번의 로그인으로 사용 할 수 있습니다.
NTIS 바로가기다음과 같은 기능을 한번의 로그인으로 사용 할 수 있습니다.
DataON 바로가기다음과 같은 기능을 한번의 로그인으로 사용 할 수 있습니다.
Edison 바로가기다음과 같은 기능을 한번의 로그인으로 사용 할 수 있습니다.
Kafe 바로가기국가/구분 | United States(US) Patent 등록 |
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국제특허분류(IPC7판) |
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출원번호 | US-0141375 (2002-05-08) |
발명자 / 주소 |
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출원인 / 주소 |
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대리인 / 주소 |
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인용정보 | 피인용 횟수 : 890 인용 특허 : 9 |
A method of calibrating glucose monitor data includes collecting the glucose monitor data over a period of time at predetermined intervals. It also includes obtaining at least two reference glucose values from a reference source that temporally correspond with the glucose monitor data obtained at th
A method of calibrating glucose monitor data includes collecting the glucose monitor data over a period of time at predetermined intervals. It also includes obtaining at least two reference glucose values from a reference source that temporally correspond with the glucose monitor data obtained at the predetermined intervals. Also included is calculating the calibration characteristics using the reference glucose values and the corresponding glucose monitor data to regress the obtained glucose monitor data. And calibrating the obtained glucose monitor data using the calibration characteristics is included. In preferred embodiments, the reference source is a blood glucose meter, and the at least two reference glucose values are obtained from blood tests. In additional embodiments, the calculation of the calibration characteristics is obtained using linear regression and in particular embodiments, least squares linear regression. Alternatively, the calculation of the calibration characteristics is obtained using non-linear regression.
1. A method of calibrating sensor data collected from a sensor, wherein a calibration formula based on past calibrations is used to interpret the sensor data, the method comprising the steps of:obtaining a calibration reference value for the sensor; calculating a current calibration factor based on
1. A method of calibrating sensor data collected from a sensor, wherein a calibration formula based on past calibrations is used to interpret the sensor data, the method comprising the steps of:obtaining a calibration reference value for the sensor; calculating a current calibration factor based on the calibration reference value and a current sensor data point; identifying either a possible error or change in sensitivity in the sensor from the current calibration factor; and confirming a sensor failure or recognizing a change in sensor sensitivity by comparing the current calibration factor with an estimated value for the current calibration factor to determine whether the current calibration factor was unexpected, wherein the estimated value for the current calibration factor is determined from the calibration formula and a past calibration factor; and confirming the sensor failure when at least two unexpected calibration factors are received in succession without supporting each other. 2. The method of claim 1, further comprising:updating the calibration formula with the calibration reference value if the sensor failure is not confirmed and no change in sensor sensitivity is recognized; and interpreting the collected sensor data using the updated calibration formula. 3. The method of claim 2, wherein the calibration formula is a modified regression method.4. The method of claim 3, wherein the modified regression method is Gaussian regression method.5. The method of claim 3, wherein the calibration formula weights past calibrations based on how recent the calibration was performed.6. The method of claim 2, wherein the calibration is performed while obtaining the sensor data.7. The method of claim 1, wherein the step of confirming a sensor failure or recognizing a change in sensor sensitivity further comprises:recognizing a change in sensor sensitivity when an unexpected past calibration factor is supported by a subsequent current calibration factor in succession; restarting the calibration formula calculation when a change in sensor sensitivity is recognized. 8. The method of claim 7, further comprising:interpreting the collected sensor data using the restarted calibration formula. 9. The method of claim 1, wherein the sensor is a glucose sensor.10. The method of claim 1, wherein the current sensor data point is obtained by the steps of:sampling characteristic sensor data at a predetermined rate from a sensor over time; deriving at least one current sensor data point from the sampled characteristic sensor data at a predetermined memory storage rate. 11. The method of claim 1, wherein the current sensor data point is obtained by the steps of:sampling characteristic sensor data; deriving interval values by applying clipping limits and averaging the post-clipped sampled characteristic sensor data over a predetermined interval rate; and deriving at least one current sensor data point by averaging the derived interval values at a predetermined memory storage rate. 12. A method of calibrating sensor data collected from a sensor, wherein a calibration formula based on past calibrations is used to interpret the sensor data, the method comprising the steps of:obtaining a calibration reference value for the sensor; calculating a current calibration factor based on the calibration reference value and a current sensor data point; identifying either a possible error or change in sensitivity in the sensor from the current calibration factor; and confirming a sensor failure or recognizing a change in sensor sensitivity by comparing the current calibration factor with an estimated value determined from the calibration formula and a past calibration factor; recognizing a change in sensor sensitivity when an unexpected past calibration factor is supported by a subsequent current calibration factor in succession; restarting the calibration formula calculation when a change in sensor sensitivity is recognized by creating an artificial calibration reference value; and formulating the calibration formula using the artificial calibration reference value, a past calibration reference value and a current calibration reference value. 