Systems, Methods and Computer Program Codes for Recognition of Patterns of Hyperglycemia and Hypoglycemia, Increased Glucose Variability, and Ineffective Self-Monitoring in Diabetes
First Claim
1. A method for identifying and/or predicting patterns of hyperglycemia of a user, said method comprising:
- acquiring a plurality of SMBG data points;
classifying said SMBG data points within periods of time with predetermined durations;
evaluating glucose values in each period of time; and
indicating risk of hyperglycemia for a subsequent period of time based on said evaluation.
6 Assignments
0 Petitions
Accused Products
Abstract
A method, system, and computer program product related to the maintenance of optimal control of diabetes, and is directed to predicting patterns of hypoglycemia, hyperglycemia, increased glucose variability, and insufficient or excessive testing for the upcoming period of time, based on blood glucose readings collected by a self-monitoring blood glucose device. The method, system, and computer program product pertain directly to the enhancement of existing home blood glucose monitoring devices, by introducing an intelligent data interpretation component capable of predicting and alerting the user to periods of increased risk for hyperglycemia, hypoglycemia, increased glucose variability, and ineffective testing, and to the enhancement of emerging self-monitoring blood glucose devices by the same features. With these predictions the diabetic can take steps to prevent the adverse consequences associated with hyperglycemia, hypoglycemia, and increased glucose variability.
630 Citations
297 Claims
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1. A method for identifying and/or predicting patterns of hyperglycemia of a user, said method comprising:
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acquiring a plurality of SMBG data points; classifying said SMBG data points within periods of time with predetermined durations; evaluating glucose values in each period of time; and indicating risk of hyperglycemia for a subsequent period of time based on said evaluation. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 261, 262, 263, 264)
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2. The method of claim 1, wherein said evaluation comprising:
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determining individual deviations towards hyperglycemia based on said glucose values; determining a composite probability in each said period of time based on individual and absolute deviations; and comparing said composite probability in each period of time against a preset threshold.
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3. The method of claim 2, wherein the determination of said deviations comprises calculating the average and standard deviation of SMBG for each said period of time.
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4. The method of claim 2, wherein the determination of said deviations comprises calculating deviation contrasts for each said period of time.
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5. The method of claim 4, wherein said deviation contrasts are computed as
where Xk represents the average SMBG readings in period of time k, X represents the mean of all the SMBG readings, SD represents the standard deviation of all SMBG readings, SDk represents the standard deviation of SMBG readings in period of time k, N represents the total number of SMBG readings, and Nk represents the number of SMBG readings in period of time k. -
6. The method of claim 4, wherein said deviation contrasts are computed as
-
X k - Y k SD 1 where Yk is the average of the mean SMBG readings in the periods of time other than k, Xk represents the average SMBG readings in period of time k, and SD1 represents an estimate of the standard deviation of Xk−
Yk.
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7. The method of claim 2, wherein said composite probability comprises probability of exceeding an absolute threshold and probability of exceeding a relative personal threshold.
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8. The method of claim 2, wherein said composite probability is computed as
CPk(α- 1)=Pk(α
1).Φ
(tk)where Pk(α
1) represents the probability of average SMBG in each said period of time to exceed preset threshold level α
1 , Φ
(tk) represents the probability of said average SMBG data in each said period of time to be higher than average SMBG data of rest of said periods of time.
- 1)=Pk(α
-
9. The method of claim 8, wherein said Φ
- (tk) is the distribution function of a central normal distribution.
-
10. The method of claim 2, wherein said composite probability is computed as
CPk(α- 1)=Pk(α
1).Φ
(tk)where Pk(α
1 ) represents the probability of average SMBG in each said period of time to exceed preset threshold level α
1, Φ
(tk) represents the probability of said average SMBG data in each said period of time to be higher than a grand mean.
- 1)=Pk(α
-
11. The method of claim 10, wherein said Φ
- (tk) is the distribution function of a central normal distribution.
-
12. The method of claim 2, wherein the calculation of said composite probabilities comprises calculating probability of said average SMBG data in each said period of time to be higher than average SMBG data of rest of said periods of time.
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13. The method of claim 2, wherein the calculation of said composite probabilities comprise calculating probability of said average SMBG data in each said period of time to be higher than a grand mean.
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14. The method of claim 1, wherein said plurality of SMBG readings comprises SMBG data from about two to six weeks of monitoring together with the time of each reading.
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15. The method of claim 1, wherein each said period of time has a predetermined number of SMBG data points.
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16. The method of claim 15, wherein said predetermined number of SMBG data points is at least about five for each said period of time.
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17. The method of claim 1, wherein said periods of time comprises splitting twenty-four hour days into time bins with predetermined durations.
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18. The method of claim 17, wherein said predetermined durations is between two to eight hours.
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19. The method of claim 17, wherein said predetermined durations is fewer than twenty-four hours.
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20. The method of claim 1, wherein said subsequent period of time comprises a next period of time.
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21. The method of claim 1, wherein indication of said risk for hyperglycemia comprises issuing a message indicating a pattern of high blood sugar for a subsequent period of time.
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22. The method of claim 21, wherein said message indicating a pattern of high blood glucose is received immediately by a user prior to said subsequent period of time.
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23. The method of claim 21, wherein said subsequent period of time comprises a next period of time.
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24. The method of claim 1, wherein indication of said risk for hyperglycemia comprises issuing a message indicating a pattern of high blood sugar within about 24 hours of said acquisition of plurality of SMBG data points.
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25. The method of claim 1, wherein indication of said risk for hyperglycemia comprises issuing a message indicating a pattern of high blood sugar within about 12 hours of said acquisition of plurality of SMBG data points.
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26. The method of claim 1, wherein indication of said risk for hyperglycemia comprises issuing a message indicating a pattern of high blood sugar within about 6 hours of said acquisition of plurality of SMBG data points.
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27. The method of claim 1, wherein indication of said risk for hyperglycemia comprises issuing a message indicating a pattern of high blood sugar at the completion of the above claimed steps.
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28. The method of claim 1, wherein the indication of said risk of hyperglycemia occurs near contemporaneously to the latest SMBG testing.
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261. The method of claim 1, wherein the indication of said risk of hyperglycemia comprises issuing a message indicating a pattern of hyperglycemia, wherein the issuance occurs contemporaneously to a user-initiated action or at a predetermined time.
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262. The method of claim 1, wherein indication of said risk for hyperglycemia comprises issuing a message indicating a pattern of hyperglycemia, wherein the issuance occurs in real time or at a predetermined time.
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263. The method of claim 261, wherein said user-initiated action is the acquisition of one or more SMBG data points.
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264. The method of claim 261 or 262, wherein said predetermined time is within 24 hours of the acquisition of one or more SMBG data points.
