Monitoring device for management of insulin delivery
First Claim
1. A monitoring system for use with diabetic treatment management, the monitoring system comprising:
- a communication interface configured and operable to permit access to stored raw log data obtained over a certain time and being time spaced data points of glucose measurements, meals consumed and insulin delivery;
a control unit configured for receiving and processing said raw log data, the control unit comprising;
a sectioning module configured to section the raw log data within at least one time window;
the sectioned time window being at least one of Basal data Section (BaS), Meals data Section (MS) and Bolus data Section (BS), each sectioned time window having a starting point and having an end point such that the BaS being selected outside an effect window of either a meal event or an insulin bolus, the MS being selected at a predetermined time ahead of a meal data point, and the starting point of the BS being selected as one of the following;
(a) the end point of the MS or the BaS, and (b) an insulin bolus data point which is outside the MS;
the end point of the BS being selected as one of the following, (i) the starting point of the MS or BaS and (ii) a predetermined time ahead of the insulin bolus data point without any intervening insulin bolus; and
an unsupervised learning controller configured and operable to determine an informative data piece from a residual log data portion of said raw log data, analyze said informative data piece and select a sectioned time window for calculation of an individualized patient'"'"'s profile related data comprising at least one of global insulin pump setting of basal rate, correction factor (CF), carbohydrate ratio (CR) and insulin activity curve parameters, wherein calculation of the basal rate is based on BaS, calculation of at least one of insulin activity curve parameters, correction factor (CF) and carbohydrate ratio (CR) is based on MS, and calculation of the correction factor (CF) or insulin activity curve parameters is based on BS.
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Accused Products
Abstract
Monitoring system and method for use with diabetic treatment management. The system includes: a communication interface configured to permit access to stored raw log data, obtained over a certain time, being indicative of glucose measurements, meals consumed and insulin delivery; and a control unit including an unsupervised learning controller configured to receive and process said raw log data and determine at least one global insulin pump setting of basal rate, correction factor, carbohydrate ratio and insulin activity curve parameters. The system may include a processing unit including a first processor for processing measured data indicative of blood glucose level and generating first processed data, a second processor including at least one fuzzy logic module which receives input parameters corresponding to the measured data, the first processed data and a reference data, and processes the data to produce a qualitative output parameter to determine whether any treatment parameter should be modified.
46 Citations
49 Claims
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1. A monitoring system for use with diabetic treatment management, the monitoring system comprising:
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a communication interface configured and operable to permit access to stored raw log data obtained over a certain time and being time spaced data points of glucose measurements, meals consumed and insulin delivery; a control unit configured for receiving and processing said raw log data, the control unit comprising; a sectioning module configured to section the raw log data within at least one time window;
the sectioned time window being at least one of Basal data Section (BaS), Meals data Section (MS) and Bolus data Section (BS), each sectioned time window having a starting point and having an end point such that the BaS being selected outside an effect window of either a meal event or an insulin bolus, the MS being selected at a predetermined time ahead of a meal data point, and the starting point of the BS being selected as one of the following;
(a) the end point of the MS or the BaS, and (b) an insulin bolus data point which is outside the MS;
the end point of the BS being selected as one of the following, (i) the starting point of the MS or BaS and (ii) a predetermined time ahead of the insulin bolus data point without any intervening insulin bolus; andan unsupervised learning controller configured and operable to determine an informative data piece from a residual log data portion of said raw log data, analyze said informative data piece and select a sectioned time window for calculation of an individualized patient'"'"'s profile related data comprising at least one of global insulin pump setting of basal rate, correction factor (CF), carbohydrate ratio (CR) and insulin activity curve parameters, wherein calculation of the basal rate is based on BaS, calculation of at least one of insulin activity curve parameters, correction factor (CF) and carbohydrate ratio (CR) is based on MS, and calculation of the correction factor (CF) or insulin activity curve parameters is based on BS. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49)
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15. A method for use in determination of insulin pump settings, the method comprising:
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performing unsupervised learning of the insulin pump settings, said unsupervised learning comprising; a) obtaining raw log data input accumulated on one or more glucose monitoring units recording glucose levels of a single treated patient along a certain time; b) sectioning the raw log data to predetermined data sections;
each of the predetermined data sections being at least one of Basal data Section (BaS), Meals data Section (MS) and Bolus data Section (BS), each section having a starting point and having an end point such that the BaS being selected outside an effect window of either a meal event or an insulin bolus, the MS being selected at a predetermined time ahead of a meal data point, and the starting point of the BS being selected as one of the following;
(a) the end point of the MS or the BaS, and (b) an insulin bolus data point which is outside the MS;
