Data visualization and user support tool system and method for continuous glucose monitoring

Abstract

The present application provides data visualization and user support tool systems and methods for continuous glucose monitoring, involving a computer-implemented method comprising: receiving, at a mobile computing device, analyte data obtained from a continuous analyte sensor device, wherein the analyte data includes analyte concentration values each associated with a measurement of time; processing, at the mobile computing device, the analyte data to produce an arrangement of the analyte concentration values over a plurality of time intervals; generating a graph of the arrangement of the analyte concentration values; modifying the graph to indicate one or more patterns in the analyte data; and displaying, at the mobile computing device, the modified graph.

Description

[0001] This application is a divisional application of Chinese Patent Application No. 201780041486.5, filed August 10, 2017, entitled "SYSTEMS AND METHODS FOR HEALTH DATA VISUALIZATION AND USER SUPPORT TOOLS FOR CONTINUOUS GLUCOSE MONITORING," which claims priority to U.S. Provisional Application No. 62 / 374,539, filed August 12, 2016. The foregoing applications are incorporated by reference herein in their entirety and expressly made a part of this specification.

[0002] Incorporation by Reference of Related Applications

[0003] Any and all priority claims listed in the Application Data Sheet or any correction thereto, is incorporated herein by reference pursuant to 37 CFR 1.57. This application claims the benefit of U.S. Provisional Application No. 62 / 374,539, filed August 12, 2016. The foregoing application is incorporated by reference herein in its entirety and expressly made a part of this specification. TECHNICAL FIELD

[0004] The present disclosure relates generally to continuous monitoring of analyte values received from an analyte sensor system. More specifically, the present disclosure is directed to systems, methods, devices, and apparatuses for generating dynamic data structures and graphical displays. BACKGROUND

[0005] Diabetes mellitus is a disorder in which the pancreas does not produce enough insulin (Type I or insulin-dependent) and / or in which insulin is not effective (Type 2 or non-insulin dependent). In a diabetes mellitus condition, the victim suffers from high blood sugar, which causes a host of physiological derangements including loss of blood fat, fluid retention, and kidney failure. Hypoglycemic reactions (low blood sugar) can be induced by an unintended overdose of insulin, or following a normal dose of insulin or glucose-lowering agent accompanied by insufficient food intake or excessive exercise.

[0006] Conventionally, a person afflicted with diabetes mellitus carries a self-monitoring blood glucose (SMBG) monitor, which typically requires uncomfortable finger prick methods. Due to the lack of comfort and convenience, a person with diabetes will normally only measure his or her glucose level two to four times per day. Unfortunately, these time intervals are spaced apart far enough apart that diabetes mellitus sufferers will likely be unaware of hyperglycemic or hypoglycemic conditions until it is too late to take corrective action. Indeed, it is not only likely that a diabetes mellitus sufferer will miss an SMBG value, but also that the person will not know whether his or her blood glucose value is increasing or decreasing.

[0007] Accordingly, various non-invasive, transcutaneous (e.g., percutaneous) and / or implantable electrochemical sensors are being developed for continuously detecting and / or quantifying blood glucose levels. As a simple way to monitor glucose levels, continuous glucose monitors are becoming increasingly popular. In the past, patients have sampled glucose levels several times throughout the day, such as in the morning, around noon, and in the evening. The levels can be measured by taking a small blood sample from the patient and measuring the glucose level with a test strip or glucose meter. However, this technique has drawbacks because patients would prefer not to have to take blood samples, and users do not know what their glucose levels are between samplings throughout the day.

[0008] One potential dangerous time frame is at night because a patient's glucose level can decrease to dangerous levels during sleep. Accordingly, continuous glucose monitors have gained popularity by providing a sensor that continuously measures a patient's glucose level and wirelessly transmits the measured glucose level to a display. This allows a patient or a patient's caretaker to monitor the patient's glucose level throughout the day and even set alarms when the glucose level reaches a predefined level or experiences a defined change.

[0009] Initially, continuous glucose monitors wirelessly transmit data related to glucose levels to a dedicated display. A dedicated display is a medical device designed to display glucose levels, trend patterns, and other information to a user. However, as smartphones and software applications (apps) executing on smartphones have become ubiquitous, some users prefer to avoid carrying a dedicated display. In fact, some users prefer to monitor their glucose levels using a dedicated software application executing on their mobile computing device, such as a smartphone, tablet, or wearable device such as a smartwatch or smartglasses. In addition to a dedicated display, still other users can prefer the flexibility of accessing their glucose and glucose-related data on other mobile or stationary computing devices. SUMMARY

[0010] One embodiment includes a system, wherein the system includes: a continuous analyte sensor configured to obtain analyte measurements of a subject; a wireless transmitter configured to receive the analyte measurements from the continuous analyte sensor and at least partially process the analyte measurements to generate one or more data sets of analyte data, each data set including analyte concentration values associated with a time for one or more of the analyte measurements, wherein the wireless transmitter includes an energy storage unit, a data converter unit, a processing unit, and a transmitter unit; and an analyte data processing module operable on a mobile computing device in wireless communication with the wireless transmitter, the analyte data processing module configured to receive and process the one or more data sets to generate a graphical display on the mobile computing device, wherein the graphical display includes an arrangement of the analyte concentration values over a plurality of time intervals, the arrangement graphically modified to indicate one or more patterns in the analyte data.

[0011] In one aspect of the system, the analyte data processing module is further configured to: aggregate groups of analyte data; flag the groups of analyte data based on additional information corresponding to one or more graphical displays; arrange the flagged groups of analyte concentration values; and generate a self-reference data set from the arranged groups of analyte concentration values.

[0012] In one aspect, generating the self-reference data set further includes one or more of: flagging the analyte data based on one or more high and low thresholds for an analyte in the subject; flagging the analyte data based on performing a statistical analysis of the analyte data; and flagging the analyte data based on contextual data related to a time at which the analyte data was obtained.

[0013] In one aspect, the contextual data includes: data indicative of one or more physical locations at which analyte data was obtained, a relationship between the subject and the physical locations, a frequency of visiting the physical locations, meals, types and intensities of exercise, types and amounts of insulin administered, and a likelihood that the subject was asleep or awake when the analyte data was obtained.

[0014] In another aspect, the analyte data processing module is further configured to generate a graphical display on the mobile computing device by: receiving input of a user including a desired graphical display of the user; receiving display configuration data; regenerating the self-reference data set when the self-reference data set does not contain data to form the desired graphical display; and reformatted the self-reference data set based on the input of the user and the display configuration data.

[0015] In some aspects, the analyte data processing module is further configured to modify the graphical display by: scanning the self-reference data set for threshold flags and modifying the graphical display based on threshold flags; scanning the self-reference data set for statistical analysis flags and modifying the graphical display based on statistical analysis flags; and scanning the self-reference data set for analyte context data flags and modifying the graphical display based on context data flags.

[0016] In one aspect, modifying the graphical display includes introducing or using one or more of the following: color, gradient of color or shading, transparency, opacity, buffer, graphical icon, arrow, animation, text, number, and fade.

[0017] In one aspect, the arrangement includes a spatial-time organization of the analyte concentration values, wherein the analyte concentration values are positioned along a first direction according to a first time scale and along a second direction according to a second time scale, and an analyte level of the analyte concentration values is constituted by one or more of shape, color, shading, or size based on a magnitude of the analyte level.

[0018] In one aspect, the first direction and the second direction are linear directions.

[0019] In another aspect, the first direction is a curved direction and the second direction is a radial direction.

[0020] In some aspects, the first time scale is hourly and the second time scale is daily.

[0021] In one aspect, the first time scale is hourly and the second time scale is daily, wherein the graphical modification includes an analyte level trace overlaid on the graphical display such that higher analyte levels are closer to an outer curved region of the graphical display and lower analyte levels are closer to an inner curved region of the graphical display, or vice versa.

[0022] In one aspect, the higher analyte levels are in a first color, the lower analyte levels are in a second color, and analyte levels between the higher and lower analyte levels are in a third color.

[0023] In one aspect, the analyte level trace includes an average analyte level of the hourly analyte concentration values.

[0024] In one aspect, the analyte level trace includes a current analyte level on the daily time scale.

[0025] In another aspect, the modifying of the graphical display includes clustering of display colors, a gradient of colors or shading, alignment of zones, or lighter or darker shading of overlapping zones to modify the arrangement of the analyte concentration values over the plurality of time intervals.

[0026] In one aspect, the one or more patterns indicate high and low analyte level thresholds relative to the subject.

[0027] In one aspect, the plurality of time intervals includes a 24 hour period over 7 days.

[0028] In one aspect, the graphical display includes an isometric plot plotted over a 24 hour period over 7 days.

[0029] In one aspect, the isometric plot is displayable in a three-dimensional view.

[0030] In one aspect, the graphical display includes concentric rings.

[0031] In another aspect, the graphical display includes a pie chart.

[0032] In one aspect, the graphical display includes one or more plots.

[0033] Another embodiment includes a computer-implemented method including receiving, at a mobile computing device, analyte data obtained from a continuous analyte sensor device, wherein the analyte data includes analyte concentration values each associated with a measurement of time; processing, at the mobile computing device, the analyte data to produce an arrangement of the analyte concentration values over a plurality of time intervals; generating a graph of the arrangement of the analyte concentration values; modifying the graph to indicate one or more patterns in the analyte data; and displaying, at the mobile computing device, the modified graph.

[0034] In some aspects, the processing further includes aggregating groups of analyte data; flagging the groups of analyte data based on additional information corresponding to one or more graphical displays; arranging the flagged groups of analyte concentration values; and generating a self-reference data set from the arranged groups of analyte concentration values.

[0035] In one aspect, generating the self-reference data set further includes one or more of flagging the analyte data based on one or more high and low thresholds of an analyte in a subject; flagging the analyte data based on performing a statistical analysis of the analyte data; and flagging the analyte data based on contextual data related to a time at which the analyte data was obtained.

[0036] In some aspects, the contextual data can include data indicative of one or more physical locations where the analyte data was obtained, a relationship between the subject and the physical location, a frequency of access to the physical location, meals, types and intensities of exercise, types and amounts of insulin administered, and a likelihood that the subject was asleep or awake when the analyte data was obtained.

[0037] In another aspect, generating the graph of the arrangement of analyte concentration values further includes receiving input of a user including a desired graphical display of the user, receiving display configuration data, regenerating the self-reference data set when the self-reference data set does not contain data to form the desired graphical display, and reformulating the self-reference data set based on the input of the user and the display configuration data.

[0038] In another aspect, modifying the graph to indicate one or more patterns in the analyte data can include scanning the self-reference data set for threshold flags and modifying the graph based on threshold flags, scanning the self-reference data set for statistical analysis flags and modifying the graph based on statistical analysis flags, and scanning the self-reference data set for analyte contextual data flags and modifying the graph based on contextual data flags.

[0039] In one aspect, modifying the graph includes introducing or using one or more of the following: color, gradient of color or shading, transparency, opacity, buffer, graphical icon, arrow, animation, text, number, and gradual fade.

[0040] In one aspect, the arrangement includes a spatial-time organization of the analyte concentration values, wherein the analyte concentration values are positioned along a first direction according to a first time scale and along a second direction according to a second time scale, and an analyte level of the analyte concentration values is represented by one or more of shape, color, shading, or size based on a magnitude of the analyte level.

[0041] In one aspect, the first direction and the second direction are linear directions.

[0042] In another aspect, the first direction is a curved direction and the second direction is a radial direction.

[0043] In one aspect, the first time scale is hourly and the second time scale is daily.

[0044] In another aspect, the first time scale is hourly and the second time scale is daily, wherein the modified graph includes an analyte level trace overlaid on the modified graph such that higher analyte levels are closer to an outer curved region of the graph and lower analyte levels are closer to an inner curved region of the graph, or vice versa.

[0045] In one aspect, the higher analyte levels are in a first color, the lower analyte levels are in a second color, and analyte levels between the higher and lower analyte levels are in a third color.

[0046] In one aspect, the analyte level trace includes an average analyte level of daily analyte concentration values.

[0047] In another aspect, the analyte level trace includes a current analyte level on the hourly time scale.

[0048] In some aspects, modifying the graph can include clustering of colors, a gradient of colors or shading, alignment of regions, or lighter or darker shading of overlapping regions, thereby modifying the arrangement of the analyte concentration values over the plurality of time intervals.

[0049] In some aspects, the one or more patterns indicate the analyte concentration values relative to high and low analyte level thresholds for a subject.

[0050] In one aspect, the plurality of time intervals includes 24 hour periods over 7 days.

[0051] In one aspect, the graph includes an isometric plot plotted over 24 hour periods over 7 days.

[0052] In another aspect, the isometric plot is displayable in a three-dimensional view.

[0053] In one aspect, the graph includes concentric rings.

[0054] In one aspect, the graph includes a fan-shaped plot.

[0055] In another aspect, the graph includes one or more plots.

[0056] Another embodiment includes a system, wherein the system includes: a continuous analyte sensor configured to obtain glucose data for a subject; a wireless transmitter configured to receive the glucose data from the continuous analyte sensor and transmit the glucose data to a processing module; the processing module is further configured to receive insulin data for the subject, the glucose data for the subject, and event data for the subject and generate a graphical display on a mobile computing device, wherein the processing module further modifies the graphical display to display visual elements indicative of one or more relationships of the insulin data, the glucose data, the event data to each other or to time.

[0057] In one aspect, the event data includes one or more of insulin administration, carbohydrate intake, or exercise.

[0058] In one aspect, the insulin data includes an active insulin value, and the visual elements include a colored ring indicative of the active insulin and an estimated time remaining for the active insulin.

[0059] In one aspect, the visual elements include a trend plot of the glucose data and an interactive pop-up window associated with a region or feature of the trend plot that is presented when a user selects the region or feature of the trend plot on the graphical display, wherein the presented pop-up window includes at least some of the insulin data and / or the event data.

[0060] In another aspect, the presented pop-up window is configured to display a graphical arrangement of the insulin data including one or more of a bolus or basal amount of insulin, a time of administration of bolus insulin, a time of administration of basal insulin, or an active insulin value.

[0061] In one aspect, the presented pop-up window is configured to display a graphical arrangement of the event data including one or more of an amount of carbohydrate intake, an amount of time spent exercising, an amount of calories burned, or a heart rate level reaching a threshold or a time associated therewith.

[0062] In one aspect, the visual elements include an arrow corresponding to insulin data and a glucose reading including a glucose trend corresponding to glucose data, wherein the arrow is displayed proximate to the trend plot and is modified to indicate an effect of the insulin data on the glucose data.

[0063] In some aspects, the visual elements include trend plots of past glucose data and future glucose data, wherein the future glucose data is determined based on insulin data and action data for the subject.

[0064] In another aspect, the visual elements include a first graphical display depicting a current value of the glucose data and an indication of a future trend of the glucose data, and a second graphical display representing an amount of insulin, wherein the second graphical display is interactable with the first graphical display to depict a possible impact of the amount of insulin on the indication of the future trend of the glucose data.

[0065] In one aspect, the processing module is further configured to generate one or more data sets each based on an action of the subject and a prediction of a glucose data trend based on the action of the subject, and the visual elements include a scrollable list including one or more modified graphs each based on the one or more data sets.

[0066] In another aspect, the processing module is further configured to compare a current glucose value to high and low glucose thresholds and generate a glucose score, compare a current active insulin to high and low insulin thresholds and generate an IOB score, generate an insulin status by multiplying the glucose score and the IOB score, and grade the insulin score in one of a plurality of categories.

[0067] In one aspect, the plurality of categories includes good, attention, and bad.

[0068] In one aspect, the visual elements include a colored display, wherein each of a plurality of categories is associated with a different color, and the color associated with the graded insulin score is depicted.

[0069] In another aspect, generating the insulin status further includes multiplying by a trend value.

[0070] In one aspect, generating the insulin status further includes multiplying one or more scores based on location, food intake, and exercise.

[0071] In one aspect, the visual elements include a numerical display of a current glucose value and a graph representing a prediction of a future trend of glucose values.

[0072] In some aspects, the system includes an anticipatory module configured to receive input data of the subject related to future event data, wherein the visual elements include a glucose trend graph and the visual elements are modified accordingly when the input data is modified.

[0073] In some aspects, the visual element includes a trend plot of the glucose, wherein a region between the trend plot and a high glucose threshold is a first color and a region between the trend plot and a low threshold is a second color.

[0074] In some aspects of the system, the processing module is configured to generate the graphical display by: forming one or more data sets including at least some of the insulin data, the glucose data, and the event data; flagging or embedding additional information into at least some of the one or more data sets to generate a self-referential data set; and generating the graphical display in an arrangement that is graphically modified to indicate one or more features in the data.

[0075] One embodiment includes a computer-implemented method, comprising: obtaining glucose data of a subject by a glucose monitoring device; transmitting the glucose data of the subject by a wireless transmitter; receiving insulin data of the subject, the glucose data of the subject, and event data of the subject, and generating a graphical display on a mobile computing device, wherein the graphical display includes a display of one or more of the insulin data, the glucose data, or the event data; modifying the graphical display to display a visual element that indicates one or more relationships of the insulin data, the glucose data, or the event data to each other or to time, wherein the visual element is shaped and configured or scaled so as not to obscure the display of the insulin data or glucose data or event data, and the visual element is displayed in its entirety within the display of the insulin data, the glucose data, or the event data.

[0076] In some aspects, the event data includes one or more of insulin administration, carbohydrate intake, or exercise.

[0077] In one aspect, the insulin data includes an active insulin value, and the visual element includes a colored ring that indicates the active insulin and an estimated time remaining for the active insulin.

[0078] In some aspects, the visual element includes a trend plot of the glucose data and an interactive pop-up window associated with a region or feature of the trend plot, the interactive pop-up window being presented when a user selects the region or the feature of the trend plot on the graphical display, wherein the presented pop-up window includes at least some of the insulin data and / or the event data.

[0079] In another aspect, the presented callout window includes a graphical arrangement of the insulin data including one or more of a bolus or basal amount of insulin, a time of administration of the bolus insulin, a time of administration of the basal insulin, or an active insulin value.

[0080] In one aspect, the presented callout window includes a graphical arrangement of the event data including one or more of an amount of carbohydrate intake, an amount of time spent exercising, an amount of calories burned, or a heart rate level reaching a threshold or time associated therewith.

[0081] In some aspects, the visual element includes an arrow corresponding to insulin data and a glucose reading including a glucose trend corresponding to glucose data, wherein the arrow is displayed proximate to the trend graph and modified to indicate an impact of the insulin data on the glucose data.

[0082] In one aspect, the visual element includes a trend graph of past glucose data and future glucose data, wherein the future glucose data is determined based on insulin data and action data of the subject.

[0083] In another aspect, the visual element includes a first graphical display depicting a current value of the glucose data and an indication of a future trend of the glucose data, and a second graphical display representing an amount of insulin, wherein the second graphical display is interactable with the first graphical display to depict a possible impact of the amount of insulin on the indication of the future trend of the glucose data.

[0084] In some aspects, the method further includes generating one or more data sets each based on actions of the subject and a prediction of a glucose data trend based on the actions of the subject, wherein the visual element includes a scrollable list including one or more modified graphs each based on the one or more data sets.

[0085] In other aspects, the method further includes comparing a current glucose value to high and low glucose thresholds and generating a glucose score; comparing a current active insulin to high and low insulin thresholds and generating an IOB score; generating an insulin status by multiplying the glucose score and the IOB score; and grading the insulin score in one of a plurality of categories.

[0086] In one aspect, the plurality of categories includes good, attention, and bad.

[0087] In another aspect, the visual elements include a colored display, where each of a plurality of categories is associated with a different color, and the color associated with the ranked insulin score is depicted.

[0088] In one aspect, generating the insulin status further includes multiplying by a trend value.

[0089] In another aspect, generating the insulin status further includes multiplying one or more scores based on location, food intake, and exercise.

[0090] In another aspect, the visual elements include a numerical display of the current glucose value and a graph representing a prediction of future trends in glucose values.

[0091] In one aspect, the method further includes receiving input data of the subject related to future event data, where the visual elements include a glucose trend graph and the visual elements are modified accordingly when the input data is modified.