13. An apparatus for calibrating sensor data collected from a sensor, wherein a calibration formula based on past calibrations is used to interpret the sensor data, the apparatus comprising:means for obtaining a calibration reference value for the sensor; means for calculating a current calibration factor based on the calibration reference value and a current sensor data point; means for identifying either a possible error or change in sensitivity in the sensor from the current calibration factor; and means for confirming a sensor failure or recognizing a change in sensor sensitivity by using a means for comparing the current calibration factor with an estimated value for the current calibration factor to determine whether the current calibration factor was unexpected, wherein the estimated value for the current calibration factor is determined from the calibration formula and a past calibration factor; and means for confirming the sensor failure when at least two unexpected calibration factors are received in succession without supporting each other. 14. The apparatus of claim 13, further comprising:means for updating the calibration formula with the calibration reference value if the sensor failure is not confirmed and no change in sensor sensitivity is recognized; and means for interpreting the collected sensor data using the updated calibration formula. 15. The apparatus of claim 14, wherein the calibration formula is a modified regression method.16. The apparatus of claim 15, wherein the modified regression method is Gaussian regression method.17. The apparatus of claim 15, wherein the calibration formula weights past calibrations based on how recent the calibration was performed.18. The apparatus of claim 14, wherein the calibration is performed while obtaining the sensor data.19. The apparatus of claim 13, wherein the means for confirming a sensor failure or recognizing a change in sensor sensitivity further comprises:means for recognizing a change in sensor sensitivity when an unexpected past calibration factor is supported by a subsequent current calibration factor in succession; means for restarting the calibration formula calculation when a change in sensor sensitivity is recognized. 20. The apparatus of claim 19, further comprising:means for interpreting the collected sensor data using the restarted calibration formula. 21. The apparatus of claim 13, wherein the sensor is a glucose sensor.22. The apparatus of claim 13, wherein the current sensor data point is obtained by:means for sampling characteristic sensor data at a predetermined rate from a sensor over time; means for deriving at least one current sensor data point from the sampled characteristic sensor data at a predetermined memory storage rate. 23. The apparatus of claim 13, wherein the current sensor data point is obtained by:means for sampling characteristic sensor data; means for deriving interval values by applying clipping limits and averaging the post-clipped sampled characteristic sensor data over a predetermined interval rate; and means for deriving at least one current sensor data point by averaging the derived interval values at a predetermined memory storage rate. 24. An apparatus for calibrating sensor data collected from a sensor, wherein a calibration formula based on past calibrations is used to interpret the sensor data, the apparatus comprising:means for obtaining a calibration reference value for the sensor; means for calculating a current calibration factor based on the calibration reference value and a current sensor data point; means for identifying either a possible error or change in sensitivity in the sensor from the current calibration factor; and means for confirming a sensor failure or recognizing a change in sensor sensitivity by using a means for comparing the current calibration factor with an estimated value determined from the calibration formula and a past calibration factor; means for recognizing a change in sensor sensitivity when an unexpected past calibration factor is supported by a subsequent current calibration factor in succession; restarting the calibration formula calculation when a change in sensor sensitivity is recognized by means for creating an artificial calibration reference value; and means for formulating the calibration formula using the artificial calibration reference value, a past calibration reference value and a current calibration reference value. 25. An article of manufacture containing code for calibrating sensor data collected from a sensor, wherein a calibration formula based on past calibrations is used to interpret the sensor data, comprising a computer usable media including at least one embedded computer program that is capable of causing at least one computer to perform:obtaining a calibration reference value for the sensor; calculating a current calibration factor based on the calibration reference value and a current sensor data point; identifying either a possible error or change in sensitivity in the sensor from the current calibration factor; and confirming a sensor failure or recognizing a change in sensor sensitivity by comparing the current calibration factor with an estimated value for the current calibration factor to determine whether the current calibration factor was unexpected, wherein the estimated value for the current calibration factor is determined from the calibration formula and a past calibration factor; and confirming the sensor failure when at least two unexpected calibration factors are received in succession without supporting each other. 