초록 ▼

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.

대표청구항 ▼

What is claimed is: 1. A method of calibrating glucose monitor data, the method comprising the steps of: sampling glucose monitor data from a sensor at a predetermined sampling rate; deriving interval values from the sampled glucose monitor data over a predetermined interval rate; applying clipping

What is claimed is: 1. A method of calibrating glucose monitor data, the method comprising the steps of: sampling glucose monitor data from a sensor at a predetermined sampling rate; deriving interval values from the sampled glucose monitor data over a predetermined interval rate; applying clipping limits to the derived interval values; deriving at least one glucose monitor data point by averaging the derived interval values at a predetermined memory storage rate; obtaining from another blood glucose measuring device at least one blood glucose reference reading that is temporally associated with at least one glucose monitor data point; calibrating the sampled glucose monitor data using the at least one blood glucose reference reading and the corresponding at least one glucose monitor data point. 2. The method of claim 1, wherein the step of calibrating the sampled glucose monitor data using the at least one blood glucose reference reading and the corresponding at least one glucose monitor data point comprises: determining a calibration equation using the at least one blood glucose reference reading and the corresponding at least one glucose monitor data point; and calibrating the sampled glucose monitor data using the calibration equation. 3. The method of claim 2, wherein the step of deriving interval values from the sampled glucose monitor data over a predetermined interval rate comprises averaging the sampled glucose monitor data. 4. The method of claim 3, wherein the step of averaging the derived interval values over a predetermined memory storage rate ignores a high and a low derived interval value obtained during one cycle of the predetermined memory storage rate. 5. The method of claim 4, wherein the predetermined sampling rate is about once in 10 seconds, the predetermined interval rate is about once in 1 minute, and the predetermined memory storage rate is about once in 5 minutes. 6. The method of claim 2, wherein the step of deriving interval values from the sampled glucose monitor data over a predetermined interval rate comprises averaging the sampled glucose monitor data and ignoring a high and a low sampled value over the interval. 7. The method of claim 2, wherein the step of deriving interval values from the sampled glucose monitor data over a predetermined interval rate comprises applying clipping limits to the sampled glucose monitor data over the interval and averaging the post-clipped sampled glucose monitor data. 8. The method of claim 2, further comprising the steps of: setting clipping limits for a first derived interval value; and setting clipping limits for each subsequently derived interval value based on the clipping limits set for at least one preceding derived interval value. 9. The method of claim 2, further comprising the steps of: setting clipping limits for a first derived interval value; and setting clipping limits for each subsequently derived interval value based on the clipping limits set for all preceding derived interval values. 10. The method of claim 2, wherein the calculation of the calibration equation is obtained using linear regression. 11. The method of claim 10, wherein the linear regression is a least squares linear regression. 12. The method of claim 2, wherein the calculation of the calibration equation is obtained using non-linear regression. 13. The method of claim 2, wherein the calculation of the calibration equation is obtained using a non-regression technique. 14. The method of claim 2, wherein the calibration is performed retrospectively on the sampled glucose monitor data that has been collected for post processing using the calibration equation post process. 15. The method of claim 1, wherein the method further comprises the step of shifting the data by a predetermined time factor. 16. The method of claim 1, wherein the calibration is performed while sampling the glucose monitor data. 17. The method of claim 1, wherein one or more calculations for calculating a first calibration factor is different than one or more calculations for calculating all subsequent calibration factors. 18. The method of claim 17, wherein the one or more calculations for calculating subsequent calibration factors employ a weighted average using a calibration factor calculated from data collected since the last calibration and previous calibration factors calculated for previous calibrations. 19. The method of claim 17, wherein the calculation for calculating a first calibration factor uses a single-point calibration equation. 20. The method of claim 19, wherein the single-point calibration equation includes an offset value. 21. The method of claim 19, wherein the calculation for calculating the subsequent calibration factors uses a linear regression calibration equation. 22. The method of claim 19, wherein the calculation for calculating the subsequent calibration factors uses a non-linear regression calibration equation. 23. The method of claim 19, wherein the calculation for calculating the subsequent calibration factors uses a non-regression calibration equation. 