[0092] In one aspect, the visual elements include a trend graph of the glucose, where an area between the trend graph and a high glucose threshold is a first color and an area between the trend graph and a low threshold is a second color.

[0093] In some aspects of the method, the generating the graphical display includes forming one or more data sets comprising at least some of the insulin data, the glucose data, and the event data; flagging or embedding additional information into at least some of the one or more data sets to generate a self-referential data set; and generating the graphical display in an arrangement that is graphically modified to indicate one or more features in the data.

[0094] In one aspect, the processing module is further configured to receive diabetes-related data of the subject and generate an interactive graphical display on the mobile computing device, where a viewer is able to interact with the interactive graphical display.

[0095] In one aspect, the interactive graphical display includes a trend graph of the glucose data and an area between the trend graph and a glucose threshold, with different colors for an area above a high threshold and an area below a low threshold, where the high threshold and the low threshold are adjustable by the viewer's interaction with the interactive graphical display.

[0096] In another aspect, the viewer is able to interact with the interactive graphical display via a collapsible design layout.

[0097] In some aspects, the interactive graphical display further comprises one or more animations to convey information.

[0098] In another aspect, the viewer is able to interact with the interactive graphical display by selecting a personalized background image.

[0099] In some embodiments, the viewer is able to interact with the interactive graphical display by entering a numerical value via a graphical dial.

[0100] In one aspect, the method further comprises receiving diabetes-related data for the subject and generating an interactive graphical display on the mobile computing device, wherein a viewer is able to interact with the interactive graphical display.

[0101] In one aspect, the interactive graphical display comprises a trend plot of the glucose data and an area between the trend plot and a glucose threshold, with different colors for areas above a high threshold and areas above a low threshold, wherein the high threshold and the low threshold are adjustable by the viewer's interaction with the interactive graphical display.

[0102] In another aspect, the viewer is able to interact with the interactive graphical display via a collapsible design layout.

[0103] In some aspects, the interactive graphical display further comprises one or more animations to convey information.

[0104] In one aspect, the viewer is able to interact with the interactive graphical display by selecting a personalized background image.

[0105] In one aspect, the viewer is able to interact with the interactive graphical display by entering a numerical value via a graphical dial.

[0106] In one aspect of the system, the graphical display further comprises an indication of the subject for which analyte measurements were taken.

[0107] One embodiment includes a system comprising: a continuous analyte sensor configured to obtain analyte measurements of a subject; a wireless transmitter configured to receive the analyte measurements from the continuous analyte sensor; and an analyte data processing module operable on a mobile computing device in wireless communication with the wireless transmitter, the analyte data processing module configured to: receive at least a portion of the analyte measurements; generate a self-reference data set based in part on the analyte measurements; generate one or more graphical displays based on the self-reference data set; modify the self-reference data set; display one or more modified graphical displays based on the modified self-reference data set.

[0108] In one aspect, the analyte data processing module is further configured to: generate high or low thresholds for analyte concentration in the subject based in part on one or more of health data obtained from the subject, a statistical analysis of the analyte measurements, contextual data related to the analyte measurements, health data derived from a profile of the subject, or health data obtained from one or more health data databases; determine a time at which an analyte measurement of the subject reaches the high or low thresholds; modify one or more of the high or low thresholds when the time is equal to or less than a predetermined safety time; regenerate the self-reference data set to display an animation indicating the change in threshold.

[0109] In one aspect, the modified graphical display comprises a plot of analyte measurements versus time, and wherein the animation comprises moving a flashing threshold line from a first value to a current analyte value of the subject.

[0110] In one aspect, one or more of the desired graphical displays comprise a plot of analyte measurements versus time, and wherein the analyte data processing module is further configured to: determine one or more expected ranges of analyte values; modify the self-reference data set to display the analyte measurements based on the expected ranges of analyte values.

[0111] In some aspects, the expected ranges of analyte values are based on one or more of input from the subject, contextual data related to the analyte measurements, or health data from a health care organization or health care authority.

[0112] In some aspects, the self-reference data set is modified to display the analyte measurements related to the expected ranges using color, line style, animation, shading, gradient, or other visual element differentials.

[0113] In one aspect, the expected ranges of analyte values comprise a target range, a caution range, and an out-of-target range.

[0114] In another aspect, the self-referential data set is modified to subtract analyte values in the target range and display only analyte values in the attention range and beyond the target range.

[0115] In some aspects, the expected range of analyte values is modified based on event data obtained from the subject.

[0116] In some aspects, one or more of the modified graphical displays include a numerical display of a current value of the analyte measurement, an indication of a prediction of a future trend of analyte measurement values, a textual phrase indicating a current status and the prediction of the future trend of analyte measurement values, a plot of the analyte measurement values versus time, one or more lines indicating high and low thresholds of analyte concentration in the subject, and a graphical representation on the analyte plot indicating the current value of the analyte measurement.

[0117] In one aspect, the self-referential data set is dynamically modified based on analyte measurement values, and the self-referential data set is further modified to indicate that a current analyte measurement value reaches or exceeds a threshold of the analyte concentration values in the subject, and wherein the indication of the prediction of the future trend of analyte measurement values, the threshold line associated with reaching or exceeding the threshold, and the graphical representation of the current analyte value on the analyte plot change in style and pulse in unison.

[0118] In another aspect, the analyte data processing module is further configured to generate one or more audible alarms when an analyte threshold is reached or exceeded.

[0119] In one aspect, the self-referential data set is modified to display one or more system status messages.

[0120] In another aspect, the self-referential data set is modified to display a dark background. BRIEF DESCRIPTION OF DRAWINGS

[0121] Further aspects of the disclosure will be more readily appreciated when the detailed description which follows, taken in conjunction with the accompanying drawings, is read.

[0122] Figure 1A Aspects of an example system that can be used in connection with implementing embodiments of the disclosure are described.

[0123] Figure 1B Aspects of an example system that can be used in connection with implementing embodiments of the disclosure are described.

[0124] Figure 2A is a perspective view of an example housing that can be used in connection with implementing embodiments of an analyte sensor system.

[0125] Figure 2B is a side view of an example housing that can be used in connection with embodiments implementing an analyte sensor system.

[0126] Figure 3A Aspects of an example system that can be used in connection with embodiments implementing the present disclosure are illustrated.

[0127] Figure 3B Aspects of an example system that can be used in connection with embodiments implementing the present disclosure are illustrated.

[0128] Figure 4A is an illustration of a modified graphical display in which analyte concentration values are arranged and presented over a plurality of time intervals.

[0129] Figure 4B is a modified graphical representation made up of a bird's eye view of the plot in Figure 4A .

[0130] Figure 5 is an illustration of an exemplary graphical display in which analyte concentration values are arranged and presented in a ring plot over a plurality of time intervals.

[0131] Figure 6 is an illustration of a modified graphical display corresponding to a data structure and arrangement of analyte concentration values over a time interval.

[0132] Figure 7 is an illustration of a modified graphical display resulting from a data structure and arrangement of analyte data over a plurality of time intervals.

[0133] Figure 8 is an illustration of a modified graphical display resulting from a data structure and arrangement of analyte data over a plurality of time intervals.

[0134] Figure 9 is an illustration of a modified graphical display resulting from a data structure and arrangement of analyte data over a plurality of time intervals.

[0135] Figure 10 is an illustration of a modified graphical display of Figure 9 .

[0136] Figure 11 is a modified graphical display of Figure 10 providing a breakdown of analyte values by day.

[0137] Figure 12 is an illustration of an exemplary graphical display in which analyte concentration values are shown on a clock dial plot.

[0138] Figure 13AA flowchart of an exemplary method of the disclosed system can produce and display a modified graphical display is illustrated.

[0139] Figure 13B A flowchart of an exemplary method to implement the processes identified in Figure 13A A flowchart of an exemplary method to implement the processes identified in

[0140] Figure 13C A flowchart of an exemplary method to implement the processes identified in Figure 13A A flowchart of an exemplary method to implement the processes identified in

[0141] Figure 13D A flowchart of an exemplary method to implement the processes identified in Figure 13A A flowchart of an exemplary method to implement the processes identified in

[0142] Figure 14 An illustration of a modified graphical display produced from a data structure and arrangement of insulin data.

[0143] Figure 15 and 16 An illustration of a modified graphical display including visual elements indicative of one or more relationships of insulin data, analyte data, and event data to each other and / or with respect to a time period.

[0144] Figure 17 An illustration of Figure 15 and 16 insulin key graphs.

[0145] Figure 18 An illustration of a modified graphical display of a trend graph of analyte data.

[0146] Figure 19A and 19B An illustration of a modified graphical display based on historical, current, and predicted analyte values.

[0147] Figure 20 An illustration of a modified graphical display in which the impact of insulin doses on analyte data is shown.

[0148] Figure 21 An illustration of a modified graphical display in which a scrollable list of user's action data and future analyte value trends are depicted.

[0149] Figure 22 An illustration of a modified graphical display depicting relationships between multiple variables related to analyte data trends and user actions.

[0150] Figure 23 An illustration of a glucose trend graph in which excursions outside of high and low thresholds are visually distinguished.

[0151] Figure 24AIllustrating a modified graphical display in which a collapsible design layout is utilized.

[0152] Figure 24B and 24C Illustrating a display screen that presents a modified graphical based on user interaction with the display screen.

[0153] Figure 25 Illustrating a modified graphical display in which animation can be used to convey health-related information.

[0154] Figure 26 Illustrating a modified graphical display in which a user can customize a background image.

[0155] Figure 27 Illustrating a modified graphical display that enables a user to input numerical data using a scroll wheel.

[0156] Figure 28 Illustrating an exemplary modified display in which a user's identifier is incorporated in the modified display.

[0157] Figure 29 Illustrating a display that conveys a change in an analyte threshold via animation.

[0158] Figure 30 Illustrating an analyte graph that depicts analyte measurement values in relation to an expected range of analyte values.

[0159] Figure 31 Illustrating an exemplary modified graphical display that conveys information about the concentration of an analyte value in a subject, a threshold value, a related analyte graph, and / or an analyte monitoring system status and report.

[0160] The accompanying drawings are included to provide a further understanding of the present disclosure and are incorporated in and constitute a part of this specification, illustrate presently preferred embodiments of the present disclosure, and together with the description serve to explain the principles of the present disclosure. In the drawings: DETAILED DESCRIPTION

[0161] Embodiments of the present disclosure are directed to systems, methods, and devices for generating dynamic data structures and graphical displays. In various deployments described herein, analyte data is glucose data generated by an analyte sensor system configured to connect to display devices and the like. As described in detail herein, implementing aspects of the present disclosure can modify graphical displays of analyte data in a manner to conveniently and efficiently indicate patterns in the analyte data. Moreover, implementing aspects of the present disclosure can also conveniently indicate one or more relationships between glucose data, insulin data, and a user's actions. In particular, such aspects of the present disclosure relate to, for example, generating from reference data structures and modifying graphical displays based on the data structures to convey information related to the management of diabetes.

[0162] The details of some example embodiments of the systems, methods, and devices of the present disclosure are set forth in this specification and in some cases in other parts of the disclosure. Other features, objects, and advantages of the disclosure will be apparent from the description of the disclosure, specification, drawings, examples, and claims. All these additional systems, methods, devices, features, and advantages are intended to be included in this specification (whether expressly or by implication), are part of the disclosure, and are protected by one or more of the claims.

[0163] SUMMARY

[0164] In some embodiments, a system for continuous measurement of an analyte in a subject is provided. The system can include a continuous analyte sensor configured to continuously measure a concentration of an analyte in a subject, and a sensor electronics module physically connected to the continuous analyte sensor during sensor use. In certain embodiments, the sensor electronics module includes electronics configured to process a stream of data associated with analyte concentrations measured by the continuous analyte sensor in order to generate sensor information including, for example, raw sensor data, transformed sensor data, and / or any other sensor data. The sensor electronics module can be further configured to generate sensor information tailored for respective display devices, such that different display devices can receive different sensor information.

[0165] The term "analyte" as used herein is a broad term, and is to be given its ordinary and customary meaning to a person of ordinary skill in the art (and is not to be limited to a special or customized meaning), and refers without limitation to a substance or chemical constituent in a biological fluid (e.g., blood, interstitial fluid, cerebrospinal fluid, lymph fluid, urine, sweat, saliva, etc.) that can be analyzed. Analytes can include naturally occurring, artificial, metabolic, and / or reaction products. In some embodiments, the analyte for measurement by the methods or devices is glucose. However, other analytes are contemplated, including but not limited to: carboxyprothrombin; acetoacetate; acetone; acetyl-CoA; carnitine; adenine phosphoribosyl transferase; adenosine deaminase; albumin; alpha-fetoprotein; amino acid profile (arginine (Krebs cycle), histidine / urocanic acid, homocysteine, phenylalanine / tyrosine, tryptophan); androstenedione; antipyrine; arabinitol enantiomers; arginase; biotinidase; biopterin; C-reactive protein; L-carnitine; carnosinase; CD4; ceruloplasmin; chenodeoxycholic acid; chloroquine; cholesterol; cholinesterase; conjugated 1-beta hydroxy cholic acid; cortisol; creatine kinase; creatine kinase MM isoenzyme; cyclosporine A; d-penicillamine; desethylchloroquine; dehydroepiandrosterone sulfate; DNA (acetylation polymorphism, alcohol dehydrogenase, alpha 1- antitrypsin, cystic fibrosis, Duchenne / Becker muscular dystrophy, glucose-6-phosphate dehydrogenase, hemoglobin A, hemoglobin S, hemoglobin C, hemoglobin D, hemoglobin E, hemoglobin F, D-Punjab, beta-thalassemia, hepatitis B virus, HCMV, HIV-1, HTLV-1, Leigh's disease, MCAD, RNA, PKU, Plasmodium vivax, sex differentiation, 21-deoxycortisol); desbutylhalofantrine; dihydropteridine reductase; diphtheria / tetanus antitoxin; erythrocyte arginase; erythrocyte protoporphyrin; esterase D; fatty acids / acylglycines; glycocholestanol / trans-cholestanol; free beta-human chorionic gonadotropin; free erythrocyte porphyrins; free thyroxine (FT4); free triiodothyronine (FT3); fusidic acid diacyl; galactose / Gal-1 -phosphate uridyltransferase; hemocyanin; hemoglobin A; hemoglobin A2; hemoglobin C; hemoglobin D; hemoglobin E; hemoglobin F; haptoglobin type; heavy chain disease; hemolipase; hepatitis B surface antigen; hepatitis C virus; horseradish peroxidase; human growth hormone deficiency; human immunodeficiency virus; human leukocyte antigen; human milk oligosaccharides; hydrocarbon dehydrogenase; hydroxybutyric acid; imidazole propionate; immunoreactive trypsin; ketone bodies; lactate; lead; lipoproteins ((a), B / A-1, beta); lysosomal enzymes; mefloquine; netilmicin; phenobarbitone; phenytoin; phytan / porphyrin; progestone; prolactin; proline peptides; purinenucleoside phosphorylase; quinine; reverse triiodothyronine (rT3); selenium; serum pancreatic lipase; sisomicin; somatomedin C; specific antibodies (e.g., to tumor antigens); succinylacetone; succinylcanolone; testosterone; trace metals; transferrin; transferrin variants; transketolases; vitamins (A, B12, folate); and zinc protoporphyrin.Specific antibodies (adenovirus, antinuclear antibody, anti-zeta antibody, arbovirus, pseudorabies virus, dengue virus, dracunculus medinensis, echinococcus granulosus, entamoeba histolytica, enterovirus, giardia duodenalis, helicobacter pylori, hepatitis b virus, herpes virus, HIV-1, IgE (atopic disease), influenza virus, isoprene (2-methyl-1,3-butadiene), leishmania donovani, leptospira, measles / rubella / mumps, mycobacterium leprae, mycoplasma pneumoniae, myoglobin, onchocerca volvulus, parainfluenza virus, plasmodium falciparum, poliovirus, pseudomonas aeruginosa, respiratory syncytial virus, rickettsia (scrub typhus), schistosoma mansoni, toxoplasma gondii, xanthium, trypanosoma cruzi / lestrangli, vesicular stomatitis virus, wuchereria bancrofti, flaviviruses (e.g., deer tick, dengue, bunga virus, west nile virus, yellow fever or zika virus); specific antigens (hepatitis b virus, HIV-1); succinyl; sulfonamide; theophylline; thyroid stimulating hormone (TSH); thyroxine (T4); thyroxine binding globulin; trace elements; transferrin; UDP-galactose-4-epimerase; urea; uroporphyrinogen i synthase; vitamin a; white blood cells; and zinc protoporphyrin. In certain embodiments, salts, sugars, proteins, fats, vitamins, and hormones that naturally occur in blood or interstitial fluid can also constitute analytes. Analytes can naturally occur in biological body fluids, such as, for example, metabolic products, hormones, antigens, antibodies, and the like. Alternatively, analytes can be introduced into the body or be non-native, such as, for example, contrast agents for imaging, radioisotopes, chemical reagents, carbon fluorocarbon-based synthetic blood, or pharmaceutical or medicinal compositions, including, but not limited to: glucagon, ethanol, synthetic metabolic steroids, and nicotine. Metabolic products of pharmaceutical and medicinal compositions are also contemplated analytes. Neurochemicals and other chemicals produced in the human body can also be analyzed, such as, for example, ascorbic acid, uric acid, dopamine, norepinephrine, 3-methoxytyramine (3MT), 3,4-dihydroxyphenylacetic acid (DOPAC), homovanillic acid (HVA), serotonin (5HT), formylindoleacetic acid (FHIAA), and intermediates in the citric acid cycle.

[0166] Alerts

[0167] In certain embodiments, one or more alerts are associated with the sensor electronics module. For example, each alert can include one or more alert conditions indicating when the respective alert has been triggered. For example, a low blood glucose alert can include an alert condition indicating a minimum glucose level. Alert conditions can also be based on transformed sensor data, such as trend data, and / or sensor data from multiple different sensors (e.g., an alert can be based on sensor data from both a glucose sensor and a temperature sensor). For example, a low blood glucose alert can include an alert condition indicating a minimum required trend in the subject's glucose level that must exist before the alert is triggered. The term "trend" as used herein generally refers to data indicating some property of data taken over time, such as calibrated or filtered data from a continuous glucose sensor. A trend can indicate, for example, an amplitude, rate of change, acceleration, direction, etc. of data, including transformed or raw sensor data.

[0168] In certain embodiments, each of the alerts is associated with one or more actions to be performed in response to triggering of the alert. Alert actions can include, for example, activating an alarm, such as displaying information on a display of the sensor electronics module or activating an audible or vibrating alarm coupled to the sensor electronics module, and / or transmitting data to one or more display devices external to the sensor electronics module. For any delivery actions associated with an alert that is triggered, one or more delivery options define the content and / or format of the data to be transmitted, the device to which the data is to be transmitted, when the data is to be transmitted, and / or a communication protocol for the data delivery.

[0169] In certain embodiments, multiple delivery actions (each having respective delivery options) can be associated with a single alert, such that displayable sensor information having different content and formatting is transmitted, for example, to respective display devices in response to triggering of the single alert. For example, a mobile phone can receive a data packet including minimum displayable sensor information (which can be specifically formatted for display on the mobile phone), while a desktop computer can receive a data packet including most (or all) of the displayable sensor information generated by the sensor electronics module in response to triggering of the common alert. Advantageously, the sensor electronics module is not tethered to a single display device, but is configured to communicate with multiple different display devices directly, systematically, simultaneously (e.g., via a broadcast), regularly, periodically, randomly, on-demand, in response to a query, based on an alert or alarm, and / or the like.