the end point of the BS being selected as one of the following, (i) the starting point of the MS or BaS and (ii) a predetermined time ahead of the insulin bolus data point without any intervening insulin bolus;c) determining informative data piece from raw log data input being sectioned to data sections, the informative data piece being determined from said data section; and d) calculating global insulin pump settings from the informative data piece, wherein said settings include at least one parameter of basal plan, Carbohydrate Ratio (CR), Correction Factor (CF) or Active Insulin Function (AIF) wherein calculation of the basal rate is based on BaS, calculation of at least one of insulin activity curve parameters, correction factor (CF) and carbohydrate ratio (CR) is based on MS, and calculation of the correction factor (CF) or insulin activity curve parameters is based on BS. - View Dependent Claims (16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33)
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34. A method for determining an Active Insulin Function (AIF) for use in insulin treatment of a patient, the method comprising:
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a) obtaining raw log data obtained over a certain time and being indicative of glucose measurements of the patient, b) sectioning the raw log data being indicative of glucose measurements, meals events and insulin delivery of the patient to predetermined data sections;
each of the predetermined data sections being at least one of Meals data Section (MS) and Bolus data Section (BS), each section having a starting point and having an end point such that the MS being selected at a predetermined time ahead of a meal data point, and the starting point of the BS being selected as one of the following;
(a) the end point of the MS or the BaS, and (b) an insulin bolus data point which is outside the MS;
the end point of the BS being selected as one of the following, (i) the starting point of the MS or BaS and (ii) a predetermined time ahead of the insulin bolus data point without any intervening insulin bolus;c) obtaining a set of glucose measurements and paired time stamps for the raw log data in the time section; d) normalizing each glucose measurement of the set thereby obtaining a series of normalized glucose measurements and paired time stamp; e) processing said normalized glucose measurements and paired time stamp into a substantially monotonic non-increasing series;
thereby obtaining the Active Insulin Function (AIF).
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35. A control unit for use with diabetic treatment management, the control unit comprising:
- a data processor utility configured and operable as an unsupervised learning controller preprogrammed for processing raw log data input obtained over a certain time and being indicative of glucose measurements, meals events and insulin delivery, said processing comprising sectioning the raw log data to predetermined data sections;
each of the predetermined data sections being at least one of Basal data Section (BaS), Meals data Section (MS) and Bolus data Section (BS), each section having a starting point and having an end point such that the BaS being selected outside an effect window of either a meal event or an insulin bolus, the MS being selected at a predetermined time ahead of a meal data point, and the starting point of the BS being selected as one of the following;
(a) the end point of the MS or the BaS, and (b) an insulin bolus data point which is outside the MS;
the end point of the BS being selected as one of the following, (i) the starting point of the MS or BaS and (ii) a predetermined time ahead of the insulin bolus data point without any intervening insulin bolus;
determining an informative data piece from residual log data portion of said raw log data and selecting said informative data piece for further processing to determine at least one of basal rate, correction factor (CF), carbohydrate ratio (CR) and insulin activity curve parameters, and generating global insulin pump settings wherein calculation of the basal rate is based on BaS, calculation of at least one of insulin activity curve parameters, correction factor (CF) and carbohydrate ratio (CR) is based on MS, and calculation of the correction factor (CF) or insulin activity curve parameters is based on BS.
- a data processor utility configured and operable as an unsupervised learning controller preprogrammed for processing raw log data input obtained over a certain time and being indicative of glucose measurements, meals events and insulin delivery, said processing comprising sectioning the raw log data to predetermined data sections;
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36. A computer program recordable on a storage medium and comprising a machine readable format, the computer program being configured and operable to, when being accessed, carry out the following:
- identifying raw log data input corresponding to a certain time period and comprising glucose measurements, meals events and insulin delivery;
sectioning the raw log data to predetermined data sections;
each of the predetermined data sections being at least one of Basal data Section (BaS), Meals data Section (MS) and Bolus data Section (BS), each section having a starting point and having an end point such that the BaS being selected outside an effect window of either a meal or an insulin bolus, the MS being selected at a predetermined time ahead of a meal data point, and the starting point of the BS being selected as one of the following;
(a) the end point of the MS or the BaS, and (b) an insulin bolus data point which is outside the MS;
the end point of the BS being selected as one of the following, (i) the starting point of the MS or BaS and (ii) a predetermined time ahead of the insulin bolus data point without any intervening insulin bolus;
determining an informative data piece and residual log data portion of said raw log data;
selecting said informative data piece and calculating therefrom at least one of basal rate, correction factor (CF), carbohydrate ratio (CR) and insulin activity curve parameters, and generating output data comprising values for global insulin pump settings wherein calculation of the basal rate is based on BaS, calculation of at least one of insulin activity curve parameters, correction factor (CF) and carbohydrate ratio (CR) is based on MS, and calculation of the correction factor (CF) or insulin activity curve parameters is based on BS.
- identifying raw log data input corresponding to a certain time period and comprising glucose measurements, meals events and insulin delivery;
Specification