24. An article of manufacture containing code for calibrating glucose monitor data, comprising a computer usable medium including at least one embedded computer program that is capable of causing at least one computer to perform: sampling glucose monitor data from a sensor at a predetermined sampling rate; deriving interval values from the sampled glucose monitor data over a predetermined interval rate; applying clipping limits to the derived interval values; deriving at least one glucose monitor data point by averaging the derived interval values at a predetermined memory storage rate; obtaining from another blood glucose measuring device at least one blood glucose reference reading that is temporally associated with at least one glucose monitor data point; calibrating the sampled glucose monitor data using the at least one blood glucose reference reading and the corresponding at least one glucose monitor data point. 25. The article of manufacture of claim 24, wherein the step of calibrating the sampled glucose monitor data using the at least one blood glucose reference reading and the corresponding at least one glucose monitor data point comprises: determining a calibration equation using the at least one blood glucose reference reading and the corresponding at least one glucose monitor data point; and calibrating the sampled glucose monitor data using the calibration equation. 26. The article of manufacture of claim 25, wherein the step of deriving interval values from the sampled glucose monitor data over a predetermined interval rate comprises averaging the sampled glucose monitor data. 27. The article of manufacture of claim 26, wherein the step of averaging the derived interval values over a predetermined memory storage rate ignores a high and a low derived interval value obtained during one cycle of the predetermined memory storage rate. 28. The article of manufacture of claim 27, wherein the predetermined sampling rate is about once in 10 seconds, the predetermined interval rate is about once in 1 minute, and the predetermined memory storage rate is about once in 5 minutes. 29. The article of manufacture of claim 25, wherein the step of deriving interval values from the sampled glucose monitor data over a predetermined interval rate comprises averaging the sampled glucose monitor data and ignoring a high and a low sampled value over the interval. 30. The article of manufacture of claim 25, wherein the step of deriving interval values from the sampled glucose monitor data over a predetermined interval rate comprises applying clipping limits to the sampled glucose monitor data over the interval and averaging the post-clipped sampled glucose monitor data. 31. The article of manufacture of claim 25, further performing the steps of: setting clipping limits for a first derived interval value; and setting clipping limits for each subsequently derived interval value based on the clipping limits set for at least one preceding derived interval value. 32. The article of manufacture of claim 25, further performing the steps of: setting clipping limits for a first derived interval value; and setting clipping limits for each subsequently derived interval value based on the clipping limits set for all preceding derived interval values. 33. The article of manufacture of claim 25, wherein the calculation of the calibration equation is obtained using linear regression. 34. The article of manufacture of claim 33, wherein the linear regression is a least squares linear regression. 35. The article of manufacture of claim 25, wherein the calculation of the calibration equation is obtained using non-linear regression. 36. The article of manufacture of claim 25, wherein the calculation of the calibration equation is obtained using a non-regression technique. 37. The article of manufacture of claim 25, wherein the calibration is performed retrospectively on the sampled glucose monitor data that has been collected for post processing using the calibration equation post process. 38. The article of manufacture of claim 24, further performing the step of shifting the data by a predetermined time factor. 39. The article of manufacture of claim 24, wherein the calibration is performed while sampling the glucose monitor data. 40. The article of manufacture of claim 24, wherein one or more calculations for calculating a first calibration factor is different than one or more calculations for calculating all subsequent calibration factors. 41. The article of manufacture of claim 40, wherein the one or more calculations for calculating subsequent calibration factors employ a weighted average using a calibration factor calculated from data collected since the last calibration and previous calibration factors calculated for previous calibrations. 42. The article of manufacture of claim 40, wherein the calculation for calculating a first calibration factor uses a single-point calibration equation. 43. The article of manufacture of claim 42, wherein the single-point calibration equation includes an offset value. 44. The article of manufacture of claim 42, wherein the calculation for calculating the subsequent calibration factors uses a linear regression calibration equation. 45. The article of manufacture of claim 42, wherein the calculation for calculating the subsequent calibration factors uses a non-linear regression calibration equation. 46. The article of manufacture of claim 42, wherein the calculation for calculating the subsequent calibration factors uses a non-regression calibration equation.