[0170] In some embodiments, a clinical risk alert is provided that includes alert conditions that combine intelligent and dynamic estimation algorithms that estimate current or predicted risk with greater accuracy, more timeliness regarding upcoming risk, avoidance of false alarms, and less annoyance to the patient. Generally, the clinical risk alert includes dynamic and intelligent estimation algorithms based on analyte values, rates of change, accelerations, clinical risk, statistical probabilities, known physiological constraints, and / or individual physiological patterns that provide more appropriate, clinically safe, and patient-friendly alerts. U.S. Patent Publication No. 2007 / 0208246, which is incorporated herein by reference in its entirety, describes some systems and methods associated with the clinical risk alerts (or alarms) described herein. In some embodiments, the clinical risk alert can be triggered for a predetermined period of time to allow the user to attend to his / her condition. Additionally, the clinical risk alert can be deactivated when outside of a clinical risk zone so that the patient is not disturbed by repeated clinical alerts (e.g., visual, audible, or vibratory) when the patient's condition improves. In some embodiments, the dynamic and intelligent estimation determines the likelihood that the patient will avoid a clinical risk based on analyte concentration, rate of change, and other aspects of the dynamic and intelligent estimation algorithms. If the likelihood of avoiding a clinical risk is minimal or nonexistent, the clinical risk alert will be triggered. However, if there is a likelihood of avoiding a clinical risk, the system is configured to wait a predetermined amount of time and re-analyze the likelihood of avoiding a clinical risk. In some embodiments, when there is a likelihood of avoiding a clinical risk, the system is further configured to provide goals, therapy recommendations, or other information that can assist the patient in proactively avoiding a clinical risk.

[0171] In some embodiments, the sensor electronics module is configured to search for one or more display devices within a communication range of the sensor electronics module and wirelessly transmit sensor information (e.g., data packets including displayable sensor information, one or more alert conditions, and / or other alert information) to the display devices. Accordingly, the display devices are configured to display at least some of the sensor information and / or issue an alert to the subject (and / or caregiver), where the alert mechanism is located on the display device.

[0172] In some embodiments, the sensor electronics module is configured to provide one or more different alarms via the sensor electronics module and / or via transmission of a data packet indicating that an alarm should be initiated by one or more display devices (e.g., sequentially and / or simultaneously). In certain embodiments, the sensor electronics module provides only a data field indicating that an alarm condition exists, and the display device upon reading the data field indicating the existence of an alarm condition can decide to trigger an alarm. In some embodiments, the sensor electronics module determines which of the one or more alarms to trigger based on the triggered one or more alerts. For example, when an alert trigger indicates a severe hypoglycemia, the sensor electronics module can perform a number of actions, such as activating an alarm on the sensor electronics module, transmitting a data packet to a monitoring device to indicate activation of an alarm on a display, and transmitting a data packet to a care provider as a text message. As an example, the text message can appear on a custom monitoring device, a cell phone, a pager device, and / or the like, including displayable sensor information indicating the subject's condition (e.g., "severe hypoglycemia").

[0173] In some embodiments, the sensor electronics module is configured to wait for a period of time for the subject to respond to a triggered alert (e.g., by pressing or selecting a snooze and / or disconnect function and / or button on the sensor electronics module and / or display device), after which additional alerts are triggered (e.g., in an escalating manner) until one or more alerts are responded to. In some embodiments, the sensor electronics module is configured to send a control signal (e.g., a stop signal) to a medical device associated with an alarm condition (e.g., hypoglycemia), such as an insulin pump, where the stop alert triggers a stoppage of insulin delivery via the pump.

[0174] In some embodiments, the sensor electronics module is configured to transmit alarm information directly, systemically, simultaneously (e.g., via a broadcast), regularly, periodically, randomly, on demand, in response to a query (from a display device), based on an alert or alarm, and / or the like. In some embodiments, the system further includes a repeater such that the wireless communication distance of the sensor electronics module can be increased, for example, to 10, 20, 30, 50, 75, 100, 150, or 200 meters or more, where the repeater is configured to forward wireless communications from the sensor electronics module to a display device located away from the sensor electronics module. The repeater can be used in a home of a child with diabetes. For example, to allow a parent to carry a display device or to place a display device in a fixed location, such as in a large house where the parent sleeps a distance away from the child.

[0175] Display device

[0176] In some embodiments, the sensor electronics module is configured to search for and / or attempt wireless communication with display devices in a list of display devices. In some embodiments, the sensor electronics module is configured to search for and / or attempt wireless communication with the list of display devices in a predetermined and / or programmable order (e.g., hierarchical and / or incremental), e.g., where a failed attempt and / or alarm regarding communication with a first display device triggers an attempt and / or alarm regarding communication with a second display device, etc. In one example embodiment, the sensor electronics module is configured to sequentially search and attempt to alarm the subject or care provider using a list of display devices, e.g.: (1) a default display device or custom analyte monitoring device; (2) a mobile phone via audible and / or visual methods, e.g., a text message to the subject and / or care provider, a voice message to the subject and / or care provider, and / or 911); (3) a tablet computer; (4) a smart watch or bracelet; and / or (5) smart glasses or other wearable display device.

[0177] Depending on the embodiment, the one or more display devices that receive data packets from the sensor electronics module are "dumb displays" in that they display displayable sensor information received from the sensor electronics module without requiring additional processing (e.g., prospective algorithmic processing necessary for real-time display of sensor information). In some embodiments, the displayable sensor information comprises transformed sensor data that does not require processing by the display device prior to display of the displayable sensor information. Some display devices can include software comprising display instructions (including software programming configured to display the displayable sensor information and optionally query the sensor electronics module for the displayable sensor information) configured to enable display of the displayable sensor information on the display device. In some embodiments, the display devices are programmed at the manufacturer with the display instructions and can include security and / or verification to avoid piracy of the display device. In some embodiments, the display devices are configured to display the displayable sensor information via a downloadable program (e.g., Java script downloadable via the Internet) such that any display device that supports downloading of the program (e.g., any display device that supports Java applets) can thus be configured to display the displayable sensor information (e.g., mobile phones, tablet computers, PDAs, PCs, and the like).

[0178] In some embodiments, certain display devices can directly wirelessly communicate with the sensor electronics module, but intermediate network hardware, firmware, and / or software can be included within the direct wireless communication. In some embodiments, a transponder (e.g., a Bluetooth transponder) can be used to retransmit the transmitted displayable sensor information to a location further away than the immediate range of the telemetry module of the sensor electronics module, where the transponder enables the direct wireless communication when substantial processing of the displayable sensor information does not occur. In some embodiments, a receiver (e.g., a Bluetooth receiver) can be used to retransmit the transmitted displayable sensor information, possibly in a different format, e.g., in a text message, onto a TV screen, where the receiver enables the direct wireless communication when substantial processing of the sensor information does not occur. In certain embodiments, the sensor electronics module wirelessly transmits the displayable sensor information directly to one or more display devices, such that the displayable sensor information transmitted from the sensor electronics module is received by the display devices without intermediate processing of the displayable sensor information.

[0179] In certain embodiments, one or more display devices include a built-in verification mechanism, where verification is required for communication between the sensor electronics module and the display device. In some embodiments, to verify data communication between the sensor electronics module and the display device, a challenge-response protocol is provided, e.g., a password verification, where the challenge is a request for a password and a valid response is the correct password, such that pairing of the sensor electronics module and the display device can be achieved by the user and / or manufacturer via the password. In some cases, this can be referred to as two-way verification.

[0180] In some embodiments, one or more display devices are configured to query the sensor electronics module for displayable sensor information, where the display device acts as a master device requesting sensor information from the sensor electronics module (e.g., a slave device) on demand, e.g., in response to the query. In some embodiments, the sensor electronics module is configured for periodic, systematic, regular, and / or periodic transmission of sensor information to one or more display devices (e.g., every 1, 2, 5, or 10 minutes or more). In some embodiments, the sensor electronics module is configured to transmit data packets associated with triggered alerts (e.g., triggered by one or more alert conditions). However, any combination of the above states of data transmission can be implemented with any combination of paired sensor electronics modules and display devices. For example, one or more display devices can be configured for querying the sensor electronics module database and for receiving alert information triggered by satisfaction of one or more alert conditions. Additionally, the sensor electronics module can be configured for periodic transmission of sensor information to one or more display devices (the same or different display devices as described in the previous example), whereby the system can include display devices that act differently with respect to how to obtain sensor information.

[0181] In some embodiments, the display devices are configured to query the data storage memory in the sensor electronics module for certain types of data content, including direct queries of databases in the memory of the sensor electronics module and / or requests for configured or configurable packets of data content therefrom; i.e., the data stored in the sensor electronics module is configurable, searchable, predetermined, and / or pre-packaged based on the display device with which the sensor electronics module is communicating. In some additional or alternative embodiments, the sensor electronics module generates displayable sensor information based on its knowledge of which display device will receive a particular transmission. Additionally, some display devices are capable of obtaining calibration information and wirelessly transmitting the calibration information to the sensor electronics module, such as through manual entry of calibration information, automatic transfer of calibration information, and / or integral reference analyte monitors incorporated into the display device. U.S. Patent Publication Nos. 2006 / 0222566, 2007 / 0203966, 2007 / 0208245, and 2005 / 0154271 describe systems and methods for providing integral reference analyte monitors incorporated into display devices and / or other calibration methods that can be implemented with the embodiments disclosed herein, all of which are incorporated herein by reference in their entireties.

[0182] Generally, a plurality of display devices (e.g., custom analyte monitoring devices (which can also be referred to as analyte display devices), mobile phones, tablet computers, smart watches, reference analyte monitors, medication delivery devices, medical devices, and personal computers) can be configured to wirelessly communicate with a sensor electronics module. The plurality of display devices can be configured to display at least some of the displayable sensor information wirelessly communicated from the sensor electronics module. The displayable sensor information can include sensor data, such as raw data and / or transformed sensor data, such as analyte concentration values, rate of change information, trend information, alert information, sensor diagnostic information, and / or calibration information.

[0183] Analyte sensor

[0184] Reference Figure 1A In some embodiments, the analyte sensor 10 includes a continuous analyte sensor, such as a subcutaneous, transcutaneous (e.g., transdermal), or intravascular device. In some embodiments, such a sensor or device can analyze a plurality of intermittent blood samples. While the present disclosure includes embodiments of glucose sensors, these embodiments can also be used for other analytes. Glucose sensors can use any glucose measurement method, including enzymatic, chemical, physical, electrochemical, spectrophotometric, polarimetric, calorimetric, iontophoretic, radiometric, immunochemical, and the like.

[0185] The glucose sensor can use any known method, including invasive, minimally invasive, and non-invasive sensing techniques (e.g., fluorescence monitoring), to provide a data stream indicative of glucose concentration in the host. The data stream is typically a raw data signal that is converted to a calibrated and / or filtered data stream to provide useful glucose values to the user, such as the patient or a caretaker (e.g., a parent, relative, guardian, teacher, doctor, nurse, or any other person concerned with the health of the host).

[0186] The glucose sensor can be any device capable of measuring glucose concentration. According to one example embodiment described below, an implantable glucose sensor can be used. However, it should be understood that the devices and methods described herein can be applied to any device capable of detecting glucose concentration and providing an output signal representative of the glucose concentration (e.g., in the form of analyte data).

[0187] In certain embodiments, the analyte sensor 10 is an implantable glucose sensor, such as described with reference to U.S. Patent 6,001,067 and U.S. Patent Publication US-2005-0027463-A1. In embodiments, the analyte sensor 10 is a transcutaneous glucose sensor, such as described with reference to U.S. Patent Publication US-2006-0020187-A1. In embodiments, the analyte sensor 10 is configured to be implanted in a blood vessel of the host or implanted extracorporeally, such as described in U.S. Patent Publication US-2007-0027385-A1, co-pending U.S. Patent Publication US-2008-0119703-A1, filed October 4, 2006, U.S. Patent Publication US-2008-0108942-A1, filed March 26, 2007, and U.S. Patent Application US-2007-0197890-A1, filed February 14, 2007. In embodiments, the continuous glucose sensor includes a transcutaneous sensor such as described in U.S. Patent 6,565,509 issued to Say et al. In embodiments, the analyte sensor 10 is a continuous glucose sensor including a subcutaneous sensor such as described in U.S. Patent 6,579,690 issued to Bonnecaze et al. or U.S. Patent 6,484,046 issued to Say et al. In embodiments, the continuous glucose sensor includes a refillable subcutaneous sensor such as described with reference to U.S. Patent 6,512,939 issued to Colvin et al. The continuous glucose sensor can include an intravascular sensor such as described with reference to U.S. Patent 6,477,395 issued to Schulman et al. The continuous glucose sensor can include an intravascular sensor such as described with reference to U.S. Patent 6,424,847 issued to Mastrototaro et al.

[0188] Figure 2A and 2BThese are perspective and side views of a housing 200 used in conjunction with embodiments of the analyte sensor system 8 according to certain aspects of this disclosure. In some embodiments, the housing 200 includes a mounting unit 214 and a sensor electronics module 12 attached thereto. The housing 200 is shown in a functional position, including the mounting unit 214 and the sensor electronics module 12 matingly engaged therein. In some embodiments, the mounting unit 214, also referred to as a housing or sensor compartment, includes a base 234 adapted to fasten to the skin of the subject or user. The base 234 may be formed of a variety of hard or soft materials and may include a low profile for minimal protrusion of the device from the subject during use. In some embodiments, the base 234 is at least partially formed of a flexible material, which can provide many advantages over other transdermal sensors, however, it may suffer from motion-related artifacts associated with movement of the subject when using the device. The mounting unit 214 and / or the sensor electronics module 12 may be located above the sensor insertion site to protect the site and / or provide minimal footprint (utilization of the surface area of ​​the subject's skin).

[0189] In some embodiments, a detachable connection is provided between the mounting unit 214 and the sensor electronics module 12. This achieves improved manufacturability, meaning that the potentially relatively inexpensive mounting unit 214 can be discarded when the analyte sensor system 8 is serviced or maintained, while the relatively more expensive sensor electronics module 12 can be reused in multiple sensor systems. In some embodiments, the sensor electronics module 12 is configured with signal processing (programming), such as being configured to filter, calibrate, and / or execute other algorithms that can be used to calibrate and / or display sensor information. However, an integrated (non-detachable) sensor electronics module can be configured.

[0190] In some embodiments, the contact 238 is mounted on or within a sub-assembly hereinafter referred to as contact sub-assembly 236, which is configured to engage within the base 234 and hinge 248 of the mounting unit 214, allowing the contact sub-assembly 236 to pivot relative to the mounting unit 214 between a first position (for insertion) and a second position (for use). The term “hinge” as used herein is a broad term and is used in its general sense to include, but is not limited to, any of a variety of pivoting, articulated, and / or articulated mechanisms, such as adhesive hinges, sliding joints, and the like; the term hinge does not necessarily imply a fulcrum or fixed point around which an articulated connection is surrounded. In some embodiments, the contact 238 is formed of a conductive elastic material, such as a carbon black elastomer, through which the sensor 10 extends.

[0191] See further Figure 2A and 2BIn certain embodiments, the mounting unit 214 is provided with an adhesive pad 208 disposed on the back surface of the mounting unit and including a releasable backing layer. Thus, removal of the backing layer and pressing at least a portion of the base 234 of the mounting unit 214 onto the skin of the host will adhere the mounting unit 214 to the skin of the host. Additionally or alternatively, an adhesive pad can be placed over some or all of the analyte sensor system 8 and / or sensor 10 after sensor insertion is complete to ensure adhesion, and optionally, to ensure an air-tight or water-tight seal around the wound exit site (or sensor insertion site) (not shown). Suitable adhesive pads can be selected and designed to stretch, elongate, conform, and / or vent the area (e.g., the skin of the host). The embodiments described with reference to U.S. Patent No. 7,310,544, which is incorporated herein by reference in its entirety, are described in greater detail. Configurations and arrangements can provide water-resistant, waterproof, and / or air-tight sealing properties associated with the mounting unit / sensor electronics module embodiments described herein. Figure 2A and 2B The described embodiments. Configurations and arrangements can provide water-resistant, waterproof, and / or air-tight sealing properties associated with the mounting unit / sensor electronics module embodiments described herein.

[0192] Various methods and devices suitable for use in connection with aspects of some embodiments are disclosed in U.S. Patent Publication No. US-2009-0240120-A1, which is incorporated herein by reference in its entirety for all purposes.

[0193] Example configurations

[0194] Referring again to Figure 1A , a system 100 is depicted that can be used in connection with implementing aspects of an analyte sensor system. In some cases, the system 100 can be used to implement various systems described herein. According to certain aspects of the present disclosure, the system 100 includes, in embodiments, the analyte sensor system 8 as well as display devices 110, 120, 130, and 140. The analyte sensor system 8 in the illustrated embodiments includes a sensor electronics module 12 and a continuous analyte sensor 10 associated with the sensor electronics module 12. The sensor electronics module 12 can be in wireless communication (e.g., directly or indirectly) with one or more of the display devices 110, 120, 130, and 140. In embodiments, the system 100 also includes a medical device 136 and a server system 134. The sensor electronics module 12 can also be in wireless communication (e.g., directly or indirectly) with the medical device 136 and the server system 134. In some examples, the display devices 110-140 can also be in wireless communication with the server system 134 and / or the medical device 136.

[0195] In certain embodiments, sensor electronics module 12 includes electronic circuitry associated with measuring and processing continuous analyte sensor data, including prospective algorithms associated with processing and calibration of sensor data. Sensor electronics module 12 can be physically connected to continuous analyte sensor 10 and can be integral with continuous analyte sensor 10 (attached in a non- releasable manner) or releasably attachable to the continuous analyte sensor. Sensor electronics module 12 can include hardware, firmware, and / or software that enables measurement of analyte levels via a glucose sensor. For example, sensor electronics module 12 can include a potentiostat, a power source for providing power to the sensor, other components useful for signal processing and data storage, and a telemetry module for transmitting data from the sensor electronics module to one or more display devices. The electronics can be attached to a printed circuit board (PCB) or the like, and can take various forms. For example, the electronics can be in the form of an integrated circuit (IC), such as an application specific integrated circuit (ASIC), a microcontroller, and / or a processor.

[0196] Sensor electronics module 12 can include sensor electronics configured to process sensor information, such as sensor data, and generate transformed sensor data and displayable sensor information. Examples of systems and methods for processing sensor analyte data are described in more detail in U.S. Patents 7,310,544 and 6,931,327, and U.S. Patent Publication Nos. 2005 / 0043598, 2007 / 0032706, 2007 / 0016381, 2008 / 0033254, 2005 / 0203360, 2005 / 0154271, 2005 / 0192557, 2006 / 0222566, 2007 / 0203966, and 2007 / 0208245, all of which are herein incorporated by reference in their entirety for all purposes.

[0197] Referring again to Figure 1ADisplay devices 110, 120, 130, and / or 140 are configured to display (and / or alarm) displayable sensor information that can be transmitted by sensor electronics module 12 (e.g., in a customized data packet transmitted to the display device based on the respective preferences of the display device). Each of display devices 110, 120, 130, or 140 may include a display, such as a touchscreen display 112, 122, 132, and / or 142, for displaying sensor information and / or analyte data to a user and / or receiving input from the user. For example, a graphical user interface may be presented to the user for these purposes. In some embodiments, instead of or supplementing a touchscreen display, the display device may include other types of user interfaces, such as a voice user interface, for transmitting sensor information to the user of the display device and / or receiving user input. In some embodiments, one, some, or all of the display devices are configured to display or additionally transmit sensor information as if it were transmitted from the sensor electronics module (e.g., in a data packet transmitted to the respective display device), without requiring any additional forward-looking processing required for the calibration and real-time display of the sensor data.

[0198] In exemplary embodiments of this disclosure, the medical device 136 may be a passive device. For example, the medical device 136 may be an insulin pump for administering insulin to a user, such as... Figure 1B As shown. This insulin pump may need to receive and track glucose values ​​emitted from the analyte sensor system 8 for a variety of reasons. One reason is to provide the insulin pump with the ability to pause or activate insulin administration when the glucose value falls below a threshold. One solution that allows a passive device (e.g., medical device 136) to receive analyte data (e.g., glucose values) without being integrated with the analyte sensor system 8 is to include the analyte data in an advertising message emitted from the analyte sensor system 8. The data included in the advertising message can be encoded so that only a device with identification information associated with the analyte sensor system 8 can decode the analyte data. In some embodiments, the medical device 136 includes, for example, a sensor device 136b that can be attached or worn by a user, which is wired or wirelessly connected to a dedicated monitor or display device 136a to process sensor data and / or display data from the sensor device 136a and / or receive input for operation of the sensor device and / or data processing.