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2. The method of claim 1, wherein said evaluation comprising:
-
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29. A system for identifying and/or predicting patterns of hyperglycemia of a user, said system comprising:
-
an acquisition module acquiring plurality of SMBG data points; and a processor programmed to; classify said SMBG data points within periods of time with predetermined durations; evaluate glucose values in each period of time; and indicate risk of hyperglycemia for a subsequent period of time based on said evaluation. - View Dependent Claims (30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 265, 266, 267, 268)
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30. The system of claim 29, wherein said evaluation comprising:
-
determining individual deviations towards hyperglycemia based on said glucose values; determining a composite probability in each said period of time based on individual and absolute deviations; and comparing said composite probability in each period of time against a preset threshold.
-
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31. The system of claim 30, wherein the determination of said deviations comprises calculating the average and standard deviation of SMBG for each said period of time.
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32. The system of claim 30, wherein the determination of said deviations comprises calculating deviation contrasts for each said period of time.
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33. The system of claim 32, wherein said deviation contrasts are computed as
where Xk represents the average SMBG readings in period of time k, X represents the mean of all the SMBG readings, SD represents the standard deviation of all SMBG readings, SDk represents the standard deviation of SMBG readings in period of time k, N represents the total number of SMBG readings, and Nk represents the number of SMBG readings in period of time k. -
34. The system of claim 32, wherein said deviation contrasts are computed as
-
X k - Y k SD 1 where Yk is the average of the mean SMBG readings in the periods of time other than k, Xk represents the average SMBG readings in period of time k, and SD1 represents an estimate of the standard deviation of Xk−
Yk.
-
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35. The system of claim 30, wherein said composite probability comprises probability of exceeding an absolute threshold and probability of exceeding a relative personal threshold.
-
36. The system of claim 30, wherein said composite probability is computed as
CPk(α- 1)=Pk(α
1).Φ
(tk)where Pk(α
1) represents the probability of average SMBG in each said period of time to exceed preset threshold level α
1, Φ
(tk) represents the probability of said average SMBG data in each said period of time to be higher than average SMBG data of rest of said periods of time.
- 1)=Pk(α
-
37. The system of claim 36, wherein said Φ
- (tk) is the distribution function of a central normal distribution.
-
38. The system of claim 30, wherein said composite probability is computed as
CPk(α- 1)=Pk(α
1).Φ
(tk)where Pk(α
1) represents the probability of average SMBG in each said period of time to exceed preset threshold level α
1, Φ
(tk) represents the probability of said average SMBG data in each said period of time to be higher than a grand mean.
- 1)=Pk(α
-
39. The system of claim 38, wherein said Φ
- (tk) is the distribution function of a central normal distribution.
-
40. The system of claim 30, wherein the calculation of said composite probabilities comprises calculating probability of said average SMBG data in each said period of time to be higher than average SMBG data of rest of said periods of time.
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41. The system of claim 30, wherein the calculation of said composite probabilities comprise calculating probability of said average SMBG data in each said period of time to be higher than a grand mean.
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42. The system of claim 29, wherein said plurality of SMBG readings comprises SMBG data from about two to six weeks of monitoring together with the time of each reading.
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43. The system of claim 29, wherein each said period of time has a predetermined number of SMBG data points.
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44. The system of claim 43, wherein said predetermined number of SMBG data points is at least about five for each said period of time.
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45. The system of claim 29, wherein said periods of time comprises splitting twenty-four hour days into time bins with predetermined durations.
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46. The system of claim 45, wherein said predetermined durations is between two to eight hours.
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47. The system of claim 45, wherein said predetermined durations is fewer than twenty-four hours.
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48. The system of claim 29, wherein said subsequent period of time comprises a next period of time.
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49. The system of claim 29, wherein indication of said risk for hyperglycemia comprises issuing a message indicating a pattern of high blood sugar for a subsequent period of time.
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50. The system of claim 49, wherein said message indicating a pattern of high blood glucose is received immediately by a user prior to said subsequent period of time.
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51. The system of claim 49, wherein said subsequent period of time comprises a next period of time.
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52. The system of claim 29, wherein indication of said risk for hyperglycemia comprises issuing a message indicating a pattern of high blood sugar within about 24 hours of said acquisition of plurality of SMBG data points.
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53. The system of claim 29, wherein indication of said risk for hyperglycemia comprises issuing a message indicating a pattern of high blood sugar within about 12 hours of said acquisition of plurality of SMBG data points.
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54. The system of claim 29, wherein indication of said risk for hyperglycemia comprises issuing a message indicating a pattern of high blood sugar within about 6 hours of said acquisition of plurality of SMBG data points.
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55. The system of claim 29, wherein indication of said risk for hyperglycemia comprises issuing a message indicating a pattern of high blood sugar at the completion of the above claimed steps.
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56. The system of claim 29, wherein the indication of said risk of hyperglycemia occurs near contemporaneously to the latest SMBG testing.
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57. The system of claim 29, further comprising a display module, said display module displaying message to the user in the event of risk for hyperglycemia.
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265. The system of claim 29, wherein the indication of said risk of hyperglycemia comprises issuing a message indicating a pattern of hyperglycemia, wherein the issuance occurs contemporaneously to a user-initiated action or at a predetermined time.
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266. The system of claim 29, wherein indication of said risk for hyperglycemia comprises issuing a message indicating a pattern of hyperglycemia, wherein the issuance occurs in real time or at a predetermined time.
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267. The system of claim 265, wherein said user-initiated action is the acquisition of one or more SMBG data points.
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268. The system of claim 265 or 266, wherein said predetermined time is within 24 hours of the acquisition of one or more SMBG data points.
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30. The system of claim 29, wherein said evaluation comprising:
-
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58. A computer program product comprising a computer useable medium having computer program logic for enabling at least one processor in a computer system to identify and/or predict patterns of hyperglycemia of a user, said computer program logic comprising:
-
acquiring plurality of SMBG data points; classifying said SMBG data points within periods of time with predetermined durations; evaluating glucose values in each period of time; and indicating risk of hyperglycemia for a subsequent period of time based on said evaluation. - View Dependent Claims (59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 269, 270, 271, 272)
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59. The computer program product of claim 58, wherein said evaluation comprising:
-
determining individual deviations towards hyperglycemia based on said glucose values; determining a composite probability in each said period of time based on individual and absolute deviations; and comparing said composite probability in each period of time against a preset threshold.
-
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60. The computer program product of claim 59, wherein the determination of said deviations comprises calculating the average and standard deviation of SMBG for each said period of time.
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61. The computer program product of claim 59, wherein the determination of said deviations comprises calculating deviation contrasts for each said period of time.
-
62. The computer program product of claim 61, wherein said deviation contrasts are computed as
where Xk represents the average SMBG readings in period of time k, X represents the mean of all the SMBG readings, SD represents the standard deviation of all SMBG readings, SDk represents the standard deviation of SMBG readings in period of time k, N represents the total number of SMBG readings, and Nk represents the number of SMBG readings in period of time k. -
63. The computer program product of claim 61, wherein said deviation contrasts are computed as
-
X k - Y k SD 1 where Yk is the average of the mean SMBG readings in the periods of time other than k, Xk represents the average SMBG readings in period of time k, and SD1 represents an estimate of the standard deviation of Xk−
Yk.
