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-0495956 (2012-06-13) |
등록번호 | US-9149233 (2015-10-06) |
발명자 / 주소 |
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출원인 / 주소 |
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대리인 / 주소 |
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인용정보 | 피인용 횟수 : 1 인용 특허 : 543 |
Systems and methods for processing sensor data are provided. In some embodiments, systems and methods are provided for calibration of a continuous analyte sensor. In some embodiments, systems and methods are provided for classification of a level of noise on a sensor signal. In some embodiments, sys
Systems and methods for processing sensor data are provided. In some embodiments, systems and methods are provided for calibration of a continuous analyte sensor. In some embodiments, systems and methods are provided for classification of a level of noise on a sensor signal. In some embodiments, systems and methods are provided for determining a rate of change for analyte concentration based on a continuous sensor signal. In some embodiments, systems and methods for alerting or alarming a patient based on prediction of glucose concentration are provided.
1. A method for calibration of a continuous glucose sensor, the method comprising: receiving, using electronic circuitry, sensor data from a continuous analyte sensor, the sensor data comprising one or more sensor data points;receiving and processing, using the electronic circuitry, calibration info
1. A method for calibration of a continuous glucose sensor, the method comprising: receiving, using electronic circuitry, sensor data from a continuous analyte sensor, the sensor data comprising one or more sensor data points;receiving and processing, using the electronic circuitry, calibration information to generate a calibration function;evaluating, using the electronic circuitry, a predictive accuracy of the calibration information to determine a predictive accuracy metric;calibrating, using the electronic circuitry, sensor data using the calibration function;comparing, using the electronic circuitry, the predictive accuracy metric to one or more thresholds; andprocessing, using the electronic circuitry, the calibrated sensor data to generate output, wherein the processing is performed differently depending upon the comparison of the predictive accuracy metric to the one or more thresholds, wherein the processing comprises controlling insulin delivery and/or insulin therapy instructions differently based on the comparison of the predictive accuracy metric to the one or more thresholds. 2. The method of claim 1, wherein the processing comprises determining a time period before requesting additional reference data. 3. The method of claim 2, wherein the time period is between about 0 minutes and 7 days. 4. The method of claim 2, further comprising displaying the time period before reference data will be requested. 5. The method of claim 1, wherein the receiving and processing calibration information comprises receiving a matched data pair and forming a calibration set including the matched data pair, and wherein the evaluating a predictive accuracy comprises evaluating a discordance of the matched data pair and/or the matched data pairs in the calibration set. 6. The method of claim 1, wherein the receiving and processing calibration information comprises receiving reference data, and wherein the evaluating a predictive accuracy comprises evaluating a leverage of the reference data based at least in part on a glucose concentration associated with the reference data. 7. The method of claim 1, wherein the processing comprises controlling alarms indicative of at least one of hypoglycemia, hyperglycemia, predicted hypoglycemia, or predicted hyperglycemia differently based on the comparison of the predictive accuracy metric to the one or more thresholds. 8. The method of claim 1, wherein the processing comprises diagnosing a sensor condition differently based at least in part on the comparison of the predictive accuracy metric to the one or more thresholds. 9. The method of claim 1, wherein the one or more thresholds delineate at least three predetermined ranges of accuracy. 10. The method of claim 1, wherein determining the predictive accuracy metric comprises calculating the predictive accuracy metric in terms of a percentage or a deviation value. 11. A system for processing continuous analyte sensor data, comprising: a continuous analyte sensor configured to continuously measure a concentration of an analyte in a host; anda computer system that receives sensor data from the continuous analyte sensor, wherein the computer system is configured to receive and process calibration information to generate a calibration function,evaluate a predictive accuracy of calibration information to determine a predictive accuracy metric,calibrate the sensor data using the calibration function,compare the predictive accuracy metric to one or more thresholds,process the calibrated sensor data to generate output, wherein the processing is performed differently depending upon the comparison of the predictive accuracy metric to the one or more thresholds, andcontrol insulin delivery and/or insulin therapy instructions differently based on the comparison of the predictive accuracy metric to the one or more thresholds. 12. The system of claim 11, wherein the computer system is configured to determine a time period to request additional reference data based on the predictive accuracy metric. 13. The system of claim 12, wherein the time period is between about 0 minutes and 7 days. 14. The system of claim 12, wherein the computer system is configured to display the time period before reference data will be requested. 15. The system of claim 11, wherein the calibration information comprises one or more matched data pairs, a calibration set including a plurality of the one or more matched data pairs, and wherein the computer system is configured to evaluate a predictive accuracy by evaluating a discordance of the matched data pair and/or the matched data pairs in the calibration set. 16. The system of claim 11, wherein the calibration information comprises reference data, and wherein the computer system is configured to evaluate a predictive accuracy by evaluating a leverage of the reference data based at least in part on a glucose concentration associated with the reference data. 17. The system of claim 11, wherein the computer system is configured to control an alarm indicative of at least one of hypoglycemia, hyperglycemia, predicted hypoglycemia, and predicted hyperglycemia differently based on the comparison of the predictive accuracy metric to the one or more thresholds. 18. The system of claim 11, wherein the computer system is configured to diagnose a sensor condition differently based at least in part on the comparison of the predictive accuracy metric to the one or more thresholds. 19. The system of claim 11, wherein the one or more thresholds delineate at least three predetermined ranges of accuracy. 20. The system of claim 11, wherein determining the predictive accuracy metric comprises calculating the predictive accuracy metric in terms of a percentage or a deviation value.
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