[0199] See further Figure 1AThe plurality of display devices can include custom display devices specifically designed to display certain types of displayable sensor information (e.g., in some embodiments, numerical values and arrows) associated with analyte data received from sensor electronics module 12. Analyte display device 110 is an example of such a custom device. In some embodiments, one of the plurality of display devices is a smartphone, such as an Android, iOS, or other operating system-based mobile phone 120, and is configured to display graphical representations of continuous sensor data (e.g., including current and historical data). Other display devices can include other handheld devices, such as a tablet computer 130, a smart watch 140, a medical device 136 (e.g., an insulin delivery device or a blood glucose meter), and / or a desktop or laptop computer.

[0200] Because different display devices provide different user interfaces, the content of the data package (e.g., the amount, format, and / or type of data to be displayed, alarms, and the like) can be customized (e.g., by the manufacturer and / or differently programmed by the end user) for each particular display device. Thus, in Figure 1A embodiments, multiple different display devices can be in direct wireless communication with a sensor electronics module (e.g., an on-body sensor electronics module 12 physically connected to a continuous analyte sensor 10) during a sensor session to enable multiple different types and / or levels of display and / or functionality associated with displayable sensor information, as described in greater detail elsewhere herein.

[0201] As further explained in Figure 1A , system 100 can also include a wireless access point (WAP) 138, which can be used to couple one or more of analyte sensor system 8, the plurality of display devices, server system 134, and medical device 136 to each other. For example, WAP 138 can provide Wi-Fi and / or cellular connectivity within system 100. Near field communication (NFC) can also be used between devices of system 100. Server system 134 can be used to collect analyte data from analyte sensor system 8 and / or the plurality of display devices, to perform analysis thereon, for example, to generate general or individualized models of glucose levels and profiles, and the like.

[0202] Reference is now made to Figure 3A , which depicts system 300. System 300 can be used in connection with implementing embodiments of the disclosed systems, methods, and devices. For example, Figure 3A various components described below can be used to provide wireless communication of glucose data, for example, between an analyte sensor system and a plurality of display devices, medical devices, servers, and the like, as shown in Figure 1A

[0203] As further explained in Figure 3A ​As shown, system 300 can include an analyte sensor system 308 and one or more display devices 310. Additionally, in the illustrated embodiment, system 300 includes a server system 334, which in turn includes a server 334a coupled to a processor 334c and a storage device 334b. Analyte sensor system 308 can be coupled to display devices 310 and / or server system 334 via a communication medium 305.

[0204] As will be described in detail herein, analyte sensor system 308 and display devices 310 can exchange messaging via communication medium 305, and communication medium 305 can also be used to communicate analyte data to display devices 310 and / or server system 334. As mentioned above, display devices 310 can include a variety of electronic computing devices, such as a smartphone, a tablet computer, a laptop computer, a wearable device, etc. Display devices 310 can also include analyte display device 110 and medical device 136. It is noted here that the GUI of display devices 310 can perform several functions, such as accepting user input and displaying menus and information derived from analyte data. The GUI can be provided by various operating systems known in the art, such as iOS, Android, Windows Mobile, Windows, Mac OS, Chrome OS, Linux, Unix, gaming platform OS (e.g., Xbox, PlayStation, Wii), etc. In various embodiments, communication medium 305 can be based on one or more wireless communication protocols, such as Bluetooth, Bluetooth Low Energy (BLE), ZigBee, Wi-Fi, 802.11 protocols, infrared (IR), radio frequency (RF), 2G, 3G, 4G, etc., and / or wired protocols and mediums.

[0205] In various embodiments, the elements of system 300 can be used to perform the various processes described herein and / or can be used to perform the various operations described herein with respect to one or more disclosed systems and methods. Upon studying this disclosure, one of skill in the art will appreciate that system 300 can include a plurality of analyte sensor systems, communication medium 305, and / or server system 334.

[0206] As noted, the communication medium 305 can be used to connect or communicatively couple the analyte sensor system 308, the display device 310, and / or the server system 334 to each other or to a network, and the communication medium 305 can be implemented in a variety of forms. For example, the communication medium 305 can include an Internet connection, such as a local area network (LAN), a wide area network (WAN), a fiber optic network, an Internet over power line, a hardwired connection (e.g., a bus), and the like, or any other kind of network connection. The communication medium 305 can be implemented using any combination of routers, cables, modems, switches, fiber optics, wires, radios (e.g., microwave / RF links), and the like. Moreover, the communication medium 305 can be implemented using a variety of wireless standards, such as Bluetooth®, BLE, Wi-Fi, 3GPP standards (e.g., 2G GSM / GPR / EDGE, 3G UMTS / CDMA2000, or 4G LTE / LTE-U), and the like. Upon reading this disclosure, those skilled in the art will recognize other ways of implementing the communication medium 305 for communication purposes.

[0207] The server 334a can receive, collect, or monitor information including analyte data and related information from the analyte sensor system 308 and / or the display device 310, such as input in response to analyte data or input received in conjunction with an analyte monitoring application running on the analyte sensor system or the display device 310. In these cases, the server 334a can be configured to receive this information via the communication medium 305. This information can be stored in the storage device 334b and can be processed by the processor 334c. For example, the processor 334c can include an analysis engine capable of performing analysis on information that the server 334a has collected, received, etc. via the communication medium 305. In embodiments, the server 334a, the storage device 334b, and / or the processor 334c can be implemented as a distributed computing network, such as a cloud network, or as a relational database or the like.

[0208] ​​The server 334a can include, for example, an Internet server, a router, a desktop or laptop computer, a smart phone, a tablet computer, a processor, a module, or the like, and can be implemented in various forms, including, for example, an integrated circuit or collection thereof, a printed circuit board or collection thereof, or in a discrete housing / packaging / rack or multiple thereof. In embodiments, the server 334a directs, at least in part, communications conducted over the communication medium 305. These communications include the transfer and / or messaging of advertisements, commands, or other messaging, and analyte data. For example, the server 334a can process and exchange messages related to frequency bands, transmission timing security, alerts, etc., between the analyte sensor system 308 and the display device 310. The server 334a can update information stored on the analyte sensor system 308 and / or the display device 310, e.g., by transferring an application. The server 334a can send / receive information to / from the analyte sensor system 308 and / or the display device 310 in real-time or sporadically. Further, the server 334a can implement cloud computing capabilities for the analyte sensor system 308 and / or the display device 310.

[0209] Figure 3B A system 302 is depicted that includes examples of additional aspects of the disclosure that can be used in connection with implementing an analyte sensor system. As illustrated, the system 302 can include an analyte sensor system 308. As shown, the analyte sensor system 308 can include an analyte sensor 375 (e.g., in Figure 1A may be designated by reference number 10) coupled to a sensor measurement circuit 370 for processing and managing sensor data. The sensor measurement circuit 370 can be coupled to a processor / microprocessor 380 (e.g., can be part of item 12 in Figure 1A In some embodiments, the processor 380 can perform part or all of the functions of the sensor measurement circuit 370 for obtaining and processing sensor measurements from the sensor 375. The processor 380 can be further coupled to a radio or transceiver 320 (e.g., can be part of item 12 in Figure 1A for transmitting sensor data and receiving requests and commands from external devices, such as the display device 310, which can be used to display or otherwise provide sensor data (or analyte data) to a user. As used herein, the terms "radio" and "transceiver" are used interchangeably and generally refer to a device that can wirelessly transmit and receive data. The analyte sensor system 308 can further include a storage device 365 (e.g., can be part of item 12 in Figure 1A and a real-time clock (RTC) 380 (e.g., can be part of item 12 in Figure 1A for storing and tracking sensor data.

[0210] As mentioned above, a wireless communication protocol can be used to transmit and receive data between the analyte sensor system 308 and the display device 310 via the communication medium 305. These wireless protocols can be designed for wireless networks optimized for periodic and small data transmissions to and from multiple devices in close range, such as a personal area network (PAN), which can transmit at low rates if necessary. For example, one such protocol can be optimized for periodic data transfer, where a transceiver can be configured to transmit data in short intervals and then enter a low-power mode in long intervals. The protocol can have low overhead requirements for normal data transmission and for initially setting up a communication channel, such as by reducing overhead, to reduce power consumption. In some embodiments, a burst broadcast scheme can be used (e.g., one-way communication). This can eliminate the overhead required for an acknowledgement signal and allow periodic transmissions that consume little power.

[0211] The protocol can be further configured to establish a communication channel with multiple devices while implementing an interference avoidance scheme. In some embodiments, the protocol can utilize an adaptive isochronous network topology that defines various time slots and frequency bands for communication with several devices. The protocol can thus modify transmission windows and frequencies in response to interference and support communication with multiple devices. Accordingly, the wireless protocol can use a time and frequency division multiplexing (TDMA)-based scheme. The wireless protocol can also employ a direct sequence spread spectrum (DSSS) and frequency hopping spread spectrum scheme. Various network topologies can be used to support short-range and / or low-power wireless communication, such as a peer-to-peer, star, tree, or mesh network topology, such as Wi-Fi, Bluetooth, and Bluetooth Low Energy (BLE). The wireless protocol can operate in various frequency bands, such as the open ISM band, such as 2.4 GHz. Further, to reduce power usage, the wireless protocol can adaptively configure data rates according to power consumption.

[0212] Further referring to Figure 3B , the system 302 can include a display device 310 communicatively coupled to the analyte sensor system 308 via the communication medium 305. In the illustrated embodiment, the display device 310 includes a connectivity interface 315 (also including a transceiver 320), a storage device 325 (also storing an analyte sensor application 330 and / or additional applications), a processor / microprocessor 335, a graphical user interface (GUI) 340 that can be presented using a display 345 of the display device 310, and a real-time clock (RTC) 350. A bus (not shown here) can be used to interconnect the various elements of the display device 310 and to communicate data between these elements.

[0213] Display device 310 can be used to alert and provide sensor information or analyte data to a user, and can include a processor / microprocessor 335 for processing and managing sensor data. Display device 310 can include a display 345, a storage device 325, an analyte sensor application 330, and a real-time clock 350 for displaying stored and tracking sensor data. Display device 310 can further include a radio or transceiver 320 coupled to other elements of display device 310 via a connectivity interface 315 and / or bus. Transceiver 320 can be used to receive sensor data and to send requests, instructions, and / or data to analyte sensor system 308. Transceiver 320 can further employ a communication protocol. Storage device 325 can also be used to store an operating system for display device 310 and / or custom (e.g., proprietary) applications designed for wireless data communication between the transceiver and display device 310. Storage device 325 can be a single memory device or multiple memory devices, and can be volatile or non-volatile memory for storing data and / or instructions for software programs and applications. Instructions can be executed by processor 335 to control and manage transceiver 320.

[0214] In some embodiments, when a standardized communication protocol is used, commercially available transceiver circuitry can be utilized that incorporates processing circuitry to handle low-level data communication functions, such as management of data encoding, transmission frequency, handshaking protocols, and the like. In these embodiments, processor 335, 380 need not manage these activities, but rather provide the required data values for transmission, and manage high-level functions such as power up or down, set the rate of transmission messages, and the like. Instructions and data values for performing these high-level functions can be provided to the transceiver circuitry via data buses and transfer protocols established by the manufacturer of transceiver 320, 360.

[0215] Components of the analyte sensor system 308 can need to be replaced periodically. For example, the analyte sensor system 308 can include an implantable sensor 375, which can be attached to a sensor electronics module that includes sensor measurement circuitry 370, a processor 380, a storage device 365, and a transceiver 360, as well as a battery (not shown). The sensor 375 can need to be replaced periodically (e.g., every 7 to 30 days). The sensor electronics module can be configured to be powered and active for much longer than the sensor 375 (e.g., for three to six months or more) until the battery needs to be replaced. Replacing these components can be difficult and require the assistance of trained personnel. Reducing the need to replace these components, particularly the battery, significantly improves the convenience and cost of using the analyte sensor system 308, including for the user as well. In some embodiments, when the sensor electronics module is first used (or, in some cases, reactivated once the battery has been replaced), it can be connected to the sensor 375 and a sensor session can be established. As will be further described below, there can be a process to initially establish communication between the display device 310 and the sensor electronics module when the module is first used or reactivated (e.g., the battery is replaced). Once the display device 310 and the sensor electronics module have established communication, the display device 310 and the sensor electronics module can be in communication periodically and / or continuously for the life of several sensors 375, until, for example, the battery needs to be replaced. Each time the sensor 375 is replaced, a new sensor session can be established. The new sensor session can be initiated by a process that is done using the display device 310, and the process can be triggered by a notification of the new sensor via communication between the sensor electronics module and the display device 310, which can be persistent across sensor sessions.

[0216] The analyte sensor system 308 generally collects analyte data from the sensor 375 and transmits it to the display device 310. Data points regarding analyte values can be collected and transmitted over the life of the sensor 375, e.g., in the range of 1 to 30 days or more. New measurements can be transmitted often enough to adequately monitor glucose levels. Rather than having the transmission and reception circuitry of each of the analyte sensor system 308 and the display device 310 communicate continuously, the analyte sensor system 308 and the display device 310 can regularly and / or periodically establish a communication channel between them. Thus, the analyte sensor system 308 can communicate at predetermined time intervals via wireless transmission with the display device 310 (e.g., a handheld computing device, a medical device, or a dedicated device) in some cases. The duration of the predetermined time intervals can be selected to be long enough so that the analyte sensor system 308 does not consume excessive power by transmitting data more frequently than necessary, but frequent enough to provide substantially real-time sensor information (e.g., measured glucose values or analyte data) to the display device 310 for output (e.g., via the display 345) to the user. While the predetermined time interval is every five minutes in some embodiments, it should be appreciated that this time interval can vary to any desired length of time.

[0217] With continued reference to Figure 3B As shown, the connectivity interface 315 interfaces the display device 310 to the communication medium 305 so that the display device 310 can be communicatively coupled to the analyte sensor system 308 via the communication medium 305. The transceiver 320 of the connectivity interface 315 can include multiple transceiver modules that can operate under different wireless standards. The transceiver 320 can be used to receive analyte data, as well as associated commands and messages, from the analyte sensor system 308. In addition, the connectivity interface 315 can include additional components for controlling radio and / or wired connections in some cases, such as baseband and / or Ethernet modems, audio / video codecs, etc.

[0218] The storage device 325 can include volatile memory (e.g., RAM) and / or nonvolatile memory (e.g., flash memory), can include any of EPROM, EEPROM, cache, or can include some combination / variation thereof. In various embodiments, the storage device 325 can store user input data and / or other data collected by the display device 310 (e.g., input from other users gathered via the analyte sensor application 330). The storage device 325 can also be used to store large amounts of analyte data received from the analyte sensor system 308 for later retrieval and use, e.g., for determining trends and triggering alerts. Additionally, the storage device 325 can store the analyte sensor application 330, which when executed using, e.g., the processor 335, receives input (e.g., by conventional hard / soft keys or touch screen, voice detection, or other input mechanisms) and allows the user to interact with analyte data and related content via the GUI 340, as will be described in further detail herein.

[0219] In various embodiments, the user can interact with the analyte sensor application 330 via a GUI 340, which can be provided by a display 345 of the display device 310. For example, the display 345 can be a touch screen display that accepts various gestures as input. The application 330 can process and / or present analyte-related data received by the display device 310 according to various operations described herein, and present these data via the display 345. Additionally, the application 330 can be used to obtain, access, display, control, and / or interface with analyte data and related messaging and processes associated with the analyte sensor system 308, as described in further detail herein.

[0220] The application 330 can be downloaded, installed, and initially configured / setup on the display device 310. For example, the display device 310 can obtain the application 330 from the server system 334 or from another source accessed via a communication medium (e.g., the communication medium 305), such as an application store or the like. After installation and setup, the application 330 can be used to access and / or interface with analyte data (e.g., whether stored on the server system 334, locally from the storage 325, or from the analyte sensor system 308). By way of illustration, the application 330 can present a menu that includes various controls or commands that can be executed in connection with the operation of the analyte sensor system 308 and one or more display devices 310. The application 330 can also be used to interface with or control other display devices 310 to, for example, communicate or make analyte data available thereto, including, for example, by directly receiving / transmitting analyte data to another display device 310 and / or transmitting instructions for the analyte sensor system 308 and another display device 310 to connect, as will be described herein. In some embodiments, the application 330 can interact with other applications of the display device to retrieve or provide relevant data, such as other health data.

[0221] The analyte sensor application 330 can include various code / function modules, such as a display module, a menu module, a list module, and the like, as will become clear from the description of various functionality herein (e.g., in connection with the disclosed methods). These modules can be implemented individually or in combination. Each module can include computer-readable media and have computer-executable code stored thereon such that the code can be operatively coupled to and / or executed by the processor 335 (which may, for example, include circuitry for such execution) to perform particular functionality with respect to interfacing with analyte data and performing tasks related thereto (e.g., as described herein with respect to various operations and flowcharts, etc.). As will be further described below, the display module can present various screens to the user (e.g., via the display 345), where the screens contain graphical representations of information provided by the application 330. In other embodiments, the application 330 can be used to display an environment to the user for viewing and interacting with various display devices that can be connected to the analyte sensor system 308 as well as interacting with the analyte sensor system 308 itself. The sensor application 330 can include a native application that is modified with a software design kit (e.g., depending on the operating system) in order to carry out the functionality / features described herein.

[0222] Referring again to Figure 3BThe display device 310 also includes a processor 335. The processor 335 can include processor sub-modules, including, for example, an application processor that interfaces with and / or controls other elements of the display device 310, such as the connectivity interface 315, the application programs 330, the GUI 340, the display 345, the RTC 350, and the like. The processor 335 can include a controller and / or microcontroller that provides various controls related to device management, such as interfaces with buttons and switches, for example, a list of available or previously paired devices, information related to measurement values, information related to network conditions (e.g., link quality and the like), information related to timing, type, and / or structure of messaging exchanged between the analyte sensor system 308 and the display device 310, and the like. In addition, the controller can include various controls related to the collection of user input, such as a user's fingerprint (e.g., to authorize user access to data or to authorize / encrypt data, including analyte data) and analyte data.

[0223] The processor 335 can include circuitry, such as logic circuitry, memory, battery and power circuitry, and other circuitry drivers for peripheral components and audio components. The processor 335, and any sub-processors thereof, can include logic circuitry for receiving, processing, and / or storing data received and / or input to the display device 310, as well as data to be transmitted or communicated by the display device 310. The processor 335 can be coupled to the display 345, as well as the connectivity interface 315 and the storage 325 (including the application programs 330) by a bus. Thus, the processor 335 can receive and process electrical signals generated by these respective elements and thus perform various functions. For example, the processor 335 can access stored content from the storage 325 at the direction of the application programs 330 and process the stored content for display and / or output by the display 345. In addition, the processor 335 can process the stored content for transmission to other display devices 310, the analyte sensor system 308, or the server system 334 via the connectivity interface 315 and the communication medium 305. The display device 310 can include other peripheral components not shown in detail in the Figure 3B

[0224] ​In other embodiments, the processor 335 can further obtain, detect, calculate, and / or store data input by a user via the display 345 or GUI 340 or received from the analyte sensor system 308 (e.g., analyte sensor data or related messaging) over a period of time. The processor 335 can use this input to gauge the user's physiological and / or psychological response to the data and / or other factors (e.g., time of day, location, etc.). In various embodiments, the user response or other factors can indicate preferences with respect to the use of certain display devices 310 under certain conditions, and / or the use of certain connection / transmission schemes under various conditions, as will be described in further detail herein.

[0225] It should be noted that at this time, similarly named elements between the display device 310 and the analyte sensor system 308 can include similar features, structures, and / or capabilities. Thus, the above description of the display device 310 can apply, in some cases, to the analyte sensor system 308 with respect to these elements.