-
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64. The computer program product of claim 59, wherein said composite probability comprises probability of exceeding an absolute threshold and probability of exceeding a relative personal threshold.
-
65. The computer program product of claim 59, wherein said composite probability is computed as
CPk(α- 1)=Pk(α
1).Φ
(tk)where Pk(α
1) represents the probability of average SMBG in each said period of time to exceed preset threshold level α
1, Φ
(tk) represents the probability of said average SMBG data in each said period of time to be higher than average SMBG data of rest of said periods of time.
- 1)=Pk(α
-
66. The computer program product of claim 65, wherein said Φ
- (tk) is the distribution function of a central normal distribution.
-
67. The computer program product of claim 59, wherein said composite probability is computed as
CPk(α- 1)=Pk(α
1).Φ
(tk)where Pk(α
1) represents the probability of average SMBG in each said period of time to exceed preset threshold level α
1, Φ
(tk) represents the probability of said average SMBG data in each said period of time to be higher than a grand mean.
- 1)=Pk(α
-
68. The computer program product of claim 67, wherein said Φ
- (tk) is the distribution function of a central normal distribution.
-
69. The computer program product of claim 59, wherein the calculation of said composite probabilities comprises calculating probability of said average SMBG data in each said period of time to be higher than average SMBG data of rest of said periods of time.
-
70. The computer program product of claim 59, wherein the calculation of said composite probabilities comprise calculating probability of said average SMBG data in each said period of time to be higher than a grand mean.
-
71. The computer program product of claim 58, wherein said plurality of SMBG readings comprises SMBG data from about two to six weeks of monitoring together with the time of each reading.
-
72. The computer program product of claim 58, wherein each said period of time has a predetermined number of SMBG data points.
-
73. The computer program product of claim 72, wherein said predetermined number of SMBG data points is at least about five for each said period of time.
-
74. The computer program product of claim 58, wherein said periods of time comprises splitting twenty-four hour days into time bins with predetermined durations.
-
75. The computer program product of claim 74, wherein said predetermined durations is between two to eight hours.
-
76. The computer program product of claim 74, wherein said predetermined durations is fewer than twenty-four hours.
-
77. The computer program product of claim 58, wherein said subsequent period of time comprises a next period of time.
-
78. The computer program product of claim 58, wherein indication of said risk for hyperglycemia comprises issuing a message indicating a pattern of high blood sugar for a subsequent period of time.
-
79. The computer program product of claim 78, wherein said message indicating a pattern of high blood glucose is received immediately by a user prior to said subsequent period of time.
-
80. The computer program product of claim 78, wherein said subsequent period of time comprises a next period of time.
-
81. The computer program product of claim 58, wherein indication of said risk for hyperglycemia comprises issuing a message indicating a pattern of high blood sugar within about 24 hours of said acquisition of plurality of SMBG data points.
-
82. The computer program product of claim 58, wherein indication of said risk for hyperglycemia comprises issuing a message indicating a pattern of high blood sugar within about 12 hours of said acquisition of plurality of SMBG data points.
-
83. The computer program product of claim 58, wherein indication of said risk for hyperglycemia comprises issuing a message indicating a pattern of high blood sugar within about 6 hours of said acquisition of plurality of SMBG data points.
-
84. The computer program product of claim 58, wherein indication of said risk for hyperglycemia comprises issuing a message indicating a pattern of high blood sugar at the completion of the above claimed steps.
-
85. The computer program product of claim 58, wherein the indication of said risk of hyperglycemia occurs near contemporaneously to the latest SMBG testing.
-
86. The computer program product of claim 58, said computer logic further comprising displaying message to the user in the event of risk for hyperglycemia.
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269. The computer program product of claim 58, wherein the indication of said risk of hyperglycemia comprises issuing a message indicating a pattern of hyperglycemia, wherein the issuance occurs contemporaneously to a user-initiated action or at a predetermined time.
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270. The computer program product of claim 58, wherein indication of said risk for hyperglycemia comprises issuing a message indicating a pattern of hyperglycemia, wherein the issuance occurs in real time or at a predetermined time.
-
271. The computer program product of claim 269, wherein said user-initiated action is the acquisition of one or more SMBG data points.
-
272. The computer program product of claim 269 or 270, wherein said predetermined time is within 24 hours of the acquisition of one or more SMBG data points.
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59. The computer program product of claim 58, wherein said evaluation comprising:
-
-
87. A method for identifying and/or predicting patterns of hypoglycemia of a user, said method comprising:
-
acquiring plurality of SMBG data points; classifying said SMBG data points within periods of time with predetermined durations; evaluating glucose values in each period of time; and indicating risk of hypoglycemia for a subsequent period of time based on said evaluation. - View Dependent Claims (88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 273, 274, 275, 276)
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88. The method of claim 87, wherein said evaluation comprising:
-
determining individual deviations towards hypoglycemia based on said glucose values; determining a composite probability in each said period of time based on individual and absolute deviations; and comparing said composite probability in each period of time against a preset threshold.
-
-
89. The method of claim 88, wherein the determination of said deviations comprises calculating the average and standard deviation of SMBG for each said period of time.
-
90. The method of claim 88, wherein the determination of said deviations comprises calculating deviation contrasts for each said period of time.
-
91. The method of claim 90, wherein said deviation contrasts are computed as
where Xk represents the average SMBG readings in period of time k, X represents the mean of all the SMBG readings, SD represents the standard deviation of all SMBG readings, SDk represents the standard deviation of SMBG readings in period of time k, N represents the total number of SMBG readings, and Nk represents the number of SMBG readings in period of time k. -
92. The method of claim 90, wherein said deviation contrasts are computed as
-
X k - Y k SD 1 where Yk is the average of the mean SMBG readings in the periods of time other than k, Xk represents the average SMBG readings in period of time k, and SD1 represents an estimate of the standard deviation of Xk−
Yk.
-
-
93. The method of claim 88, wherein said composite probability comprises probability of blood glucose being lower than an absolute threshold and probability of blood glucose being lower than a relative personal threshold.
-
94. The method of claim 88, wherein said composite probability is computed as
CPk(α- 1)=Pk(α
1).Φ
(tk)where Pk(α
1) represents the probability of average SMBG in each said period of time to be lower than preset threshold level α
1, Φ
(tk) represents the probability of said average SMBG data in each said period of time to be lower than average SMBG data of rest of said periods of time.
- 1)=Pk(α
-
95. The method of claim 94, wherein said Φ
- (tk) is the distribution function of a central normal distribution.
-
96. The method of claim 88, wherein said composite probability is computed as
CPk(α- 1)=Pk(α
1).Φ
(tk)where Pk(α
1) represents the probability of average SMBG in each said period of time to be lower than preset threshold level α
1, Φ
(tk) represents the probability of said average SMBG data in each said period of time to be lower than a grand mean.
- 1)=Pk(α
-
97. The method of claim 96, wherein said Φ
- (tk) is the distribution function of a central normal distribution.
-
98. The method of claim 88, wherein the calculation of said composite probabilities comprises calculating probability of said average SMBG data in each said period of time to be lower than average SMBG data of rest of said periods of time.