26. The article of manufacture of claim 25, further performing:updating the calibration formula with the calibration reference value if the sensor failure is not confirmed and no change in sensor sensitivity is recognized; and interpreting the collected sensor data using the updated calibration formula. 27. The article of manufacture of claim 26, wherein the calibration formula is a modified regression method.28. The article of manufacture of claim 27, wherein the modified regression method is Gaussian regression method.29. The article of manufacture of claim 27, wherein the calibration formula weights past calibrations based on how recent the calibration was performed.30. The article of manufacture of claim 26, wherein the calibration is performed while obtaining the sensor data.31. The article of manufacture of claim 25, wherein the step of confirming a sensor failure or recognizing a change in sensor sensitivity further performs:recognizing a change in sensor sensitivity when an unexpected past calibration factor is supported by a subsequent current calibration factor in succession; restarting the calibration formula calculation when a change in sensor sensitivity is recognized. 32. The article of manufacture of claim 31, further performing:interpreting the collected sensor data using the restarted calibration formula. 33. The article of manufacture of claim 25, wherein the sensor is a glucose sensor.34. The article of manufacture of claim 25, wherein the current sensor data point is obtained by performing the steps of:sampling characteristic sensor data at a predetermined rate from a sensor over time; deriving at least one current sensor data point from the sampled characteristic sensor data at a predetermined memory storage rate. 35. The article of manufacture of claim 25, wherein the current sensor data point is obtained by performing the steps of:sampling characteristic sensor data; deriving interval values by applying clipping limits and averaging the post-clipped sampled characteristic sensor data over a predetermined interval rate; and deriving at least one current sensor data point by averaging the derived interval values at a predetermined memory storage rate. 36. An article of manufacture containing code for calibrating sensor data collected from a sensor, wherein a calibration formula based on past calibrations is used to interpret the sensor data, comprising a computer usable media including at least one embedded computer program that is capable of causing at least one computer to perform:obtaining a calibration reference value for the sensor; calculating a current calibration factor based on the calibration reference value and a current sensor data point; identifying either a possible error or change in sensitivity in the sensor from the current calibration factor; and confirming a sensor failure or recognizing a change in sensor sensitivity by comparing the current calibration factor with an estimated value determined from the calibration formula and a east calibration factor; recognizing a change in sensor sensitivity when an unexpected past calibration factor is supported by a subsequent current calibration factor in succession; restarting the calibration formula calculation when a change in sensor sensitivity is recognized by creating an artificial calibration reference value; and formulating the calibration formula using the artificial calibration reference value, a past calibration reference value and a current calibration reference value. 37. A method of calibrating sensor data collected from a sensor, wherein a calibration formula based on past calibrations is used to interpret the sensor data, the method comprising the steps of:obtaining a calibration reference value for the sensor; calculating a current calibration factor based on the calibration reference value and a current sensor data point; identifying a possible error from the current calibration factor; updating the calibration formula with the calibration reference value if no error is identified; and interpreting the collected sensor data using the updated calibration formula; wherein the calibration formula is a modified regression method which weights past calibrations based on how recent the calibration was performed. 38. The method of claim 37, wherein the calibration formula is updated and used to interpret the collected sensor data while obtaining the sensor data.39. A method of calibrating sensor data collected from a sensor, wherein a calibration formula based on past calibrations is used to interpret the sensor data, the method comprising the steps of:obtaining a calibration reference value for the sensor; and calculating a current calibration factor based on the calibration reference value and a current sensor data point; wherein the current sensor data point is obtained by the steps of: sampling characteristic sensor data; deriving interval values by applying clipping limits and averaging the post-clipped sampled characteristic sensor data over a predetermined interval rate; and deriving at least one current sensor data point by averaging the derived interval values at a predetermined memory storage rate.
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