[0226] In some aspects of the systems, devices, and methods according to the present disclosure, health-related and non-health-related data are aggregated, structured, and / or transformed for use in intelligently producing outputs including new analytical data constructs, displays, and controls of devices of the system and other systems. Such health-related information can include glucose and related data (e.g., insulin, meals, activities, etc.), and non-health-related data can include location data, user demographic data, etc. Embodiments in accordance with such aspects of the present technology are perceived to improve the operation of the system, for example, by reducing the complexity of data processing and data transmission between devices, reducing the amount of data and processing algorithms to store and operate, and thereby speeding up the performance of the system as described herein. Further, embodiments in accordance with such aspects of the present technology are contemplated to improve the user's ability to manage their diabetes or other conditions through continuous analyte monitoring. Examples of techniques and tools for producing such outputs regarding glucose status, trends, history, context, and insights to help the user make informed decisions in managing their diabetes are disclosed below. The disclosed techniques, systems, devices, and tools can also be applied to other health conditions.

[0227] In managing diabetes, more and more CGM system users want to see more glucose data over time in their life environment, such as how their glucose levels fluctuate (generally and specific to particular meals) during their eating habits, their lifestyle (e.g., during workdays and at home or playtime), physical activities, etc. But display screens are limited in size, resolution, and other technical parameters. Moreover, even with larger display screens, cramming more data on the screen does not always improve the effectiveness of data display or help the user viewing the data presented on the screen to understand. To address such limitations in CGM systems, data display should be intelligently designed and constructed to avoid information overload and clutter, which leads to misinterpretation, confusion, missed information, etc., of the data, or worse, poor decisions. For example, poor data display can ultimately lead to poor decisions by the user, which can thus be detrimental to their glucose management and health.

[0228] Moreover, while meaningful data that is more context-dependent is needed, manufacturers of CGM systems must pay attention to regulations and standards put forth by regulatory bodies such as the Federal Drug Administration (FDA). In some cases, data displayed within a "actionable time period," such as within 3 hours in real time, can be subject to certain limitations or requirements, which can affect the classification of the CGM device and related software applications. These regulations and limitations also affect the cost of their target products, software, or services.

[0229] Users of CGM devices and related software need more meaningful displays and graphics that can efficiently and intelligently present the user's health-related data to enable safe and wise decisions for managing the user's glucose and health. The data visualization techniques and modified graphics as described herein can be used to intelligently present information about the user's glucose status, trends, history, and corresponding context, thereby overcoming technical and situational challenges (e.g., legal or regulatory) and providing benefits to the end user directly (e.g., providing decision support) and indirectly (e.g., saving the user time in their daily life when they manage their diabetes).

[0230] Glucose pattern visualization

[0231] As discussed above, analyte data collected by the analyte sensor system 308 can include raw sensor data. A raw sensor data unmodified graphical representation can have little value to a user, as the user can potentially miss important information hidden in the clutter of large amounts of or unmodified raw sensor data. Accordingly, embodiments described herein include systems and methods of building a data structure or arrangement of analyte data that features facilitate displaying the analyte data in a modified graphical representation to conveniently indicate patterns and / or information of value to a user's health.

[0232] In some embodiments, the analyte sensor system 308 can generate one or more data sets of analyte data corresponding to analyte measurements in one or more time intervals. For example, in some embodiments, the analyte sensor system 308 can generate a data set corresponding to analyte measurements every 5 minutes. Other time intervals are possible. The analyte sensor system 308 can generate analyte concentration values for each analyte data set. The display device 310 can receive the raw analyte concentration values and generate a data structure or arrangement of analyte data, which in turn can generate a modifiable graphical display. The modifiable graphical display can be efficiently adjusted to alter one or more features that can conveniently indicate patterns or other valuable health information to a viewer.

[0233] In some example implementations, the analyte sensor system 308 or the display device 310 processes the data sets to generate a graphical display that can be displayed on the display device 310, where the graphical display includes an arrangement of analyte concentration values over a plurality of time intervals, the arrangement being modified graphically to, for example, indicate one or more patterns in the analyte data. In some examples, the arrangement of analyte concentration values for the graphical display includes a spatial-time organization of analyte concentration values, where the analyte concentration values are positioned according to a first time scale along a first direction and according to a second time scale along a second direction. The analyte levels of the analyte concentration values are modifiable and represented in the graphical display by one or more of: modification in the graphical display by introduction or use of shapes, colors, shading, gradients of color or shading, various intensities or contrasts of different shading, transparency, opacity, buffer zones, graphical icons, arrows, animations, text, numbers, or fading based on various health parameters, magnitudes of analyte levels, and / or statistical measures associated with analyte levels or groups of analyte levels. In some embodiments, the analyte application 330 operable on the display device 310 processes the data sets to generate a graphical display that is displayed on the display 345, which can be modified or adjusted according to the magnitudes of analyte levels and / or measures.

[0234] Figure 4Ais a modified graphical display in which analyte concentration values are arranged and presented over multiple time intervals such that a viewer can readily detect patterns in the analyte data over the multiple time intervals. The data structure or arrangement of analyte data produced by the embodiments described herein can produce a modified graphical display using color, shape, shading, size, or other visual elements to make it easier for a viewer to detect patterns in the analyte data. The analyte application 330 can receive intermittent analyte concentration values corresponding to an original data set and produce a data structure or arrangement of analyte data that enables a modified graphical display, such as the graph 400A. The graph 400A illustrates analyte concentration values according to a first time scale in a first direction 402. The graph 400A also illustrates analyte concentration values according to a second time scale along a second direction 404. In Figure 4A In the example shown in FIG. 4, the first time scale is an hourly time scale in a day (24 hour period) and the analyte concentration values for a whole day or multiple days are indicated on a daily time scale. The second time scale is a daily time scale of a week (7 days) and the analyte concentration values for a whole week or multiple weeks are indicated on a weekly time scale. In the example graph 400A, the concentration of analyte values for a 24 hour period in a week is shown, but other time intervals can be used. For example, the first direction 402 can be an hourly time scale over a daily period and the second direction 404 can be a monthly period (e.g., days of a particular month), a work week period (e.g., 5 days of Monday-Friday), a weekend period, or other selected period, such as a period including a user's selection on a user interface of the display device 310. Additional data can be extended or included using averaging or other numerical / statistical techniques. For example, on the daily scale 404, an average or other statistically driven data of analyte concentration values for a particular day in a particular period of time can be represented as the analyte concentration values for that day (e.g., analyte concentration values for Sundays over the past three months). In this way, the graph 400A or other 7 day / 24 hour period graph is not limited to only the past 7 day values and can be implemented using a combination of data in any period selected by a user or system.

[0235] Exemplary plot 400A can be an isometric plot in which the magnitude of the analyte concentration values is represented by shapes along a vertical axis perpendicular to the first direction 402 and the second direction 404. The size of each shape can correspond to the magnitude of the analyte concentration value. In some embodiments, color can be used to further indicate the magnitude of the analyte concentration values or to convey additional information about the analyte data. In other embodiments, various shading can be used to identify different magnitudes of the analyte concentration values. For example, shading 406, 408, 410, 412, 414, 416, 418, or yellow if color is used, can be used in the regions of plot 400A in which the analyte concentration values exceed the high threshold value. Shading 420, 422, 424, and 426 can be used to indicate the regions of plot 400A in which the analyte concentration values fall below the low threshold value. If color is used, red can be used to indicate the regions in which the analyte concentration values fall below the low threshold value. In the arrangement of the analyte concentration values in exemplary plot 400A, a viewer can determine at a glance the times in which the analyte concentration values are above the high threshold value by observing the peaks in the data, or if color is used, the viewer can observe the yellow regions to quickly determine the times in which the analyte concentration values exceed the high threshold value. The arrangement of the analyte data as shown in exemplary plot 400A enables a viewer to easily observe patterns in the analyte data. For example, in exemplary plot 400A, regions 406, 408, 410, 412, 414, 416, and 418, corresponding to the analyte concentration values around 6 p.m., show peaks, or if shading is used, regions 406, 408, 410, 412, 414, 416, and 418 can be shown in darker shading (relative to other regions), indicating that the analyte concentration values tend to rise around 6 p.m. in the period shown. Similar patterns can be observed if color is used. Observing such patterns in the analyte concentration values can enable a patient or a patient's caretaker to make better decisions in managing the patient's health.

[0236] Figure 4Bis a graphical representation including a bird's eye view of the plot 400A, shown as plot 400B. Using the plot 400B, a user can easily observe patterns in the analyte data. In some embodiments, the plot 400A can be displayed on the display 345 in an interactive manner that allows the user to rotate, twist, skew, and / or zoom in or out on the displayed plot 400A to manipulate the viewing of the plot 400A. In this regard, the display 345 can present the plot 400A and allow the user to change the display to the plot 400B. Similar to the plot 400A, the plot 400B is modified to identify features in the analyte data, such as high analyte concentration levels illustrated by the enlarged width of the plot for each day at a particular time of day and low analyte concentration levels illustrated by the contracted width of the plot for each day at the particular time, by representing the magnitude of the analyte concentration values in a shape on a planar plot, such as along one or both of the first direction 402 and the second direction 404. Similar to the plot 400A, the plot 400B can also be modified to present a coloring or other visual element associated with the features, such as to create an effect that allows a viewer to determine at a glance times in which the analyte concentration values are above or below a high or low threshold value by observing the modification of the graphical display in the data.

[0237] Figure 5 is an illustration of an example graphical display in which analyte concentration values are arranged and presented in a ring plot 500 over a plurality of time intervals. In such embodiments, a viewer can readily and easily detect one or more patterns in the analyte data over the plurality of time intervals based on the features produced by the plot 500. The plot 500 includes concentric rings, where each ring represents analyte concentration values in a first direction 502 according to a first time scale. The concentric ring structure of the plot 500 allows for illustration of analyte concentration values according to a second time scale along a radial direction 504. In the example shown in Figure 5 In the example plot 500 shown in, the first time scale along the first direction 502 is an hourly time scale in a day (24 hour period), which may, for example, indicate hourly analyte concentration values, and the second time scale along the second time direction 504 is a daily time scale in a week (7 days), which may, for example, indicate daily analyte concentration values. In the example plot 500, analyte concentration values for a 24 hour period in a week are shown. Other time intervals can be used.

[0238] In the example graph 500, each ring can be shaded, or if color is used, color coded to represent the magnitude of the analyte concentration values relative to the high threshold, low threshold, and target zone. For example, for the example displayed ring 506 of analyte concentration values representing a 24 hour period on Sunday (or in some embodiments, a consolidation of Sundays over a period of time), a first shade 506-1 can be used to indicate the time in which the analyte concentration values have fallen below the low threshold, a second shade 506-2 can be used to indicate the time in which the analyte concentration values have been within the target range, and a third shade 506-3 can be used to indicate the time in which the analyte concentration values have exceeded the high threshold. In some implementations, in addition to or in lieu of the shades 506-1, 506-2, and 506-3, colors can be used. For example, red can indicate the time in which the analyte concentration values fall below the low threshold, white can indicate the time in which the analyte concentration values are within the target range, and yellow can indicate the time in which the analyte concentration values exceed the high threshold. In some embodiments, one or more dashed lines can be used in the display of the graph 500 to indicate the presence of unreliable or experimental data.

[0239] The arrangement of the analyte data as shown in the example graph 500 enables a viewer to observe patterns in the analyte data. For example, by scanning the example graph 500, a viewer can quickly observe that for several days of the week, the analyte concentration values exceed the high threshold around 12:00 PM.

[0240] In some embodiments, the data structure or arrangement of the analyte concentration values can be configured to produce a modified graphical display in the center zone 508 of the graph 500. For example, one or more additional visual elements can be included in the center zone 508 to indicate whether the data corresponds to a daytime time or a nighttime time. As described above, the GUI 340 of the display device 310 can be configured to receive input from a user of the system 302 via, for example, a touch sensitive display. When such input is present, the user can touch or indicate a point on any of the concentric rings in the graph 500. Subsequently, a measurement of the analyte concentration value corresponding to the touched point can be displayed in the center zone 508. In some embodiments, if no input data is received from the user, an average value or other statistically driven representative data value corresponding to the entire time period shown in the graph 500 can be displayed in the center zone 508. For example, if the user does not indicate a point on the graph 500, the weekly average of the analyte concentration values can be shown. In some instances, one or more additional graphical icons can be shown in the center zone 508 to indicate additional information about the analyte concentration values represented in the graph 500. The graphical icons can indicate whether the data relates to a daytime time, a nighttime time, a weekend, a weekday, or other time indication of the data.

[0241] In some embodiments, the user can obtain additional information about a given day by providing input to the analyte sensor application 330, such as by touching one of the rings of the graph 500. Instead of or in addition to the graph 500, an additional graph can be shown that indicates more detail corresponding to the day of the touched ring. Figure 6 A modified graphical display of a data structure and arrangement corresponding to analyte concentration values over a time interval is illustrated. The data structure and arrangement of analyte concentration values can produce a graph 600A or 600B in which the analyte concentration values are shown in a shape relative to high and low threshold values and a target zone. The time interval shown in the graph 600A or 600B can be a 24 hour period corresponding to the touched ring in the graph 500. Other time intervals can be used. The graph 600A or 600B can be displayed in parallel with the graph 500, instead of the graph 500, or in conjunction with the graph 500 when the user indicates a point on the graph 500. In addition, the user can indicate a different point along the graph 600A with a pointing device or via a touch screen, and the graph 600A can be updated and modified to show analyte data corresponding to the user's indicated point in the central zone 614 of the graph 600A. The updated analyte data can include the analyte concentration value, time, and date corresponding to the user's indicated point. In the example shown in the graph 600A, the user has indicated a desire to see analyte data corresponding to 5 AM on June 24 by touching the touch display or by rotating a point 616 on the display of the graph 600A. The graph 600B is a modified graph 600A in which the user has indicated a desire to see analyte data values corresponding to 9 AM on June 24. The analyte concentration values and corresponding times are thus modified and updated in the central zone 614.

[0242] In the graph 600A or 600B, analyte concentration values that exceed the high threshold value can be shown by protrusions that extend outward from the outer perimeter of the ring of the graph 600A or 600B. Some examples of high threshold value protrusions can include outward protrusions 602, 604, and 606. Analyte concentration values that are below the low threshold value can be indicated by protrusions that extend inward from the inner perimeter of the graph 600A or 600B. Some examples of low threshold value protrusions can include inward protrusions 608, 610, and 612. As described above, in some embodiments, the user can touch a point 616 on or along the ring graph 600A, and the measurement of the analyte concentration value corresponding to the touched point can be shown in the central zone 614 of the graph 600A.

[0243] In some embodiments, the plots 600A or 600B can utilize shading, gradients, or colors corresponding to the magnitude of the analyte concentration values. For example, the plots 600A or 600B can be generated or modified to utilize various intensities and / or contrasts of shading to indicate the analyte concentration values. Shading 602, 604, 606, and similar shading can be used to indicate where the analyte concentration values exceed the high threshold value. The intensity of the shading can correspond to the magnitude of the analyte concentration values. Shading 608, 610, 612, and similar shading can be used in regions of the plots 600A or 600B where the analyte concentration values are below the low threshold value. A neutral shading, such as shading 618, can be used to indicate analyte concentration values within the target range. One of ordinary skill in the art can appreciate that the shading as described above is exemplary and other visual elements including other shading, textures, gradients, and / or colors can be used.

[0244] Figure 7 is an illustration of a modified graphical display generated by the data structure and arrangement of analyte data over a plurality of time intervals. The data structure and arrangement of analyte concentration values can generate a cross-sectional plot 700 in which the analyte concentration values are shown in one or more segments in a curved direction and in a radial direction. In such embodiments, a viewer can readily and easily detect one or more patterns in the analyte data over the plurality of time intervals based on the features generated by the plot 700. The plot 700 illustrates analyte concentration values in a first direction 702. The first direction 702 can be a curved direction according to a first time scale. The plot 700 also illustrates analyte concentration values according to a second time scale along a second direction 704. The second direction 704 can be a radial direction.

[0245] In Figure 7 the example of the plot 700, the first time scale is a daily time scale in a week (7 days) along the first direction 702, which can indicate daily analyte concentration values, for example, in 7 segments. The second time scale is an hourly time scale in a day (24 hour period), which can indicate hourly analyte concentration values, for example. Other time intervals can be used. Each segment of the plot 700 can represent hourly analyte concentration values over a 24 hour period, with other 24 hour period analyte concentration values shown adjacent thereto. In some embodiments, the segments of the plot 700 can optionally be separated by one or more buffer zones 706. The analyte data represented in the plot 700 need not be limited to analyte data in a 7 day period. Aggregation of the displayed analyte data for each day can also be used to generate the plot 700.

[0246] The plot 700 can be shaded or color coded, as described above with respect to Figure 5 and 6to convey additional information about the analyte concentration values.

[0247] A user can click on any section of the graph 700 to obtain a specialized view of the time interval corresponding to the section. In some embodiments, upon selection of a section, the graphical display 700 can be modified to show the remaining sections collapsed into the selected section, with only the selected section subsequently displayed to provide a graphical display focused on the selected section. While the remaining sections are collapsed, the combined graph 700 can also display a graph of highs and lows corresponding to the analyte data relative to high and low thresholds.

[0248] Figure 8 is an illustration of a modified graphical display produced by the data structure and arrangement of analyte data over multiple time intervals. The data structure and arrangement of analyte concentration values can produce a graph 800 showing analyte concentration values over multiple time intervals on a time scale 802. The magnitude of the analyte concentration values can be represented on a vertical axis 804. The time scale 802 can represent a 24 hour period. Other time periods can be configured and displayed. Each graph 806, 808, 810, and the like represents analyte concentration values over a different 24 hour period. For example, analyte concentration values over a week can be represented by graphs 806, 808, 810, etc. The aggregation of the displayed analyte data for each day can also be used to produce graphs 806, 808, 810, etc. Each graph can visually distinguish the analyte concentration values of different time intervals using areas under the curve shaded with different opacities. A user can point to a point on the graph 800 by a pointing device or via a touch screen, and a pop-up window 812 can be shown that includes a measurement of the analyte concentration value corresponding to the selected point on the graph 800.

[0249] In some embodiments, one or more side tabs can be used to visually isolate the analyte data and present a more focused view. For example, if graphs 806, 808, 810, and the like represent analyte data over a week, a set of side tabs or buttons 806-1, 808-1,... 810-1 can be used, where activating side tab or button 806-1 more prominently displays graph 806 and its corresponding area under the curve and opacity relative to the other displayed analyte data. The unselected analyte data can be shown with less prominent shading. A side tab or button 814 can be activated and more prominently display all of the analyte data.

[0250] In some embodiments, one or more buttons or icons can be used to isolate analyte data relative to high and low thresholds. For example, in graph 800, a user can point to high threshold button 816 via a pointing device or by touching a touchscreen. Graph 800 can be modified to visually distinguish regions of analyte data having magnitudes above one or more high thresholds. The visual distinction can be created by using different shading, gradients, or, in the case of using colors, by using different intensities or gradients of color. Similarly, a user can point to low threshold button 818 via a pointing device or by touching a touchscreen. Graph 800 can be modified to visually distinguish regions of analyte data having magnitudes below one or more low thresholds. Buttons or icons 816 and 818 can be displayed as pressed, thereby activating their corresponding display, or they can be displayed as unpressed, thereby deactivating their corresponding display. In some embodiments, cumulative information about analyte data corresponding to the analyte data captured by graph 800 can be shown. For example, one or more icons or visual elements indicating the percentage of analyte data above a high threshold, below a low threshold, and within the high and low thresholds can be shown, respectively. The percentage icons can be shown simultaneously when their corresponding high or low threshold buttons have been pressed. In one embodiment, the shape of the percentage icons can be a circle, where the thickness, color intensity, or opacity of the circle is determined based on the percentage shown in the center of the circle.

[0251] The high or low thresholds can be input by a user or derived from patient data or multiple patient data available to system 302. Multiple thresholds can be input, defined, or derived for different time intervals, time periods, or dates. Multiple thresholds can be input, defined, or derived as described above with respect to the embodiments of FIGS. 1-7. Figure 5 and 6 Graph 800 can be rendered in colors as described above with respect to the embodiments of FIGS. 1-7.