-
99. The method of claim 88, wherein the calculation of said composite probabilities comprise calculating probability of said average SMBG data in each said period of time to be lower than a grand mean.
-
100. The method of claim 87, wherein said plurality of SMBG readings comprises SMBG data from about two to six weeks of monitoring together with the time of each reading.
-
101. The method of claim 87, wherein each said period of time has a predetermined number of SMBG data points.
-
102. The method of claim 101, wherein said predetermined number of SMBG data points is at least about five for each said period of time.
-
103. The method of claim 87, wherein said periods of time comprises splitting twenty-four hour days into time bins with predetermined durations.
-
104. The method of claim 103, wherein said predetermined durations is between two to eight hours.
-
105. The method of claim 103, wherein said predetermined durations is fewer than twenty-four hours.
-
106. The method of claim 87, wherein said subsequent period of time comprises a next period of time.
-
107. The method of claim 87, wherein indication of said risk for hypoglycemia comprises issuing a message indicating a pattern of low blood sugar for a subsequent period of time.
-
108. The method of claim 107, wherein said message indicating a pattern of low blood glucose is received immediately by a user prior to said subsequent period of time.
-
109. The method of claim 107, wherein said subsequent period of time comprises a next period of time.
-
110. The method of claim 87, wherein indication of said risk for hypoglycemia comprises issuing a message indicating a pattern of low blood sugar within about 24 hours of said acquisition of plurality of SMBG data points.
-
111. The method of claim 87, wherein indication of said risk for hypoglycemia comprises issuing a message indicating a pattern of low blood sugar within about 12 hours of said acquisition of plurality of SMBG data points.
-
112. The method of claim 87, wherein indication of said risk for hypoglycemia comprises issuing a message indicating a pattern of low blood sugar within about 6 hours of said acquisition of plurality of SMBG data points.
-
113. The method of claim 87, wherein indication of said risk for hypoglycemia comprises issuing a message indicating a pattern of low blood sugar at the completion of the above claimed steps.
-
114. The method of claim 87, wherein the indication of said risk of hypoglycemia occurs near contemporaneously to the latest SMBG testing.
-
273. The method of claim 87, wherein the indication of said risk of hypoglycemia comprises issuing a message indicating a pattern of hypoglycemia, wherein the issuance occurs contemporaneously to a user-initiated action or at a predetermined time.
-
274. The method of claim 87, wherein indication of said risk for hypoglycemia comprises issuing a message indicating a pattern of hypoglycemia, wherein the issuance occurs in real time or at a predetermined time.
-
275. The method of claim 273, wherein said user-initiated action is the acquisition of one or more SMBG data points.
-
276. The method of claim 273 or 274, wherein said predetermined time is within 24 hours of the acquisition of one or more SMBG data points.
-
88. The method of claim 87, wherein said evaluation comprising:
-
-
115. A system for identifying and/or predicting patterns of hypoglycemia of a user, said system comprising:
-
an acquisition module acquiring plurality of SMBG data points; and a processor programmed to; classify said SMBG data points within periods of time with predetermined durations; evaluate glucose values in each period of time; and indicate risk of hypoglycemia for a subsequent period of time based on said evaluation. - View Dependent Claims (116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 277, 278, 279, 280)
-
116. The system of claim 115, wherein said evaluation comprising:
-
determining individual deviations towards hypoglycemia based on said glucose values; determining a composite probability in each said period of time based on individual and absolute deviations; and comparing said composite probability in each period of time against a preset threshold.
-
-
117. The system of claim 116, wherein the determination of said deviations comprises calculating the average and standard deviation of SMBG for each said period of time.
-
118. The system of claim 116, wherein the determination of said deviations comprises calculating deviation contrasts for each said period of time.
-
119. The system of claim 118, wherein said deviation contrasts are computed as
where Xk represents the average SMBG readings in period of time k, X represents the mean of all the SMBG readings, SD represents the standard deviation of all SMBG readings, SDk represents the standard deviation of SMBG readings in period of time k, N represents the total number of SMBG readings, and Nk represents the number of SMBG readings in period of time k. -
120. The system of claim 118, wherein said deviation contrasts are computed as
-
X k - Y k SD 1 where Yk is the average of the mean SMBG readings in the periods of time other than k, Xk represents the average SMBG readings in period of time k, and SD1 represents an estimate of the standard deviation of Xk−
Yk.
-
-
121. The system of claim 116, wherein said composite probability comprises probability of blood glucose being lower than an absolute threshold and probability of blood glucose being lower than a relative personal threshold.
-
122. The system of claim 116, wherein said composite probability is computed as
CPk(α- 1)=Pk(α
1).Φ
(tk)where Pk(α
1) represents the probability of average SMBG in each said period of time to be lower than preset threshold level α
1, Φ
(tk) represents the probability of said average SMBG data in each said period of time to be lower than average SMBG data of rest of said periods of time.
- 1)=Pk(α
-
123. The system of claim 122, wherein said Φ
- (tk) is the distribution function of a central normal distribution.
-
124. The system of claim 116, wherein said composite probability is computed as
CPk(α- 1)=Pk(α
1).Φ
(tk)where Pk(α
1) represents the probability of average SMBG in each said period of time to be lower than preset threshold level α
1, Φ
(tk) represents the probability of said average SMBG data in each said period of time to be lower than a grand mean.
- 1)=Pk(α
-
125. The system of claim 124, wherein said Φ
- (tk) is the distribution function of a central normal distribution.
-
126. The system of claim 116, wherein the calculation of said composite probabilities comprises calculating probability of said average SMBG data in each said period of time to be lower than average SMBG data of rest of said periods of time.
-
127. The system of claim 116, wherein the calculation of said composite probabilities comprise calculating probability of said average SMBG data in each said period of time to be lower than a grand mean.
-
128. The system of claim 115, wherein said plurality of SMBG readings comprises SMBG data from about two to six weeks of monitoring together with the time of each reading.
-
129. The system of claim 115, wherein each said period of time has a predetermined number of SMBG data points.
-
130. The system of claim 129, wherein said predetermined number of SMBG data points is at least about five for each said period of time.
-
131. The system of claim 115, wherein said periods of time comprises splitting twenty-four hour days into time bins with predetermined durations.
-
132. The system of claim 131, wherein said predetermined durations is between two to eight hours.
-
133. The system of claim 131, wherein said predetermined durations is fewer than twenty-four hours.
-
134. The system of claim 115, wherein said subsequent period of time comprises a next period of time.
-
135. The system of claim 115, wherein indication of said risk for hypoglycemia comprises issuing a message indicating a pattern of low blood sugar for a subsequent period of time.
-
136. The system of claim 135, wherein said message indicating a pattern of low blood glucose is received immediately by a user prior to said subsequent period of time.
-
137. The system of claim 135, wherein said subsequent period of time comprises a next period of time.
-
138. The system of claim 115, wherein indication of said risk for hypoglycemia comprises issuing a message indicating a pattern of low blood sugar within about 24 hours of said acquisition of plurality of SMBG data points.
