# US 2014/0156204 A1 · Method and Apparatus for Providing Glycemic Control > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 2014/0156204 A1 - Document ID: US20140156204A1 - Status: Published application - Kind: A1 - Application number: 14/174,657 - Filed: 2014-02-06 - Published: 2014-06-05 - Earliest claimed: 2008-05-30 - Assignees: Abbott Diabetes Care Inc. - Applicants: Abbott Diabetes Care Inc. - Inventors: Marc Barry Taub; Timothy Christian Dunn; Nathan Christopher Crouther - Web page: https://patentgrep.com/patent/US20140156204A1 ## CPC - A61B 5/14532: {for measuring glucose, e.g. by tissue impedance measurement} - A61B 5/1118: {Determining activity level} - A61B 5/14546: {for measuring analytes not otherwise provided for, e.g. ions, cytochromes} - A61B 5/14865: {invasive, e.g. introduced into the body by a catheter or needle or using implanted sensors} - A61B 5/4848: {Monitoring or testing the effects of treatment, e.g. of medication} - A61B 5/6849: {in combination with a needle set} - A61B 5/7246: {using correlation, e.g. template matching or determination of similarity} - A61B 5/7275: {Determining trends in physiological measurement data; Predicting development of a medical condition based on physiological measurements, e.g. determining a risk factor} - G01N 33/66: involving blood sugars, e.g. galactose - G16H 10/60: for patient-specific data, e.g. for electronic patient records - G16H 20/10: relating to drugs or medications, e.g. for ensuring correct administration to patients - G16H 20/40: relating to mechanical, radiation or invasive therapies, e.g. surgery, laser therapy, dialysis or acupuncture - G16H 40/63: for local operation - G16H 50/50: for simulation or modelling of medical disorders - A61B: DIAGNOSIS; SURGERY; IDENTIFICATION (usefulness limited to only animals A61D) - G01N: INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES (measuring or testing apparatus or processes other than immunoassay, involving enzymes or microorganisms C12M, C12Q) - G16H: HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA ## Abstract Methods to provide glycemic control and therapy management based on monitored glucose data, and current and/or target Hb1AC levels are provided. Systems to provide glycemic control and therapy management based on monitored glucose data, and current and/or target Hb1AC levels are provided. Kits to provide glycemic control and therapy management based on monitored glucose data, and current and/or target Hb1AC levels are provided. ## Claims ### Claim 1 (canceled) ### Claim 2 An analyte concentration monitoring system, comprising: a display screen; one or more processors; an input module configured to receive sensor data from an analyte sensor configured to generate sensor data points indicative of a measured an analyte concentration; memory; and one or more programs, wherein the one or more programs are stored in the memory and are configured to be executed by the one or more processors, the one or more programs including: instructions to apply a weighted value to each sensor data point falling within a timeframe of sensor data, the weighted value depending upon a concentration value of the sensor data; instructions to aggregate the weighted sensor data according to time of day; and instructions to display the aggregated, weighted sensor data on a chart. ### Claim 3 (depends on 2) The system of claim 2, wherein aggregating the sensor data according to time of day includes aggregating each sensor data point that falls within the same five minute interval of a day. ### Claim 4 (depends on 2) The system of claim 2, further comprising instructions to highlight significant time ranges of the displayed sensor data, wherein significant time ranges of displayed data are determined based on exceeding thresholds for both frequency and severity. ### Claim 5 (depends on 4) The system of claim 4, wherein the determination of significant time ranges has an increased sensitivity during a predefined nighttime range of time, wherein increased sensitivity corresponds to lower frequency and severity thresholds. ### Claim 6 (depends on 2) The system of claim 2, further comprising a user interface incorporating the display screen, wherein the user interface includes a timeframe selection control that allows a user to select of modify the timeframe. ### Claim 7 (depends on 6) The system of claim 6, wherein the chart is automatically updated based on modification of the timeframe using the timeframe selection control. ### Claim 8 A computer-implemented method for identifying patterns in continuous analyte data, the method comprising: obtaining analyte data points from computer memory falling within a designated date range; applying one of more filters to the analyte data to generate contributor data points; weighting each the contributor data point based on the contributor data point's analyte value; assigning each weighted contributor data point to a matching epoch; identifying if an epoch is a match based on whether the contributor or contributors assigned to the epoch meet at least one pattern threshold; determining one or more patterns by scanning the epochs for flags; and outputting information representative of the determined one or more patterns. ### Claim 9 (depends on 8) The method of claim 8, wherein the designated date range is at least three days. ### Claim 10 (depends on 8) The method of claim 8, wherein weighting each contributor data point is based on a predetermined weight assignment map or mathematical assignment function. ### Claim 11 (depends on 8) The method of claim 8, wherein weighting each contributor comprises assigning a weighted value to each contributor, wherein the assigned weighted value is smaller if the analyte value is less clinically significant than if the analyte value is more clinically significant. ### Claim 12 (depends on 11) The method of claim 11, wherein the assignment of weighted values is non-linear based on the analyte value. ### Claim 13 (depends on 8) The method of claim 8, wherein each epoch spans a determined time of day and wherein each contributor is added to the epoch that spans the corresponding time of day. ### Claim 14 (depends on 8) The method of claim 8, wherein the pattern thresholds comprise thresholds selected from the group consisting of: a threshold minimum number of contributors in an epoch; a threshold average weighted value of the contributors in an epoch; a threshold medium weighted value of the contributors in the epoch; a threshold sum of the weighted values of the contributors in the epoch; a threshold average difference of the weighted values of the contributors in the epoch; a threshold standard deviation value of the weighted values of the contributors in the epoch; and a threshold correlation value. ### Claim 15 (depends on 14) The method of claim 14, wherein at least one of the one or more pattern thresholds is defined in terms of a percentage. ### Claim 16 (depends on 8) The method of claim 8, wherein an epoch is flagged when at least some of the one or more thresholds are satisfied. ### Claim 17 (depends on 8) The method of claim 8, wherein determining the one or more patterns comprises determining a start and an end of the pattern. ### Claim 18 (depends on 17) The method of claim 17, wherein the outputted information comprises the start time and the end time. ### Claim 19 (depends on 8) The method of claim 8, wherein determining the one or more patterns is based on the frequency of matching epochs and the weighted values of the matching epochs. ### Claim 20 (depends on 8) The method of claim 8, wherein the outputted information comprises a triggering alert notifying a user of the one or more detected patterns. ### Claim 21 (depends on 8) The method of claim 8, wherein the outputted information is processed further to form or modify a medication administration routine. ### Claim 22 (depends on 8) A analyte concentration pattern detection system configured to perform the method of claim 8, the system comprising a continuous analyte sensor to generate the analyte concentration data points, computer memory to store the generated analyte data points, a processor module configured to perform the applying, the weighting, the assigning, the identifying, and the determining. ### Claim 23 (depends on 22) The system of claim 22, further comprising instructions stored in the memory, wherein the instructions, when executed by the processor module, cause the processor module to perform the applying, the weighting, the assigning, the identifying, and the determining.