[0252] Figure 9is an illustration of a modified graphical display produced by the data structure and arrangement of analyte data over multiple time intervals. The data structure and arrangement of analyte concentration values can produce a plot 900 showing analyte concentration values over a plurality of time intervals on a time scale 902. The magnitude of the analyte concentration values can be represented on a vertical axis 904. The time scale 902 can represent a 24 hour period. But other time periods can be configured and displayed. Each of the example plots 906, 908, 910, and the like, represents analyte concentration values in a different 24 hour period. For example, analyte concentration values over a week can be represented by plots 906, 908, 910, etc. A user can point to any portion of the plot 900 via a pointing device, for example by moving a mouse pointer over the plot 900 or by touching a display that displays the plot 900. An icon or overlaid graphical display can be shown on the plot 900 that the user has pointed to, for example a pop-up window 912, where the pop-up window can display measurements of analyte data corresponding to the point selected by the user. If the user clicks or points to a portion of the plot 900 where overlapping or future data is detected, a graphical display 914 can appear within the area of the plot 900, directing the user to click for more information. If the user clicks on the graphical display 914, an additional graphical display can appear within the area of the plot 900, for example a text box 916, providing additional information to the user.

[0253] In some embodiments, the plots 906, 908, 910, and the like, can be reproduced in different line shapes or styles depending on the reliability of the underlying analyte data they represent. For example, a dashed line style can indicate uncertain analyte data. A solid line can indicate analyte data that is reliably tracked. A dotted line 924 can indicate projected future analyte data. The plot keys 918 can be included with the display of the plot 900 along with a description of each plot style.

[0254] In some embodiments, one or more buttons or icons can be used to isolate analyte data relative to high and low thresholds. For example, in graph 900, a user can point to a high threshold button or other virtual menu or button option via a pointing device or by touching a touchscreen. Graph 900 can be modified to visually distinguish regions 920 of analyte data having values ​​higher than one or more high thresholds. Visual distinctions can be created by using different shading, gradients, or, where color is used, by using different intensities or gradients of color. Similarly, a user can point to a low threshold button or other virtual menu or button option via a pointing device or by touching a touchscreen. Graph 900 can be modified to visually distinguish regions 922 of analyte data having values ​​lower than one or more low thresholds. Buttons or icons can be displayed as pressed, thus activating their corresponding display, or they can be displayed as not pressed, thus deactivating their corresponding display.

[0255] Figure 10 yes Figure 9 The modified graphical display is illustrated below. Graph 1000 is similar to Graph 900, where the threshold viewing button or other virtual menu or button option is pressed or activated. Areas above one or more high thresholds 1002 and 1004 are visually distinguished by a first-style coloring to indicate the time during which analyte data values ​​have exceeded high thresholds 1002 and 1004. Areas below one or more low thresholds 1006 and 1008 are visually distinguished by a second-style coloring to indicate the time during which analyte data values ​​have fallen below low thresholds 1006 and 1008. (As described above relative to...) Figure 9 The discussion also covered other ways to visually distinguish between high and low offsets in the analyzed data. For example, if color is used, color gradients or different intensities of color can be employed.

[0256] Can be used as Figure 11 The example graph 1100 shown provides a daily breakdown of graphs 906, 908, 910, or the like from graph 900, and similarly, features 602, 604, 606, 608, and the like from graph 600A or 600B. Alternatively, other time intervals may be used. In the exemplary graph 1100, a bar chart is used to view the daily breakdown of analyte data. Axis 1102 indicates time. The magnitude of the analyte concentration values ​​can be represented on the vertical axis 1104. A user can trigger the display of graph 1100 by pointing at a specific graph 906, 908, or 910 via a pointing device or by touching a touchscreen. One or more lines may indicate the range and / or threshold level of the average analyte concentration values ​​used to generate graph 1100. Figure 11In the example shown in FIG. 10, high threshold levels 1002 and 1004 and low threshold levels 1006 and 1008 are shown on the graph 1100.

[0257] Figure 12 FIG. 12 is an illustration of an exemplary graphical display in which analyte concentration values are arranged and presented over a plurality of time intervals and shown on a clock dial graph 1200 so that a viewer can easily detect one or more patterns in the analyte data over the plurality of time intervals. In one embodiment, the graph 1200 can utilize different shading, each shade corresponding to an analyte concentration value that is above a high threshold, below a low threshold, or a target value. The analyte concentration values for a number of time intervals, such as a number of days, can be superimposed to make up the graph 1200. In this context, a gradient can be created to indicate a pattern over the plurality of time intervals depicted in the graph 1200. For example, if a dark shade 1208 is used to indicate an analyte concentration value that is below a low threshold, and the analyte concentration values for a seven day period for the time between 12 noon and 12 midnight are superimposed to make up the graph 1200, a gradient of the shade 1208 for the time between 3 a.m. and 6 a.m. can indicate a drop in analyte values during that time in the seven day period. A user can conveniently find this pattern in the analyte data over the 7 day time period and take appropriate action to better manage their health. In some embodiments, an analyte trend graph can also be included in the graph 1200 to indicate changes in analyte concentration values in the graph 1202.

[0258] In some embodiments, the graph 1202 can be an analyte level trace overlaid on the clock dial graph 1200 so that higher analyte levels are closer to the outer curved regions of the graph 1200 and lower analyte levels are closer to the inner curved regions of the graph 1200, or vice versa. As described, various analyte level values can be represented in the graph 1200 using various gradients and / or contrasting shades. Higher analyte levels can be in a first shade 1206, lower analyte levels can be in a second shade 1204, and analyte levels between higher and lower analyte levels can be in a third shade 1208. The analyte level trace 1202 can include an average analyte level of daily analyte concentration values or alternatively include a current analyte level on an hourly time scale.

[0259] In some embodiments, a most recently detected analyte concentration value or an average of analyte concentration values can be shown in the center 1204 of the graph 1200. In some embodiments, additional icons can indicate whether the data depicted in the graph 1200 corresponds to daytime or nighttime values.

[0260] In some embodiments, the implemented graphical display 1200 can be reproduced on the display 345. The display device 310 can receive input from the user (e.g., a tap on the touchscreen 345) and flip the graph 1200 to show a display graph depicting the percentage of time that the user has experienced analyte concentration values above a high threshold, below a low threshold, or within the two thresholds during the time period depicted in the graph 1200.

[0261] Figure 13A A flowchart 1300 of an exemplary method by which the system 302 can generate and display the modified graphical displays 400A, 400B, 500, 600, 700, 800, 900, 1000, 1100, and 1200 is illustrated in accordance with some embodiments. The process 1300 begins at block 1302. At block 1304, the analyte sensor application 330 can receive, at the display device 310, analyte data obtained from the continuous analyte sensor device 375 or from the sensor measurement circuit 370. The analyte data received at the analyte sensor application 330 can include analyte concentration values associated with analyte measurements during a time period. At block 1306, the analyte sensor application 330 can cause the processor 335 to process, at the display device 310, the analyte concentration values to generate an arrangement of the analyte concentration values over a plurality of time intervals. At block 1308, the analyte sensor application 330 can cause the processor 335 to generate a graph of the arrangement of the analyte concentration values. At block 1310, the analyte sensor application 330 can cause the processor 335 to modify the graph to indicate one or more features in the analyte concentration values. For example, modifying the graph to indicate one or more features in the analyte concentration values can modify the graph to indicate one or more patterns in the analyte concentration values. At block 1312, the analyte sensor application 330 can cause the processor 335 to display, at the display 345 of the display device 310, the modified graph. The method ends at block 1314.

[0262] Figure 13B An implementation Figure 13AThe process identified in block 1306 of flowchart 1306 is an example method of processing analyte data, e.g., analyte concentration values, to generate a modified graphical display of the arrangement of analyte concentration values over a plurality of time intervals. While this example method is described in the context of the processor 335 of the display device 310 implementing the method, it should be appreciated that other devices of the system can be configured to implement the method. The process 1306 begins at block 1316. In some embodiments, at block 1318, the processor 335 aggregates groups of analyte concentration values based on time values of the analyte concentration values at a time of day. For example, a day, week, month, or other time period of analyte data can be aggregated based on every 5, 10, 15, or other time points of the day, e.g., analyte concentration values grouped at 12:00 PM, 12:10 PM, 12:20 PM, 12:30 PM, etc. In some instances, analyte concentration values can not all align with the same time of day time value, e.g., 12:00 PM, 12:01 PM, 11:59 PM. In such instances, the processor 335 can associate analyte concentration values to a particular time point (e.g., 12:00 PM) for all values falling within a certain range (e.g., ± 5 minutes).

[0263] At block 1320, the processor 335 can flag or embed additional data with the analyte data for generating the graph at block 1308 or the modified graph at block 1310. The additional data can include flagging or tabulating the analyte data based on one or more time scales, the relationship of the flagged or tabulated analyte data to one or more sets of high and low thresholds of analyte data in the subject or a group of subjects, contextual information related to the aggregated analyte data collected at block 1318, and any other information that can be later recalled or otherwise used to generate or modify the graphical displays of the plots described above. In some embodiments, the process of flagging or embedding additional data with the analyte data is performed after analyzing the data, as shown at block 1322. Figure 13A The additional data flagged or embedded with the analyte data at block 1308 to generate the graph or at block 1310 to generate the modified graph can include flagging or tabulating the analyte data based on one or more time scales, the relationship of the flagged or tabulated analyte data to one or more sets of high and low thresholds of analyte data in the subject or a group of subjects, contextual information related to the aggregated analyte data collected at block 1318, and any other information that can be later recalled or otherwise used to generate or modify the graphical displays of the plots described above. In some embodiments, the process of flagging or embedding additional data with the analyte data is performed after analyzing the data, as shown at block 1322.

[0264] At block 1322, the processor 335 analyzes the grouped analyte concentration values. In some embodiments, the processor 335 can determine a maximum value and / or a minimum value of the grouped values. In some embodiments, the processor 335 can determine a mean, median, standard deviation, or other statistical measure of the grouped values. Additionally, the processor 335 can perform a Fourier transform, Laplace transform, and / or sampling techniques on the grouped analyte concentration values to help form a modified graphical display indicative of patterns in the analyte data, e.g., in the plots described above. Figure 13Aat block 1310. In some embodiments, the process at block 1320 is performed on the analyzed group of analyte concentration values after block 1322, where the analyzed group of analyte concentration values can be flagged or embedded with additional data for modifying the graph at block 1310. For example, the group of analyzed analyte concentration values can have an average, median, standard deviation, etc. that is outside of a predetermined threshold or predetermined range, and can be flagged or embedded with additional data.

[0265] At block 1324, the processor 335 arranges the analyzed group of analyte concentration values based on the spatial or temporal parameters associated with the type of modified graph, as described above with respect to the graphs 400A, 400B, 500, 600, 700, 800, 900, 1000, 1100, and 1200. For example, if the graph includes a second time scale, the processor 335 can arrange the analyzed group of analyte concentration values according to their time values for the time of day of the second time scale, such as the day of the week, the day of the month, selected days of a time period (e.g., weekdays, holiday days, or other user-selected time ranges).

[0266] At block 1326, the processor 335 forms a data set of the arranged analyzed group of analyte data. The data set is structured such that it can be processed by the processor 335 as a basis to form a graphical display that can be displayed on the display 345, such as in response to a request from the user at block 1308. Figure 13A At block 1308. As described above, the data set generated at block 1326 is self- referencing, and includes information to generate the graph at block 1308 or the modified graph at block 1310 without having to search and re-call necessary information from various parts of the system 302. Figure 13A At block 1308. As described above, the data set generated at block 1326 is self- referencing, and includes information to generate the graph at block 1308 or the modified graph at block 1310 without having to search and re-call necessary information from various parts of the system 302. Figure 13A At block 1310.

[0267] Some advantages of the methods and systems can include the following. The self- referencing data set (SRDS) generated at block 1326 eliminates the need for the processor 335 to search and re-call necessary information from various parts of the system 302 to generate the graphs of blocks 1308 and 1310. Otherwise, for example, without the self-referencing data set generated at block 1326, the processor 335 would have to search, query, and / or call various parts of the system 302 each time a user requests a different graph or requests a modification of a displayed graph. Thus, the self-referencing data set generated at block 1326 improves the operation of the system 302 by reducing the complexity of data processing and data transmission between various parts of the system 302. For example, using the SRDS, the system does not have to store or process additional algorithms, such as pattern recognition algorithms, to generate, for example, displayed outputs to convey pattern information to the user. Additionally, the self-referencing data set generated at block 1326 can reduce the need for additional data processing and data transmission between various parts of the system 302 to generate, for example, the graphs of blocks 1308 and 1310. Figure 13AThe amount and frequency of data emitted by frames 1308 and 1310 for the purpose of generating graphical displays are thus reduced. This also reduces the associated processing or drawing algorithms for storage and operation, and increases the performance of system 302.

[0268] Process 1306 ends at box 1328, and further processing is handed over to... Figure 13A Box 1308.

[0269] Figure 13C Instructions for implementation Figure 13A The flowchart 1308 is an exemplary method for generating a graphical representation of analyte concentration values, as identified in block 1308. While this exemplary method is described with the processor 335 of the display device 310 implementing the method, it should be understood that other devices of the system may be configured to implement the method. Process 1308 begins at block 1330. At block 1332, the processor 335 receives user input data relating to the user's desired graphical display. This may include the type of desired graphical display (e.g., text, charts such as bar charts, pie charts, etc., or other charts, and / or graphical displays such as 400A, 400B, 500, 600, 700, 800, 900, 1000, 1100, and 1200, etc., or other graphical displays), and / or the range of graphical displays the user wishes to see relative to one or more timescales of the dataset in which process 1306 has been formed.

[0270] At box 1334, processor 335 may receive hardware or software data relating to display device 310 or display 345. Display data may include, for example, the size, dimensions, or resolution of the available viewing area, available orientation, and available input devices. At box 1336, processor 335 may determine whether the self-reference dataset formed in box 1326 contains all the information necessary to generate the desired graph for the user. As an example, the user may have requested the display of analyte data falling outside the range captured in the self-reference dataset. In these instances, process 1306 may be repeated and a more comprehensive self-reference dataset may be formed. However, in most cases, the self-reference dataset is formed in a manner containing all the necessary information and data for generating the desired graph for the user.

[0271] At box 1338, processor 335 reformats the self-reference dataset based on user input data and display device data, generating a formatted self-reference dataset. For example, if the user's desired display range is smaller than the range of data captured in the self-reference dataset, then at box 1338 processor 335 can filter the data by erasing unwanted or out-of-range data from the self-reference dataset. At box 1340, processor 335 generates a graph of the arrangement of analyte concentration values ​​based on the formatted self-reference dataset. The processing involved at box 1340 may depend on the type of graph selected by the user and the display device data. For example, if the user requires the display range as described above... Figure 4A Given the described graph 400A, the processor 335 can determine the correct scale for generating the graph 400A based on the available viewing area and the orientation of the display device 345.

[0272] Process 1308 ends at box 1342, and further processing is handed over to Figure 13A Box 1310.

[0273] Figure 13D Instructions for implementation Figure 13A The flowchart 1310 illustrates an exemplary method for modifying a graph to indicate one or more features in analyte concentration values, as identified in block 1310. While this exemplary method is described with respect to the implementation of the method by processor 335 of display device 310, it should be understood that other devices of the system may be configured to implement the method. Depending on the graphical display selected by the user, processor 335 may modify the graph generated by process 1308 to indicate one or more features and / or patterns in the analyte data. Furthermore, the modified graph may present the data in a manner that reduces information overload and potential user misinterpretation of the presented data. For example, if the user selects a three-dimensional graph, such as graph display 400A, then certain portions of the illustrated analyte data may obscure other portions of the illustrated data. Process 1310 may detect such instances and modify the illustrated data accordingly, for example, by making portions of the illustrated analyte data transparent in the overlapping area.

[0274] Process 1310 can modify the graph produced by process 1308 using color. For example, process 1310 can add various color shades to the plotted analyte data relative to one or more sets of high and low thresholds. Process 1310 can utilize flagged or extra embedded information obtained at block 1320 of process 1306 to color code the plotted data. For example, processor 335 can detect portions of the plotted data that correspond to analyte values that are 20-30% higher than the high threshold. The plotted analyte data can be modified using yellow or shades to indicate these values. If another portion of the plotted analyte data is 40-50% higher than the high threshold, then the portion of the analyte data can be indicated using a contrasting shade (e.g., a darker shade of the gray scale gradient or a darker shade of yellow if color is used). Processor 335 can query the flags or embedded extra data in the self-reference data set to detect and modify portions of the plotted data relative to the high and low thresholds.

[0275] In some examples, process 1310 can utilize statistical analysis obtained at block 1322 of process 1306 to modify the graph produced by process 1308. For example, the self-reference data set (SRDS) can include flags or embedded data that indicate which analyte values fall outside an acceptable multiple of the standard deviation of the analyte data or which analyte values are statistically unreliable. Processor 335 can modify the plotted data based on the statistically derived flags in the SRDS.

[0276] In some embodiments, the SRDS can include flags or embedded information that are based on the context of the analyte data. The context of the analyte data can be obtained or derived from a variety of sources. For example, if the analyte values obtained on a particular day of the week coincide with the detection of mobile display device 310 at a restaurant, then the SRDS can include a flag or embedded information that indicates this correlation. The frequency of the correlation between the detected analyte data and the context of the data can also be included in the SRDS. Processor 335 can modify the plotted data to include features based on the context-based flags found in the SRDS to visually indicate the user's behavioral patterns relative to the analyte data over a period of time. The user can make health or diabetes-related decisions based in part on the modified plotted analyte data and the features described therein.

[0277] In some embodiments, the processor 335 can modify the plotted data, where the modification is based on detecting flags or patterns of embedded information in the SRDS. For example, the SRDS can include flags that indicate peaks and valleys of the analyte data. The processor 335 can detect that, in a two-dimensional plot, different segments of the plotted analyte data visually merge together for many of the concentrated peaks and make it difficult for a viewer to identify the peaks. In such cases, the processor 335 can add or introduce a buffer between various segments of the plotted analyte data to remedy this situation. The processor 335 can query the flags or additional embedded data in the SRDS to detect the peaks and valleys of the data and determine if there is a pattern where the peaks are plotted too close together such that modifying the plotted data to include new or added buffers can facilitate easy visual interpretation of the plotted data.

[0278] The process 1310 begins at block 1344. The process 1310 then proceeds through a series of decisions followed by modifying the plotted data to indicate features in the analyte data. For example, modifying the plot to indicate one or more features in the analyte concentration values can modify the plotted data to indicate one or more patterns in the analyte concentration values. Those of ordinary skill in the art will readily recognize that the present technology is not limited to the series of decisions and modifications disclosed herein, and that additional series of decisions and modifications can be designed and implemented without departing from the spirit of the present technology. Not all of the disclosed decision and modification steps are required in every embodiment. One or more of the decision and modification steps can be eliminated or other steps can be added depending on the desired graphical display of the user.

[0279] At decision block 1346, the processor 335 scans the SRDS to detect if flags or embedded additional data related to the relationship between the analyte data and one or more high and low thresholds are present. A variety of such flags or otherwise embedded information can be included in the SRDS. For example, the analyte data in the SRDS can be flagged or correlated with thresholds, where different time scales within the analyte values of the SRDS can have their own associated thresholds. The analyte data in the SRDS can be flagged based on the percentage or range that the analyte data exceeds or falls below a high or low threshold. At block 1348, depending on the combination of threshold flags and the type of graph requested by the user, the processor 335 modifies the plotted data to indicate features and / or patterns in the analyte data.

[0280] In some embodiments, the modification can include using color, color gradient, shading, various degrees of transparency or opacity, changing color, gradient, or transparency based on overlay and underlying regions to allow visual detection of features and / or patterns in the analyte data, as described above with respect to the modified graphical displays 400A, 400B, 500, 600, 700, 800, 900, 1000, 1100, and 1200.

[0281] At block 1350, the processor 335 scans the SRDS to detect whether flags or embedded additional data related to the statistical analysis performed in process 1306 are present within the SRDS. The processor 335 can modify the graphical data based on the flags or embedded additional data in the SRDS, which are based on the statistical analysis. For example, analyte data in the SRDS can be flagged based on the relationship of the analyte data to the standard deviation, mean, variance, or other statistical parameters related to the underlying analyte data. In some embodiments, analyte data in the SRDS can be flagged if it falls outside an acceptable multiple of the standard deviation of the analyte data. Corresponding graphical modifications of the graphical analyte data can be based on these flags. Or analyte data within two multiples of the standard deviation of the analyte data can be flagged for later color modification of the graphical data.