-
139. The system of claim 115, wherein indication of said risk for hypoglycemia comprises issuing a message indicating a pattern of low blood sugar within about 12 hours of said acquisition of plurality of SMBG data points.
-
140. The system of claim 115, wherein indication of said risk for hypoglycemia comprises issuing a message indicating a pattern of low blood sugar within about 6 hours of said acquisition of plurality of SMBG data points.
-
141. The system of claim 115, wherein indication of said risk for hypoglycemia comprises issuing a message indicating a pattern of low blood sugar at the completion of the above claimed steps.
-
142. The system of claim 115, wherein the indication of said risk of hyperglycemia occurs near contemporaneously to the latest SMBG testing.
-
143. The system of claim 115, further comprising a display module, said display module displaying message to the user in the event of risk for hypoglycemia.
-
277. The system of claim 115, wherein the indication of said risk of hyperglycemia comprises issuing a message indicating a pattern of hypoglycemia, wherein the issuance occurs contemporaneously to a user-initiated action or at a predetermined time.
-
278. The system of claim 115, wherein indication of said risk for hypoglycemia comprises issuing a message indicating a pattern of hypoglycemia, wherein the issuance occurs in real time or at a predetermined time.
-
279. The system of claim 277, wherein said user-initiated action is the acquisition of one or more SMBG data points.
-
280. The system of claim 277 or 278, wherein said predetermined time is within 24 hours of the acquisition of one or more SMBG data points.
-
116. The system of claim 115, wherein said evaluation comprising:
-
-
144. A computer program product comprising a computer useable medium having computer program logic for enabling at least one processor in a computer system to identify and/or predict patterns of hypoglycemia of a user, said computer program logic comprising:
-
acquiring plurality of SMBG data points; classifying said SMBG data points within periods of time with predetermined durations; evaluating glucose values in each period of time; and indicating risk of hypoglycemia for a subsequent period of time based on said evaluation. - View Dependent Claims (145, 146, 147, 148, 149, 150, 151, 152, 153, 154, 155, 156, 157, 158, 159, 160, 161, 162, 163, 164, 165, 166, 167, 168, 169, 170, 171, 172, 281, 282, 283, 284)
-
145. The computer program product of claim 144, wherein said evaluation comprising:
-
determining individual deviations towards hypoglycemia based on said glucose values; determining a composite probability in each said period of time based on individual and absolute deviations; and comparing said composite probability in each period of time against a preset threshold.
-
-
146. The computer program product of claim 145, wherein the determination of said deviations comprises calculating the average and standard deviation of SMBG for each said period of time.
-
147. The computer program product of claim 145, wherein the determination of said deviations comprises calculating deviation contrasts for each said period of time.
-
148. The computer program product of claim 147, wherein said deviation contrasts are computed as
where Xk represents the average SMBG readings in period of time k, X represents the mean of all the SMBG readings, SD represents the standard deviation of all SMBG readings, SDk represents the standard deviation of SMBG readings in period of time k, N represents the total number of SMBG readings, and Nk represents the number of SMBG readings in period of time k. -
149. The computer program product of claim 147, wherein said deviation contrasts are computed as
-
X k - Y k SD 1 where Yk is the average of the mean SMBG readings in the periods of time other than k, Xk represents the average SMBG readings in period of time k, and SD1 represents an estimate of the standard deviation of Xk−
Yk.
-
-
150. The computer program product of claim 145, wherein said composite probability comprises probability of blood glucose being lower than an absolute threshold and probability of blood glucose being lower than a relative personal threshold.
-
151. The computer program product of claim 145, wherein said composite probability is computed as
CPk(α- 1)=Pk(α
1).Φ
(tk)where Pk(α
) represents the probability of average SMBG in each said period of time to be lower than preset threshold level α
1, Φ
(tk) represents the probability of said average SMBG data in each said period of time to be lower than average SMBG data of rest of said periods of time.
- 1)=Pk(α
-
152. The computer program product of claim 151, wherein said Φ
- (tk) is the distribution function of a central normal distribution.
-
153. The computer program product of claim 145, wherein said composite probability is computed as
CPk(α- 1)=Pk(α
1).Φ
(tk)where Pk(α
1) represents the probability of average SMBG in each said period of time to be lower than preset threshold level α
1, Φ
(tk) represents the probability of said average SMBG data in each said period of time to be lower than a grand mean.
- 1)=Pk(α
-
154. The computer program product of claim 153, wherein said Φ
- (tk) is the distribution function of a central normal distribution.
-
155. The computer program product of claim 145, wherein the calculation of said composite probabilities comprises calculating probability of said average SMBG data in each said period of time to be lower than average SMBG data of rest of said periods of time.
-
156. The computer program product of claim 145, wherein the calculation of said composite probabilities comprise calculating probability of said average SMBG data in each said period of time to be lower than a grand mean.
-
157. The computer program product of claim 144, wherein said plurality of SMBG readings comprises SMBG data from about two to six weeks of monitoring together with the time of each reading.
-
158. The computer program product of claim 144, wherein each said period of time has a predetermined number of SMBG data points.
-
159. The computer program product of claim 158, wherein said predetermined number of SMBG data points is at least about five for each said period of time.
-
160. The computer program product of claim 144, wherein said periods of time comprises splitting twenty-four hour days into time bins with predetermined durations.
-
161. The computer program product of claim 160, wherein said predetermined durations is between two to eight hours.
-
162. The computer program product of claim 160, wherein said predetermined durations is fewer than twenty-four hours.
-
163. The computer program product of claim 144, wherein said subsequent period of time comprises a next period of time.
-
164. The computer program product of claim 144, wherein indication of said risk for hypoglycemia comprises issuing a message indicating a pattern of low blood sugar for a subsequent period of time.
-
165. The computer program product of claim 164, wherein said message indicating a pattern of low blood glucose is received immediately by a user prior to said subsequent period of time.
-
166. The computer program product of claim 164, wherein said subsequent period of time comprises a next period of time.
-
167. The computer program product of claim 144, wherein indication of said risk for hypoglycemia comprises issuing a message indicating a pattern of low blood sugar within about 24 hours of said acquisition of plurality of SMBG data points.
-
168. The computer program product of claim 144, wherein indication of said risk for hypoglycemia comprises issuing a message indicating a pattern of low blood sugar within about 12 hours of said acquisition of plurality of SMBG data points.
-
169. The computer program product of claim 144, wherein indication of said risk for hypoglycemia comprises issuing a message indicating a pattern of low blood sugar within about 6 hours of said acquisition of plurality of SMBG data points.
-
170. The computer program product of claim 144, wherein indication of said risk for hypoglycemia comprises issuing a message indicating a pattern of low blood sugar at the completion of the above claimed steps.
-
171. The computer program product of claim 144, wherein the indication of said risk of hypoglycemia occurs near contemporaneously to the latest SMBG testing.
-
172. The computer program product of claim 144, further comprising a display module, said display module displaying message to the user in the event of risk for hypoglycemia.
-
281. The computer program product of claim 144, wherein the indication of said risk of hypoglycemia comprises issuing a message indicating a pattern of hypoglycemia, wherein the issuance occurs contemporaneously to a user-initiated action or at a predetermined time.
-
282. The computer program product of claim 144, wherein indication of said risk for hypoglycemia comprises issuing a message indicating a pattern of hypoglycemia, wherein the issuance occurs in real time or at a predetermined time.
-
283. The computer program product of claim 281, wherein said user-initiated action is the acquisition of one or more SMBG data points.
-
284. The computer program product of claim 281 or 282, wherein said predetermined time is within 24 hours of the acquisition of on or more SMBG data points.
-
145. The computer program product of claim 144, wherein said evaluation comprising:
-
-
173. A method for identifying and predicting patterns of high glucose variability of a user, said method comprising:
-
acquiring plurality of SMBG data points; classifying said SMBG data points within periods of time with predetermined durations; evaluating blood glucose variability in each said period of time; and indicating risk of higher variability for a subsequent period of time based on said evaluation. - View Dependent Claims (174, 175, 176, 177, 178, 179, 180, 181, 182, 183, 184, 185, 186, 187, 188, 189, 190, 191, 192, 193, 194, 195, 196, 285, 286, 287, 288, 289)
-
174. The method of claim 173, wherein said evaluation comprising:
-
determining individual probability of each period of time having higher variability than other said periods of time; determining an overall marker of variability with or without transforming said SMBG data points according to a transforming function; and comparing said individual probability of each said period of time and said overall marker of variability against preset thresholds.
-
-
175. The method of claim 174, wherein said transforming function is computed as
f(BG,a,b)=c. [(ln(BG))a−- b}]
where if BG is measured in mg/dl, then a=1.084, b=5.381, c=1.509 and if BG is measured in mmol/l, then a=1.026, b=1.861 and c=1.794.
- b}]
-
176. The method of claim 174, wherein said determination of individual probability comprises of calculating at least one risk deviation for at least some of the each of the transformed plurality of SMBG data points.
-
177. The method of claim 176, wherein said risk deviations comprise of calculating ratios of standard risk deviations.
-
178. The method of claim 177, wherein said standard risk deviations are computed as
-
∑ i = 1 N k ( f ( X ki ) - f X _ k ) 2 , where f X _ k = 1 N k ∑ i = 1 N k fX ki . where RSDk represents the risk standard deviation of SMBG readings in period of time k, X k represents the average SMBG readings in period of time k, Xki represents the number of readings that fell into period of time k on day i of the last 30 days of SMBG readings, N represents the total number of SMBG readings, and Nk represents the number of SMBG readings in period of time k.
-
-
179. The method of claim 177, wherein said ratio has approximately central normal distribution and is computed as
Zk=5*(RSDk/RSD−- 1)
where RSDk represents the risk standard deviation of SMBG readings in period of time k, and RSD represents the risk standard deviation of all SMBG readings.
- 1)
-
180. The method of claim 174, wherein said probability of a period of time having higher variability than other periods of time is computed as
P(Zk>- 0)=Φ
(Zk),wherein Φ
is the distribution function of central normal distribution.
- 0)=Φ
-
181. The method of claim 174, wherein said overall marker of variability comprise of an ADRR.
-
182. The method of claim 181, wherein said ADRR is computed as
-
∑ i = 1 M [ LR i + HR i ] , where LRi represents a maximal hypoglycemic risk value for period of time with a predetermined duration i, HRi represents a maximal hyperglycemic risk value for period of time with predetermined duration i, LRi+HRi represents a calculated risk range for a period of time with predetermined duration i, and the plurality of blood glucose data points are collected on periods of time with predetermined duration i=1, 2, . . . , M.
-
-
183. The method of claim 173, wherein said plurality of SMBG readings comprises SMBG data from about two to six weeks of monitoring together with the time of each reading.
-
184. The method of claim 173, wherein each said period of time has a predetermined number of SMBG data points.
-
185. The method of claim 184, wherein said predetermined number of SMBG data points is at least about five for each said period of time.
-
186. The method of claim 173, wherein said periods of time comprises splitting twenty-four hour days into time bins with predetermined durations.
-
187. The method of claim 186, wherein said predetermined durations is between two to eight hours.
-
188. The method of claim 186, wherein said predetermined durations is fewer than twenty-four hours.
-
189. The method of claim 173, wherein said subsequent period of time comprises a next period of time.
-
190. The method of claim 173, wherein indication of said risk for high variability comprises issuing a message indicating a pattern of high blood glucose variability for a subsequent time period.
-
191. The method of claim 173, wherein said message indicating risk of higher variability is received immediately by a user prior to said subsequent period of time.
-
192. The method of claim 190, wherein said subsequent period of time comprises a next period of time.
-
193. The method of claim 173, wherein indication of said risk for high variability comprises issuing a message indicating a pattern of high variability within about 24 hours of said acquisition of plurality of SMBG data points.
-
194. The method of claim 173, wherein indication of said risk for high variability comprises issuing a message indicating a pattern of high variability within about 12 hours of said acquisition of plurality of SMBG data points.
-
195. The method of claim 173, wherein indication of said risk for high variability comprises issuing a message indicating a pattern of high variability within about 6 hours of said acquisition of plurality of SMBG data points.
-
196. The method of claim 173, wherein indication of said risk for high variability comprises issuing a message indicating a pattern of high variability at the completion of the above claimed steps.
-
285. The method of claim 173, wherein indication of said risk for high variability comprises issuing a message indicating a pattern of high variability occurs near contemporaneously to said acquisition of plurality of said SMBG data points.
-
286. The method of claim 173, wherein indication of said risk for high variability comprises issuing a message indicating a pattern of high variability, wherein the issuance occurs contemporaneously to a user-initiated action or at a predetermined time.
-
287. The method of claim 173, wherein indication of said risk for high variability comprises issuing a message indicating a pattern of high variability, wherein the issuance occurs in real time or at a predetermined time.
-
288. The method of claim 286, wherein said user-initiated action is the acquisition of one or more SMBG data points.
-
289. The method of claim 286 or 287, wherein said predetermined time is within 24 hours of the acquisition of one or more SMBG data points.
-
174. The method of claim 173, wherein said evaluation comprising:
-
-
197. A system for identifying and/or predicting patterns of high glucose variability of a user, said system comprising:
-
an acquisition module acquiring plurality of SMBG data points; and a processor programmed to; classifying said SMBG data points within periods of time with predetermined durations; evaluating blood glucose variability in each said period of time; and indicating risk of higher variability for a subsequent period of time based on said evaluation. - View Dependent Claims (198, 199, 200, 201, 202, 203, 204, 205, 206, 207, 208, 209, 210, 211, 212, 213, 214, 215, 216, 217, 218, 219, 220, 221, 222, 290, 291, 292, 293)
-
198. The system of claim 197, wherein said evaluation comprising:
-
determining individual probability of each period of time having higher variability than other said periods of time; determining an overall marker of variability with or without transforming said SMBG data points according to a transforming function; and comparing said individual probability of each said period of time and said overall marker of variability against preset thresholds.