[0282] If the SRDS contains statistical-based flags or embedded information and their corresponding graphical modifications, at block 1352, the processor 335 can modify the graphical data accordingly. In some embodiments, the modification can include using color, color gradient, shading, various degrees of transparency or opacity to allow visual detection of features and / or patterns in the analyte data, as described above with respect to the modified graphical displays 400A, 400B, 500, 600, 700, 800, 900, 1000, 1100, and 1200.

[0283] At block 1354, the processor 335 can scan the SRDS to detect whether flags or embedded additional data related to the context of the analyte data are present. Some examples of the context of the analyte data can include context information related to the user's location when the analyte data was collected (e.g., whether the user was at a restaurant, at a gym, at home, or at work or school, how often the user was present at this location), the relationship of the analyte data to various activities of the user (e.g., whether the analyte data was collected when the user had just eaten or engaged in exercise, or was awake or asleep, whether insulin was taken and how much insulin was taken). Contextual analyte data can be obtained automatically without user intervention, or can be entered by the user.

[0284] Contextual analyte data is not limited to the examples listed herein, and one of ordinary skill in the art can readily determine other contextual analyte data that can be flagged, embedded, or otherwise referenced in the SRDS. At block 1356, the processor 335 can modify the graphical data based on the contextual flags or embedded data in the SRDS. Various graphical modifications corresponding to various contexts can be programmed in the process 1310. Contextual modifications can include the use of colors, color gradients, shading, various degrees of transparency or opacity to allow visual detection of features and / or patterns in the analyte data, as described above with respect to the modified graphical displays 400A, 400B, 500, 600, 700, 800, 900, 1000, 1100, and 1200.

[0285] Graphical modifications of the process 1310 are not limited to the examples listed above. A variety of graphics can be used for modification to indicate features, patterns, or trends in the analyte data, and to conveniently alert or convey health or diabetes-related data to the user. The processor 335 can use graphics or graphical techniques, such as graphical icons, animations, text or text boxes, font and stylized text or numbers, arrows, fading, or other techniques, to modify the graphical data in the process 1310.

[0286] At block 1358, the processor 335 can scan the flags in the SRDS and the graphics produced by the process 1308 to determine whether further modifications to the graphical data can further improve readability, reduce clutter, and better indicate features and / or patterns in the analyte data. For example, as described above, if the processor 335 detects many concentrated peaks in the graphical data and associated flags in the SRDS, the processor 335 can modify the graphical data by introducing or adding one or more buffers to improve readability and better indicate features and / or patterns in the analyte data, at block 1360, based on the type of graphical data. The processor 335 can also analyze the graphical data produced by the process 1308 and flagged data in the SRDS to detect whether overlapping regions are reproduced in a manner that reduces the conveyance of information in the graphical data. At block 1360, the processor 335 can modify the color, shading, gradient, spacing, or transparency in the overlapping regions to visually distinguish the overlapping regions and improve the ability of the graphical data to convey features, patterns, or trends in the analyte data. One of ordinary skill in the art can readily determine additional analysis of the flags and graphical data and associated modifications to improve the conveyance of health or diabetes-related data. The process 1310 ends at block 1362, and further processing is handed over to block 1312 of the process 1300. Figure 13A

[0287] ​While in some embodiments the processes of generating SRDS, graphical data, and modified graphical data are described with respect to past or collected analyte data, the systems and methods of the present technology can be used with future or predicted analyte data or a combination of past, collected, and future analyte data.

[0288] Insulin visualization

[0289] The embodiments described herein are not limited to generating data structures based on analyte data. Raw data regarding other compounds related to the health of a patient can also be received, and the system can generate data structures and data arrangements capable of generating modified graphical displays based on such data. For example, the system can receive data corresponding to the active insulin (IOB) level of a patient, and generate a data structure or data arrangement capable of generating a modified graphical display to conveniently indicate useful information regarding the health of the patient. The methods associated with Figures 13A-13D may be implemented to generate a modified graphical display associated with insulin data.

[0290] Figure 14 is an illustration of a modified graphical display 1400 generated from a data structure and arrangement of insulin data. The display 1400 can include a ring 1402, where a full circle ring can represent the duration of insulin action (DIA). An overlying ring 1404 can represent the remaining time for the placement of active insulin. The size of the overlying ring 1404 can be determined as a fraction of the full circle DIA. For example, if one hour remains of a four hour DIA, then the remaining time would be 1 / 4 of the total DIA. In this case, the overlying ring 1404 can overlie only 1 / 4 of the ring 1402. When the user takes a dose of insulin, the overlying ring 1404 overlies the entire ring 1402. As time passes and the insulin metabolizes, the overlying ring 1404 gradually decreases. In some embodiments, the ring 1402 and the overlying ring 1404 can each be reproduced in different shades to better visually distinguish the two. In some embodiments, color is used to visually distinguish the two. A graphical representation 1406 corresponding to the remaining time can be shown in the center of the ring 1402. In some embodiments, the graphical representation 1406 includes a number representing the amount of active insulin.

[0291] If the overlying ring 1404 is gradually reduced over a long period of time, the gradual reduction can be difficult to discern for some viewers. In some embodiments, when the graphical display 1400 is generated, the overlying ring 1404 is first shown fully overlapping the ring 1402, and the graphical representation 1406 is shown corresponding to the DIA. Over a short amount of time, the size of the overlying ring 1404 is rapidly reduced to correspond to the remaining time for the current amount of active insulin. At the same amount of time, the graphical representation 1406 can be shown to decrease and settle at the current amount of active insulin. For example, if a number is used for the graphical representation 1406, the number can decrease similar to a fast counter countdown and settle at the current amount of active insulin. This graphic for the overlying ring 1404 and the graphical representation 1406 shown over a short amount of time can help a viewer discern what information the graphical display 1400 is conveying.

[0292] SRDS generated based on insulin data can be flagged according to some embodiments of the process 1306 to include appropriate triggers for animation, overlying graphs, and textual information, as described above. In some implementations, when the graphical display 1400 is initiated, the processes 1308 and 1310 parse the SRDS for flags related to the generation of the graphic 1400 and modify the graphic generated by the process 1308 to generate a modified graphic 1400.

[0293] In some embodiments, the analyte sensor application 330 can be configured to receive event data, where the event data can include information about the user's actions and activities related to health management or diabetes. For example, the event data can include: meals, type of exercise, duration and intensity, and amount and type of insulin taken. The analyte sensor application 330 can be configured to generate data structures and arrangements of analyte data that, in turn, can generate modified graphical displays capable of visually representing one or more relationships of the analyte data, insulin data, and event data to each other and / or about a time period. For example, based on the visual constructs generated from the SRDS, a user of the system 302 can conveniently make health-related decisions, or detect features and / or patterns without requiring excessive mental activity.

[0294] Figure 15 and 16The modified graphical displays 1500 and 1600 generated from the data structure and data arrangement according to embodiments include visual elements that indicate one or more relationships of the insulin data, the analyte data, and the event data to each other and / or with respect to a time period. In various embodiments of the modified graphical displays 1500 and 1600, the displays can include displays of one or more of the insulin data, the analyte data, or the event data, where the displays can be modified to further display visual elements that indicate one or more relationships of the insulin data, the analyte data, or the event data to each other or with respect to a time period. The visual elements can be shaped and configured or scaled so that the visual elements do not obscure the displays of the insulin data, the analyte data, or the event data. Further, the visual elements can be displayed entirely within the displays of the insulin data, the glucose data, or the event data.

[0295] The graphical display 1500 can include an analyte trend graph 1502. Time is represented on a horizontal axis 1504. Magnitudes of analyte data are represented on a vertical axis 1506. The analyte trend graph 1502 can be represented relative to a high threshold 1508 and a low threshold 1510. Although not shown for all embodiments, the analyte trend graph 1502 can be rendered in various colors, line styles, or shading relative to the high threshold 1508 and the low threshold 1510 to visually indicate relationships of the analyte data to the high threshold 1508 and the low threshold 1510. The graphical display 1500 can additionally include an event data display area 1512. In the example shown, event data is not shown in the event data display area 1512, but can be present therein. Examples of event data are shown later in Figure 15 Figure 16 , where various icons and graphical displays are shown in the event data display area 1612. Referring back to Figure 15 , the graphical display 1500 can additionally include a graph of insulin data 1514. A horizontal axis 1516 can represent time. A vertical axis 1518 can represent magnitudes of insulin data. A user can expand or contract a time period in which the analyte trend graph 1502 and the insulin graph 1514 are displayed via different time period labels 1520. A graphical display or icon 1522 can indicate to the user that by changing the orientation of the mobile computing device from portrait to landscape or vice versa, the user can obtain different visual elements of relationships between the analyte data, the insulin data, the event data, and time. The event display area 1512 can include a display of a graphical arrangement of event data including one or more of an amount of carbohydrate intake, an amount of time spent exercising, an amount of calories burned, or a heart rate level that reached a threshold or a time associated therewith.

[0296] Referring to Figure 16 ​Graphical display 1600 is similar to graphical display 1500. Event data display area 1612 can allow a user to easily access indicators of when the user has taken actions that can be considered relevant to the user's diabetes management. For example, a meal can be indicated with a label or graphical icon 1616, or a period of exercise can be indicated by a label or graphical icon 1618. Event display area 1612 can be generated and shown to a patient's caregiver for quick access to the patient's actions relevant to diabetes management. In some embodiments, an array of graphical icons of potential actions relevant to diabetes management can be presented to the user, and the user can drag and drop them onto the analyte trend graph 1602 or event display area 1612 to indicate when the user has taken those actions. For example, the user can drag a meal event icon 1616 and drop the icon on the analyte trend graph 1602 around 12:00 PM. Event display area 1612 can then be updated to show the graphical icon 1616 corresponding to the user having eaten around 12:00 PM. Similarly, the user can add an exercise icon around 6:30 PM. In some embodiments, the user can also enter event information via voice recognition or keyboard entry, and event display area 1612 can be automatically updated based on the user's input to show relevant icons such as meal icon 1616 and exercise icon 1618.

[0297] A user can also utilize a pointing device or touch screen to point to or touch a point on the analyte trend graph 1602 and activate a pop-up window 1620. The pop-up window 1620 can include more details related to the event data displayed in event data display area 1612. The pop-up window 1620 can include, for example, a timestamp of when the user has eaten, the type or amount, the type, intensity, and duration of any exercise performed by the user, some indication of the user's general feeling, and the type and amount of insulin taken by the user. The pop-up window 1620 can include a graphical arrangement of insulin data, such as insulin data including one or more of bolus or basal amount of insulin, time of administration of bolus insulin, time of administration of basal insulin, or active insulin value.

[0298] Some embodiments of graphical display 1500 or 1600 can include a chart key. Figure 17 An example of an insulin chart key 1700 is illustrated, which can optionally be generated and displayed along with graphical display 1500 or 1600. Chart key 1700 can include graphical displays 1702, 1704, 1706, 1708, and 1710 corresponding to different types of insulin that can be taken by a user; these can include, for example, temperature basal, bolus, extended bolus, continuous bolus, and basal, respectively.

[0299] Figure 18The modified graphical display 1800 can include an analyte trend graph 1802. Time is represented on a horizontal axis 1804. The magnitude of analyte data is represented on a vertical axis 1806. One or more quantities of insulin on board (IOB) data can be represented above or on the analyte trend graph 1802 by use of one or more arrows 1808 and 1810, where the size of the arrows 1808 and 1810 corresponds to the quantity of insulin on board (IOB) that each arrow refers to. Optionally, one or more numerical representations of the quantity of insulin on board (IOB) can be displayed on or above the arrows 1808 and 1810, such as text.

[0300] In an illustrative example of use of the modified graphical display 1800, the data set configuration can be formed to allow intuitive visualization of the meaning or effect of the IOB data that it contains and displays. For example, rather than just a number, insulin on board is visualized as a downward arrow above the glucose trend graph. This can be intuitive because it is physiologically understood that insulin drives glucose down. The more insulin on board, the larger the arrow (the greater the downward force). The number of units can also optionally be displayed with the arrow. In an example use case where the user has eaten and taken insulin, it can be useful to remind the user that they can not necessarily need to take more insulin again because the insulin has not yet acted, which in turn can prevent insulin stacking. In the opposite use case, such as if the user forgets to take insulin, the absence of an arrow (or a small arrow) can be a reminder that they have forgotten.

[0301] Algorithm visualization and decision support

[0302] Diabetes can be a complex disease in which patients find themselves having to make frequent treatment decisions. As a result, the mental demands and stress of managing diabetes can be burdensome to patients. The system 302 can utilize available data to present graphical displays that depict one or more relationships between analyte data and the user's past, current, and future actions to aid in the patient's analysis and health management.

[0303] Figure 19A and 19BModified graphical displays 1900A and 1900B generated from data structures and data arrangements according to embodiments can include visual elements that indicate one or more relationships of insulin data to analyte data based on historical, current, and predicted analyte values. Modified graphical display 1900A can include an analyte trend graph 1902. Time is represented on the horizontal axis, and a magnitude of analyte data is represented on the vertical axis. Graphical display 1900A can include a current value of analyte data 1912. Graphical display 1900A can be a predicted trend graph based on action, and can include one or more predicted graph lines 1904, 1906, and 1908 based on a user's action. These actions can include, for example, eating, exercising, or taking no action. Predicted graph lines 1904, 1906, and 1908 can be based on actions that the user has already taken or can be based on actions that the user is considering. Alternatively, the prediction can be depicted as a range 1910 as illustrated in graphical display 1900B. Depending on one or more reliability parameters, underlying prediction algorithms, graphical displays 1900A and 1900B can be displayed as general range predictions similar to hurricane estimated path visualizations, or graphical displays 1900A and 1900B can be displayed as single or multiple lines. Graphical displays 1900A and 1900B can be modified according to process 1310 as described above based on flags in the SRDS corresponding to parameters related to certainty or reliability of the prediction. The modifications can include fading the prediction range where one or more certainty parameters are deteriorated. The graphical display of the prediction can visually convey the relationship between a user's action and its likely effect on analyte data, thereby alleviating stress for the patient in making treatment decisions.

[0304] In another embodiment, a predictive bolus calculator can be used to visually inform a user of the effect of administering a bolus on future trends of analyte values in the subject. Figure 20 Modified graphical displays 2002, 2004, and 2006 can be included, where the amount of recommended (or intended) bolus is represented by graphical display 2008. Graphical display 2010 can depict a current value of analyte data and an indication of future trends of analyte data. Graphical displays 2008 and 2010 can be interactive through user interaction with graphical display 2008 or through an initiating action by system 302. Graphical display 2010 can be modified based on the effect of the recommended (or intended) bolus amount on future trends of analyte values in the subject. After the modification, graphical display 2012 can depict a predicted trend of analyte values resulting from administration of the recommended (or intended) bolus. In graphical display 2006, graphical displays 2014 and 2016 can revert to their previous shapes 2008 and 2010, respectively.

[0305] Figure 21A modified graphical display 2100 is illustrated according to embodiments depicting a scrollable list of user's action data and future analyte value trends. In some embodiments, a user can have a graphical interface module that includes a button 2102 to enable adding events (e.g., actions the user has taken, including meals, boluses, exercise, stress, etc.). The system 302 can generate a modified graphical display to display a scrollable list view of input events (e.g., meal event 2104 or meal + exercise event 2106) and one or more snapshots of analyte trend values 2108 and 2110 in a time period after the event time for the current time or for a recent time range. The user can visualize the causal relationship between their actions (input events) and their analyte levels. The user's clinical team can identify patterns and react accordingly to better manage the user's health. Optionally, in some embodiments, an algorithm can be used to infer or automatically suggest and / or link multiple events to determine one or more trends of future analyte data from patterns in the analyte data.

[0306] Figure 22 A modified graphical display is illustrated in simplified display 2200 depicting relationships between multiple complex variables. Diabetic patients often have to consider numerous complex variables and consider the relationships of the variables when making decisions about their diabetes management. The modified graphical display 2200 simplifies the mental process associated with analyzing complex multiple variables that inform a diabetic patient's decisions. In some embodiments, a current analyte value can be compared to high and low analyte thresholds and an analyte score generated. The amount of active insulin can be compared to high and low active insulin thresholds and an IOB score generated. An insulin status score can be generated by multiplying the analyte score and the IOB score. In some embodiments, other diabetes parameters can be analyzed and a score determined for each parameter. The scores can become part of the insulin status score as additional multipliers. These diabetes parameter scores can include, for example: an analyte trend score, a GPS location based score (e.g., a bar or restaurant or physical location where past data can indicate the location's impact on analyte values), a food related score, a physical exercise score, etc.

[0307] The insulin status score can be ranked and categorized based on the ranked score. In some embodiments, the three categories of insulin status score can simply be good (indicating that the patient is in good status with respect to the diabetes parameters), attention (indicating that the patient should pay attention and continue to monitor the diabetes parameters and make appropriate decisions), and poor (indicating that corrective action can be needed to remedy the situation). The display visual element 2200 can include a visual element that behaves like a traffic light, including three circles 2202, 2204, and 2206. Each circle can be filled with a distinct color, shading, or gradient that is different from the other circles. Depending on the ranked insulin score, one of the shades in the traffic light 2200 can be more prominently depicted, similar to the operation of a traffic light. For example, the shading in the circle 2206 in the traffic light 2200 can indicate a good status, the shading in the circle 2204 in the traffic light 2200 can indicate attention, and the shading in the circle 2202 in the traffic light 2200 can indicate a poor status.

[0308] In some embodiments, the lookahead module allows the user to selectively increase or decrease data related to current amounts or types of insulin, exercise (intensity, type, etc.), food intake (composition, amount, etc.), stress, illness, or other parameters that affect the health management of a diabetes patient and glucose values. For example, the user can use a swipe action on a touchscreen, or otherwise indicate an increase or decrease in a current or future event, activity, or glucose-related parameter input, and see the projected impact on the glucose trend graph in real time. The predicted effects can be generated using models based on a population of patients and their glucose-related data and / or based on machine learning over time for a particular user. The lookahead module helps the user make better diabetes-related decisions by observing predictions of the cumulative impact on glucose values based on a combination of factors. For example, a patient can observe a current glucose value of 100 mg / dL and consider eating a snack, going for a run, or taking a small dose of insulin. The lookahead module will allow the user to arbitrarily select a snack size / content, exercise type, duration, or intensity, and insulin dose type and size to find a desirable combination for proper glucose control. The lookahead module can work in conjunction with other devices. For example, Time Travel on an Apple Watch can trigger the predictions.

[0309] Figure 23 An example of a modified graphical display 2300 that efficiently provides information about the user's diabetes-related data is illustrated. Figure 23The glucose trend display 2302 shows excursions above the high threshold 2304 and below the low threshold 2306 visually distinguished by using one or more shaded areas 2310 and 2312 below the analyte trend curve 2308. The excursions above the high threshold 2304 and the excursions below the low threshold 2306 can be distinguished using different shading and, in the case of using colors, different colors.

[0310] In some embodiments, instead of or in addition to the trend graph 2308 of analyte values, a simpler graphical representation of current and future analyte values 2314 can be depicted. For example, a numerical display of current analyte values 2316 can be depicted along with a graph 2318 of a future trend prediction of analyte values. In some embodiments, the graph 2314 can be in the shape of a teardrop. The graph indicating the prediction can be a triangle 2318. The direction or orientation in which the triangle 2318 points can correspond to the prediction of future analyte values. For example, a triangle 2318 pointing sharply in an upward direction can indicate a prediction of a sharp rise in analyte concentration. A triangle 2318 pointing moderately in an upward direction can indicate a prediction of a moderate rise in analyte concentration. A triangle 2318 pointing in a horizontal direction can indicate a prediction of no significant change in analyte concentration. A triangle 2318 pointing moderately downward can indicate a prediction of a moderate decrease in analyte concentration. A triangle 2318 pointing sharply downward can indicate a prediction of a significant or marked decrease in analyte concentration. The skilled artisan can also envision the same or similar correlation between the direction of the triangle 2318 and the prediction of analyte concentration.