-
-
199. The system of claim 198, wherein said transforming function is computed as
f(BG,a,b)=c. [(ln(BG))a−- b}]
where if BG is measured in mg/dl, then a=1.084, b=5.381, c=1.509 and if BG is measured in mmol/l, then a=1.026, b=1.861 and c=1.794.
- b}]
-
200. The system of claim 198, wherein said determination of individual probability comprises of calculating at least one risk deviation for at least some of the each of the transformed plurality of SMBG data points.
-
201. The system of claim 200, wherein said risk deviations comprise of calculating ratios of standard risk deviations.
-
202. The system of claim 201, wherein said standard risk deviations are computed as
-
∑ i = 1 N k ( f ( X ki ) - f X _ k ) 2 , where f X _ k = 1 N k ∑ i = 1 N k fX ki . where RSDk represents the risk standard deviation of SMBG readings in period of time k, X k represents the average SMBG readings in period of time k, Xki represents the number of readings that fell into period of time k on day i of the last 30 days of SMBG readings, N represents the total number of SMBG readings, and Nk represents the number of SMBG readings in period of time k.
-
-
203. The system of claim 201, wherein said ratio has approximately central normal distribution and is computed as Zk=5*(RSDk/RSD−
- 1) where RSDk represents the risk standard deviation of SMBG readings in period of time k, and RSD represents the risk standard deviation of all SMBG readings.
-
204. The system of claim 198, wherein said probability of a period of time having higher variability than other periods of time is computed as P (Zk>
- 0)=Φ
(Zk), where Φ
is the distribution function of central normal distribution.
- 0)=Φ
-
205. The system of claim 198, wherein said overall marker of variability comprise of an ADRR.
-
206. The system of claim 205, wherein said ADRR is computed as
-
∑ i = 1 M [ LR i + HR i ] , where LRi represents a maximal hypoglycemic risk value for period of time with a predetermined duration i, HRi represents a maximal hyperglycemic risk value for period of time with predetermined duration i, LRi+HRi represents a calculated risk range for a period of time with predetermined duration i, and the plurality of blood glucose data points are collected on periods of time with predetermined duration i=1, 2, . . . , M.
-
-
207. The system of claim 197, wherein said plurality of SMBG readings comprises SMBG data from about two to six weeks of monitoring together with the time of each reading.
-
208. The system of claim 197, wherein each said period of time has a predetermined number of SMBG data points.
-
209. The system of claim 208, wherein said predetermined number of SMBG data points is at least about five for each said period of time.
-
210. The system of claim 197, wherein said periods of time comprises splitting twenty-four hour days into time bins with predetermined durations.
-
211. The system of claim 210, wherein said predetermined durations is between two to eight hours.
-
212. The system of claim 210, wherein said predetermined durations is fewer than twenty-four hours.
-
213. The system of claim 197, wherein said subsequent period of time comprises a next period of time.
-
214. The system of claim 197, wherein indication of said risk for high variability comprises issuing a message indicating a pattern of high blood glucose variability for a subsequent time period.
-
215. The system of claim 214, wherein said message indicating risk of higher variability is received immediately by a user prior to said subsequent period of time.
-
216. The system of claim 214, wherein said subsequent period of time comprises a next period of time.
-
217. The system of claim 197, wherein indication of said risk for high variability comprises issuing a message indicating a pattern of high variability within about 24 hours of said acquisition of plurality of SMBG data points.
-
218. The system of claim 197, wherein indication of said risk for high variability comprises issuing a message indicating a pattern of high variability within about 12 hours of said acquisition of plurality of SMBG data points.
-
219. The system of claim 197, wherein indication of said risk for high variability comprises issuing a message indicating a pattern of high variability within about 6 hours of said acquisition of plurality of SMBG data points.
-
220. The system of claim 197, wherein indication of said risk for high variability comprises issuing a message indicating a pattern of high variability at the completion of the above claimed steps.
-
221. The system of claim 197, wherein the indication of said risk of high glucose variability occurs near contemporaneously to the latest SMBG testing.
-
222. The system of claim 197, further comprising a display module, said display module displaying message to the user in the event of high risk of glucose variability.
-
290. The system of claim 197, wherein the indication of said risk of high glucose variability comprises issuing a message indicating a pattern of high variability, wherein the issuance occurs contemporaneously to a user-initiated action or at a predetermined time.
-
291. The system of claim 197, wherein indication of said risk for high variability comprises issuing a message indicating a pattern of high variability, wherein the issuance occurs in real time or at a predetermined time.
-
292. The system of claim 290, wherein said user-initiated action is the acquisition of one or more SMBG data points.
-
293. The system of claim 290 or 291, wherein said predetermined time is within 24 hours of the acquisition of one or more SMBG data points.
-
198. The system of claim 197, wherein said evaluation comprising:
-
-
223. A computer program product comprising a computer useable medium having computer program logic for enabling at least one processor in a computer system to identify and/or predict patterns of high glucose variability of a user, said computer program logic comprising:
-
acquiring plurality of SMBG data points; classifying said SMBG data points within periods of time with predetermined durations; evaluating blood glucose variability in each said period of time; and indicating risk of higher variability for a subsequent period of time based on said evaluation. - View Dependent Claims (224, 225, 226, 227, 228, 229, 230, 231, 232, 233, 234, 235, 236, 237, 238, 239, 240, 241, 242, 243, 244, 245, 246, 247, 248, 294, 295, 296, 297)
-
224. The computer program product of claim 223, wherein said evaluation comprising:
-
determining individual probability of each period of time having higher variability than other said periods of time; determining an overall marker of variability with or without transforming said SMBG data points according to a transforming function; and comparing said individual probability of each said period of time and said overall marker of variability against preset thresholds.
-
-
225. The computer program product of claim 224, wherein said transforming function is computed as
f(BG,a,b)=c. [(ln(BG))a−- b}]
where if BG is measured in mg/dl, then a=1.084, b=5.381, c=1.509 and if BG is measured in mmol/l, then a=1.026, b=1.861 and c=1.794.
- b}]
-
226. The computer program product of claim 224, wherein said determination of individual probability comprises of calculating at least one risk deviation for at least some of the each of the transformed plurality of SMBG data points.
-
227. The computer program product of claim 226, wherein said risk deviations comprise of calculating ratios of standard risk deviations.
-
228. The computer program product of claim 227, wherein said standard risk deviations are computed as
-
∑ i = 1 N k ( f ( X ki ) - f X _ k ) 2 , where f X _ k = 1 N k ∑ i = 1 N k fX ki . where RSDk represents the risk standard deviation of SMBG readings in period of time k, X k represents the average SMBG readings in period of time k, Xki represents the number of readings that fell into period of time k on day i of the last 30 days of SMBG readings, N represents the total number of SMBG readings, and Nk represents the number of SMBG readings in period of time k.
-
-
229. The computer program product of claim 227, wherein said ratio has approximately central normal distribution and is computed as
Zk=5*(RSDk/RSD−- 1)
where RSDk represents the risk standard deviation of SMBG readings in period of time k, and RSD represents the risk standard deviation of all SMBG readings.
- 1)
-
230. The computer program product of claim 224, wherein said probability of a period of time having higher variability than other periods of time is computed as
P(Zk>- 0)=Φ
(Zk),wherein Φ
is the distribution function of central normal distribution.
- 0)=Φ
-
231. The computer program product of claim 224, wherein said overall marker of variability comprise of an ADRR.
-
232. The computer program product of claim 231, wherein said ADRR is computed as
-
∑ i = 1 M [ LR i + HR i ] , where LRi represents a maximal hypoglycemic risk value for period of time with a predetermined duration i, HRi represents a maximal hyperglycemic risk value for period of time with predetermined duration i, LRi+HRi represents a calculated risk range for a period of time with predetermined duration i, and the plurality of blood glucose data points are collected on periods of time with predetermined duration i=1, 2, . . . , M.
-
-
233. The computer program product of claim 223, wherein said plurality of SMBG readings comprises SMBG data from about two to six weeks of monitoring together with the time of each reading.
-
234. The computer program product of claim 223, wherein each said period of time has a predetermined number of SMBG data points.
-
235. The computer program product of claim 234, wherein said predetermined number of SMBG data points is at least about five for each said period of time.
-
236. The computer program product of claim 223, wherein said periods of time comprises splitting twenty-four hour days into time bins with predetermined durations.
-
237. The computer program product of claim 236, wherein said predetermined durations is between two to eight hours.
-
238. The computer program product of claim 236, wherein said predetermined durations is fewer than twenty-four hours.
-
239. The computer program product of claim 223, wherein said subsequent period of time comprises a next period of time.
-
240. The computer program product of claim 223, wherein indication of said risk for high variability comprises issuing a message indicating a pattern of high blood glucose variability for a subsequent time period.
-
241. The computer program product of claim 240, wherein said message indicating risk of higher variability is received immediately by a user prior to said subsequent period of time.
-
242. The computer program product of claim 241, wherein said subsequent period of time comprises a next period of time.
-
243. The computer program product of claim 223, wherein indication of said risk for high variability comprises issuing a message indicating a pattern of high variability within about 24 hours of said acquisition of plurality of SMBG data points.
-
244. The computer program product of claim 223, wherein indication of said risk for high variability comprises issuing a message indicating a pattern of high variability within about 12 hours of said acquisition of plurality of SMBG data points.
-
245. The computer program product of claim 223, wherein indication of said risk for high variability comprises issuing a message indicating a pattern of high variability within about 6 hours of said acquisition of plurality of SMBG data points.
-
246. The computer program product of claim 223, wherein indication of said risk for high variability comprises issuing a message indicating a pattern of high variability at the completion of the above claimed steps.
-
247. The computer program product of claim 223, wherein the indication of said risk of high glucose variability occurs near contemporaneously to the latest SMBG testing.
-
248. The computer program product of claim 223, further comprising a display module, said display module displaying message to the user in the event of high risk of glucose variability.
-
294. The computer program product of claim 223, wherein the indication of said risk of high glucose variability comprises issuing a message indicating a pattern of high variability, wherein the issuance occurs contemporaneously to a user-initiated action or at a predetermined time.
-
295. The computer program product of claim 223, wherein indication of said risk for high variability comprises issuing a message indicating a pattern of high variability, wherein the issuance occurs in real time or at a predetermined time.
-
296. The computer program product of claim 294, wherein said user-initiated action is the acquisition of one or more SMBG data points.
-
297. The computer program product of claim 294 or 295, wherein said predetermined time is within 24 hours of the acquisition of one or more SMBG data points.
-
224. The computer program product of claim 223, wherein said evaluation comprising:
-
-
249. A method for identifying patterns of ineffective testing of a user, said computer program product comprising:
-
acquiring plurality of SMBG data points; classifying said SMBG data points within periods of time with predetermined durations; calculating the percentage of SMBG readings in each said period of time; comparing percentage against preset thresholds; and indicating ineffective testing for said period of time. - View Dependent Claims (250, 251, 252)
-
250. The method of claim 249, wherein the indication of ineffective testing comprises issuing a message indicating ineffective testing for said period of time.
-
251. The method of claim 249, wherein said message comprises warning about insufficient testing if said percentage is below a preset threshold.
-
252. The method of claim 249, wherein said message comprises warning about excessive testing if said percentage is above a preset threshold.
-
250. The method of claim 249, wherein the indication of ineffective testing comprises issuing a message indicating ineffective testing for said period of time.
-
-
253. A system for identifying and/or predicting patterns of ineffective testing of a user, said system comprising:
-
an acquisition module acquiring plurality of SMBG data points; and a processor programmed to; classify said SMBG data points within periods of time with predetermined durations; calculate the percentage of SMBG readings in each said period of time; compare percentage against preset thresholds; and indicate ineffective testing for said period of time. - View Dependent Claims (254, 255, 256)
-
254. The system of claim 253, wherein the indication of ineffective testing comprises issuing a message indicating ineffective testing for said period of time.
-
255. The system of claim 253, wherein said message comprises warning about insufficient testing if said percentage is below a preset threshold.
-
256. The system of claim 253, wherein said message comprises warning about excessive testing if said percentage is above a preset threshold.
-
254. The system of claim 253, wherein the indication of ineffective testing comprises issuing a message indicating ineffective testing for said period of time.
-
-
257. A computer program product comprising a computer useable medium having computer program logic for enabling at least one processor in a computer system to identify and/or predict patterns of ineffective testing of a user, said computer program logic comprising:
-
acquiring plurality of SMBG data points; classifying said SMBG data points within periods of time with predetermined durations; calculating the percentage of SMBG readings in each said period of time; comparing percentage against preset thresholds; and indicating ineffective testing for said period of time. - View Dependent Claims (258, 259, 260)
-
258. The computer program product of claim 257, wherein the indication of ineffective testing comprises issuing a message indicating ineffective testing for said period of time.
-
259. The computer program product of claim 257, wherein said message comprises warning about insufficient testing if said percentage is below a preset threshold.
-
260. The computer program product of claim 257, wherein said message comprises warning about excessive testing if said percentage is above a preset threshold.
-
258. The computer program product of claim 257, wherein the indication of ineffective testing comprises issuing a message indicating ineffective testing for said period of time.
-
Specification
- Resources
-
Current AssigneeLifeScan IP Holdings, LLC, University of Virginia Patent Foundation (University of Virginia)
-
Original AssigneeLifescan Incorporated (Duv Holding Corporation), University of Virginia Patent Foundation (University of Virginia)
-
InventorsCoulson, Alan, Kovatchev, Boris P., Price, David, Otto, Erik
-
Application NumberUS11/943,226Publication NumberTime in Patent OfficeDaysField of SearchUS Class Current702/19CPC Class CodesG16H 10/60 for patient-specific data, ...G16H 15/00 ICT specially adapted for m...G16H 20/10 relating to drugs or medica...G16H 50/20 for computer-aided diagnosi...