[0311] The analyte trend display 2304 can convey analyte concentration values in a 24 hour period or other time interval selected by the user or automatically selected by the system 302. An analyte trend graph 2320 can be generated with a plot of the magnitude of the analyte concentration values versus time. The trend graph 2320 can be depicted in relation to a high threshold 2321 and a low threshold 2322. Excursions above the high threshold 2321 can be depicted by shading the area below the curve between the trend graph 2320 and the high threshold line 2321. In the display 2304, examples of the upper threshold shading of the area below the curve include areas 2324 and 2326. Excursions below the low threshold line 2322 can be depicted by shading the area below the curve between the trend graph 2320 and the low threshold line 2322. In the display 2304, examples of the lower threshold shading of the area below the curve include areas 2328 and 2330.

[0312] Interactive UI display

[0313] Some graphical displays depicting glucose, insulin, or diabetes-related data can be too cluttered with scientific-looking graphs and displays. The present technology contemplates modified graphical displays that are friendly, neat, and easy to understand.

[0314] Figure 24A Modified graphical displays are illustrated in which a collapsible design layout is utilized when a user wishes to see more detail. A user can view one or more modified graphical displays at a time or all at once if desired. For example, modified graphical display 2402 depicts a three-hour analyte trend graph 2410 in an expanded view and IOB data 2412 in a collapsed view. A user can click or touch the collapsed IOB view 2412 and obtain an expanded IOB view 2414 in modified display 2404. A user can click or touch the expanded analyte trend graph 2410 and obtain a collapsed view 2416 in modified display 2406 or a collapsed view 2420 in modified display 2408. Some data depictions can cycle through various display forms to depict the same data in a variety of easy-to-understand formats. For example, a user can click the expanded IOB view 2414 to obtain a different graphical representation of IOB data 2418 as shown in modified graphical display 2408. Subsequent user clicks or touches can collapse the IOB view 2418 back to the IOB view 2412 as shown in modified display 2402.

[0315] Figure 24B and 24C Display screens are illustrated that present graphs that can be generated and modified according to embodiments of the disclosed methods and systems. In the example shown in Figure 24B , display screens 2422, 2424, 2426, and 2428 include example graphical displays that present current glucose 2430, glucose trend graph 2434, or active insulin 2432 information, as well as other health-related information. The features of display 2422 allow for user interaction to receive user input (e.g., by touch of a particular graphical feature of the display) and generate additional information based on the selected feature. For example, if a user were to select the IOB feature 2432, display 2422 can be modified to generate display 2428, which would present an enhanced view of IOB data (e.g., formatted differently in some embodiments, and / or enlarged in some embodiments) as well as descriptive information about what active insulin is and what it means, for example, in the context of the user's current glucose information. In Figure 24C , display screens that include graphical displays can be operated via software application icons (e.g., icon 2436) and / or event or notification display screens 2438 of the operating system of the mobile computing device.

[0316] Modified graphical displays of the present technology can utilize animations to better convey information. In some embodiments, various animations including pulsing and flashing can be used in combination with the graphical displays as described above. Figure 25 Modified graphical displays are illustrated in which animations can be used to convey health-related information. Various rates and speeds of pulsing or flashing can be used to convey different information. For example, pulsing in a heartbeat pattern can indicate that the modified graphical display is depicting real-time data. Utilizing such animations can present the graphical displays with more dynamic, lifelike, and human-like light; in turn, eliminating or reducing the likelihood of user error due to misinterpretation of the graphical display. In some embodiments, the arrow in the modified graphical display including the magnetic glass 2502 (the numerical value of the current glucose concentration in the center of the circle and the small arrow on the perimeter of the circle pointing to the trend of future glucose values) can pulse at different rates of speed to indicate information. For example, pulsing at a high rate can indicate an urgency. In some embodiments, various points on the glucose trend graphs 2504, 2506, and 2508 can pulse at different rates to indicate additional information. For example, the most recent point 2510 on the trend graph 2504 can pulse to indicate the current value. The pulsing can be different at different times of the day, for example, pulsing at a slower rate at night when the user is sleeping. Modifying the graphical displays with animations can also reassure the user that the system is active and currently monitoring. Alternatively, the lack of animations can indicate to the user that the system is offline or that the data illustrated can be stale.

[0317] If the modified graphical displays include personalization customizations from the user, the user is more likely to interact with the modified graphical displays with interest and attention. Figure 26 Modified graphical displays 2602, 2604, 2606, and 2608 are illustrated in which the user can customize the background image of one or more of the graphical displays to illustrate the user's health data in a theme of the user's choosing. The background in display 2602 has been customized to a Star Wars theme. The background in display 2604 has been customized to a nature, religious, or inspirational theme. The background in display 2606 has been modified to reflect or assist in studying for the SAT exam. The background in display 2608 has been customized to reflect a retro look and feel. The SRDS can be generated with a custom background image or other user customization. When modifying one or more of the graphical displays as described above, the custom background image or the user's chosen theme can be incorporated into the modified graphical display and presented to the user.

[0318] To improve the user's ability to input data into the system, various graphical user input interfaces can be used. In some embodiments, a graphical 2702 indicating a numeric keypad can be used. Figure 27The modified graphical display is illustrated such that the user is enabled to input numerical data into the system 302 using the scroll wheel 2704 and gestures that interact with the scroll wheel 2704. The scroll wheel 2704 can be programmed to only cycle through an acceptable range of values. Moving a finger in a clockwise direction 2706 on the scroll wheel 2704 can increase the inputted value, while moving a finger counter-clockwise 2708 on the scroll wheel 2704 can decrease the inputted value.

[0319] In a home where there are multiple analyte sensor systems 308 or displays 310, the user needs to be able to identify their respective device. Some diabetes monitoring and management systems currently in use do not provide visual aids other than requiring these homes to use different colored housings to distinguish different units. The present technology can allow for a modified graphical display where an indication of the source of collected analyte, glucose, or insulin data can be generated and flagged in the appropriate SRDS and then incorporated and presented as part of one or more of the modified graphical displays described above to the correct user. Figure 28 An exemplary modified display is illustrated where the user's initial is incorporated in the display to identify the source of analyte data.

[0320] In some embodiments, as part of the setup procedure for a new receiver or a receiver used by a new user, the user will be asked to select a uniquely identifiable marker, such as an initial, a screen background, a color theme, a screen saver, an animation, or a combination of the above. The user's selection can be displayed as part of the modified graphical display as described above. If an initial is selected, such as initial 2804 in modified display 2802, Figure 28 The initial 2804 can be displayed in a corner of the screen 2802 or in a status bar 2806 of the modified display 2808 when the screen 2802 is not displaying the modified graphical display. A screen saver can be applied when the screen is not displaying the modified graphical display. The selected theme can be flagged in the SRDS and applied to the physical font, background, etc. when the modified graphical display as described above is generated. The selected animation can also be flagged and referenced in the SRDS when the modified graphical display as described above is generated.

[0321] Other example graphical displays generated from SRDS

[0322] Figure 29The modified graphical display 2900 according to embodiments can be automatically modified when the predicted health state of the user approaches an undesirable state. In the context of diabetes management, for example, CGM readings from the user can indicate that the user is approaching a hyperglycemic or hypoglycemic condition that can generate an alert. An undesirable health condition such as hyperglycemia or hypoglycemia can be detected when the magnitude of the analyte concentration value exceeds a hyperglycemic level threshold or falls below a hypoglycemic level threshold. An alarm condition can be triggered when the analyte concentration value exceeds the high threshold or falls below the low threshold. The high and low thresholds that can generate an alarm condition can be user-defined, defined by a member of the user's support team, or can be automatically defined by the system 302 based on the user's data, profile, habits, past glucose trend values, or other parameters related to diabetes management. The graphical display 2900 can be initially generated to convey diabetes health management data such as the magnet glass 2902 and glucose trend graph 2904 relative to a previously defined or default high threshold line 2908 and low threshold line 2906. In some cases, the previously defined alarm threshold can allow too much time to elapse before the user is notified. For example, the previously defined alarm threshold can be old or defined based on health data of the user that is no longer applicable. In these cases, the user can be approaching a critical condition and experience negative health consequences before the user is notified. To encourage the user to take corrective action quickly, it is desirable to automatically modify the relevant threshold linked to the alarm condition and generate one or more alarms in a timely manner. In some embodiments, the system 302 can determine the rate at which the concentration of the analyte value is approaching the high or low threshold and determine the time at which the analyte concentration value can reach the threshold. If the determined time is equal to or less than a predetermined safe time, the system 302 can automatically modify the threshold linked to the alarm condition from its previously set value to the current analyte value to immediately trigger the alarm condition, notify the user, and stimulate corrective action.

[0323] For example, a low blood glucose alert condition can have been preset to trigger an alert if the user's blood glucose level falls below a low threshold 2906 corresponding to a blood glucose level drop of 70 mg / dL or more. A graphical display 2900 is generated that depicts an analyte trend graph 2904 and the low threshold line 2906, as well as other relevant diabetes management data, such as a magnetic glass 2902. The blood glucose readings and other data obtained about the user's condition can enable the system 302 to predict that a modification of the previously set alert condition is desirable. For example, the user's analyte measurements and event data can indicate that the user's blood glucose level is currently 110 mg / dL and is falling at a rate of 2 mg / dL per minute. At this rate, the user's blood glucose level can reach the alert level of 70 mg / dL in approximately 20 minutes. In some cases, it can be undesirable or unsafe to delay corrective action for 20 minutes. For example, 20 minutes or more of safe time can be required to effectively take corrective action and achieve results before the analyte concentration value reaches an unhealthy range. When the system 302 determines that the user will reach the threshold in less time than the safe time, the system can override the existing threshold linked to the alert condition, trigger the alert condition, and notify the user immediately. The system 302 can modify the graphical display 2900 as described above to raise the low threshold level 2906 to a new low threshold level 2910 corresponding to the current blood glucose level of 110 mg / dL. An alert is generated immediately and the user is notified. The user can take corrective measures to avoid a critical situation.

[0324] The modification of the graphical display 2900 and the threshold 2906 can be accompanied by an audible alert and visual cues to attract attention and inform the user of the change made. For example, the low threshold line 2906 can be moved upward to its new position 2910, with the movement of the threshold line accompanied by an audible alert, as well as a flashing or sweeping of the line 2906 to its new position 2910. An arrow 2912 can point in the direction of the movement, and flash, pulse, or otherwise draw attention to the change.

[0325] Figure 30Illustrated are modified graphical displays 3002, 3004, 3006, 3008, and 3010 generated from the data structure and data arrangement according to embodiments, where the graphical displays 3002, 3004, 3006, 3008, and 3010 include visual elements indicating ranges of analyte data. The system 302 can automatically, by default or via user input, define various ranges of analyte data concentrations. For example, a target range of analyte concentrations can be defined as when the analyte concentration values are between a desired high threshold and a low threshold value. Note that a range can be defined as when the analyte concentration values are between a desired high threshold and a low threshold value but close to one of those thresholds such that it is likely to exceed the desired high threshold or fall below the desired low threshold in a short time. Out of target range can be defined as when the analyte concentration values have exceeded the high threshold or fallen below the low threshold. The high and low thresholds to determine ranges of analyte data can be compiled based on anonymized data and / or analyte data of other users in similar locations as the user. The target range, note range, and out of target range can be user-defined or automatically defined by the system 302 based on guidelines from a healthcare organization or authority. For example, the target range can be defined from guidelines of the American Diabetes Association (ADA) as a fasting blood glucose level of less than 100 mg / dL and a 2-hour postprandial glucose level of less than 140 mg / dL. In some embodiments, analyte concentration values that are 20% out of the ADA guidelines can be considered in the note range. For example, analyte concentration values below 80 mg / dL when fasting are considered in the target range; analyte concentration values between 80 mg / dL and 100 mg / dL when fasting are considered in the note range, and analyte concentration values out of 100 mg / dL are considered out of the target range.

[0326] Graphical displays 3002, 3004, 3006, 3008, and 3010 illustrate the magnitude of analyte data on the vertical axis and time on the horizontal axis. When generating graphical displays 3002, 3004, 3006, 3008, and 3010, various visual techniques can be used to modify the analyte data to indicate the range of analyte data. Graphical display 3002 illustrates a modified graphical display of a plot of the magnitude of analyte concentration values versus time, where the plot is modified with varying contrast or line style to illustrate the range of analyte data. In other embodiments, color coding can be used to distinguish between target, attention, and out of target ranges. The self-reference data set that generates display 3002 can be modified where analyte data is flagged by its indication of range (e.g., target, attention, and out of target). When generating graphical display 3002, each flag can be given a line style, contrast, thickness, or other distinguishing visual indicator, and based on these indicators subsequent pixels can be generated on display 3002. In example embodiment 3002, analyte data in the target range can be flagged and shown with line style 3012. Analyte data in the attention range can be flagged and its corresponding flag associated with line style 3014. Out of target range analyte values can be flagged and its corresponding flag can be assigned line style 3016. As described, other visual indicators can be used, such as color, gradient, other line style, or animation. The visual indicators associated with attention or out of target range can be selected to quickly attract and draw attention to the communicated information. For example, a darker contrast line 3016 can be used to indicate out of target analyte values.

[0327] Graphical display 3004 is similar to graphical display 3002. Analyte data in the target range can be further indicated via a rectangle 3018 around the target analyte values. Analyte values in the attention range can be highlighted with an area under the curve shaded in style 3020. Out of target analyte values can be highlighted with an area under the curve shaded in style 3022 different from style 3020 to provide visual distinction and attract the user's attention.

[0328] Graphical display 3006 is similar to graphical display 3004. Analyte values in the target range have been subtracted and are not illustrated to highlight analyte values in the attention and out of target ranges, which can present health problems and can require attention and corrective action. Graphical display 3006 allows the user to view analyte values 3024 in the attention range and out of target analyte values 3026

[0329] Graphical displays 3008 and 3010 use an adaptive target zone technique whereby the graphical display is modified to account for analyte data changes that are expected to occur whether or not diabetes is present. For example, a non-diabetic patient will experience a peak in blood glucose level after a meal, similar to a diabetic patient. For example, graphical display 3008 can be modified to adjust the attention zone 3028 based on event data obtained from the user and / or the sensor. Such adjustments can be needed to avoid unnecessarily alarming the user. For example, if a meal event is detected, an increase in the user's blood glucose level can be expected and is normal. The attention range 3028 in the relevant time range can be adjusted to account for the expected increase in blood glucose level, for example by coloring the area under the curve in the attention zone 3028 with the same shading as for the target analyte value. Graphical display 3010 uses the same adaptive target zone technique as described with respect to display 3008; however, the analyte values in the target range have been subtracted and are not illustrated, to further highlight and draw attention to the analyte values in the attention range 3030 and the analyte values in the out-of-target range 3032.

[0330] Figure 31Illustrated graphical displays generated from data structures and data arrangements according to embodiments in which the graphical displays 3102, 3104, 3106, 3108, 3110, and 3112 contain visual elements indicative of the status of the analyte monitoring system, the health status of the user, trends, alerts, or other data related to the health of the user. The illustrated graphical displays can increase contrast and improve readability using an inverted or dark background 3114, for example. An updated current analyte value reading 3116 can be displayed via a display numeral, for example 100 mg / dL. An analyte trend indicator 3118 can be displayed nested next to the updated current glucose 3116. The analyte trend indicator 3118 contains an arrow 3117 enclosed by a circle 3122, where the direction of the arrow 3117 indicates the future trend of the analyte data. The circle 3122 enclosing the arrow 3117 can be filled with a shading pattern adapted to indicate the trend or direction of future analyte values and / or provide contrast to the background 3114 to improve readability. In some embodiments, the trend indicator 3118 contains a faded ring 3119 enclosing the circle 3122. A textual description 3120 of the status and / or trend of the analyte data values can be displayed near or above the current value of the analyte data 3116 (e.g., "in range and steady"). The display 3102 can contain an analyte graph 3124 in which the magnitude of the analyte concentration values are plotted on the vertical axis and time is plotted on the horizontal axis. A dot 3126 can indicate the current analyte value on the analyte graph 3124. The dot 3126 is enclosed by a faded ring, which in some embodiments can pulse at the same rate and in the same pattern as the faded ring 3119 of the analyte indicator 3118. The analyte graph 3124 also plots a high threshold line 3128 corresponding to an upper range of desirable analyte concentration values. The graph 3124 also plots a low threshold line 3130 corresponding to a lower range of desirable analyte concentration values.

[0331] Display 3104 is similar to display 3102. The user's current glucose level 3116 has reached 200 mg / dL, the upper range of desirable analyte concentration values. Trend indicator 3118 has been updated to indicate the current and characteristic trend of analyte concentration values. Arrow 3117 has been updated to point upward moderately. Circle 3122 is updated and filled in with a coloration pattern 3132 different from that of circle 3122 to draw attention to the current high analyte concentration value. Textual description 3120 has also been updated with appropriate text to indicate that the analyte concentration value is high and rising. High threshold line 3128 has been updated and rendered in a pattern 3134 different from that of line pattern 3128 to draw attention to the high current value of analyte concentration. In some embodiments, the different pattern of line 3134 can include rendering the line in a thicker body, higher contrast pattern to draw the user's attention. Dot 3126 is updated and rendered in a pattern 3136 different from that used to produce dot 3126 to further draw attention to the high value of analyte concentration. Dot 3136 and circle 3132 can be rendered in the same pattern and the dimming ring surrounding them can pulse at the same rate to draw attention to the high analyte concentration value. In some embodiments, high threshold line 3134 can pulse at the same rate as dot 3136, circle 3132, or the dimming ring surrounding them.

[0332] Display 3106 is similar to display 3102. The user's current glucose level 3116 has dropped to 54 mg / dL, the lower limit of desirable analyte concentration values. Trend indicator 3118 has been updated to indicate the current and future trend of analyte concentration values. Arrow 3117 has been updated to change shape and point significantly downward. Circle 3122 is updated and filled in with a coloration pattern 3138 different from that of circle 3122 to draw attention to the current low analyte concentration value. Textual description 3120 has also been updated with appropriate text to indicate that the analyte concentration value is low and continues to drop rapidly. Low threshold line 3130 has been updated and rendered in a pattern 3140 different from that of line pattern 3130 to draw attention to the low current value of analyte concentration. In some embodiments, the different pattern of line 3140 can include rendering the line in a thicker body, higher contrast pattern to draw attention. Dot 3126 is updated and rendered in a pattern 3142 different from that used to produce dot 3126 to further draw attention to the low value of analyte concentration. Dot 3142 and circle 3138 can be rendered in the same pattern and the dimming ring surrounding them can pulse at the same rate to draw attention to the low analyte concentration value. In some embodiments, low threshold line 3140 can pulse at the same rate as dot 3142, circle 3138, or the dimming ring surrounding them.

[0333] The above with respect to Figure 31The display of the user data, numbers, thresholds, graphs, and future predictions described are exemplary, and other user data can trigger different displays, text, graphs, and / or thresholds without departing from the spirit of the described technology.

[0334] As described, an analyte graph 3124 of analyte data values can be displayed, in which the magnitude of analyte values over a period of time are plotted. The current value of analyte data can be indicated by a pulsing graphic 3126, such as a graphic including one or two concentric circles that gradually fade in a radial direction. The analyte graph 3124 and the data structure that generates the analyte graph 3124 can be dynamically updated based on current analyte sensor data. The data structure that generates the display 3102, 3104, 3106, or similar displays can be modified to display one or more pulsing animations, which can be pulsed in synchronization to further draw the user's attention to information related to health management. Examples of display elements that can be modified or reproduced with a pulsing animation include the trend indicator 3118, the current analyte value point 3126, and the threshold lines 3128 and 3130.

[0335] Other status information related to the operation of the analyte monitoring system can be communicated via the modified graphical displays 3108, 3110, and 3112. For example, the modified graphical display 3108 can indicate via text 3144 and 3146 that the analyte sensor is warming up and how much time can remain before the sensor is ready. A status bar 3148 can also provide a visual element of the status of the sensor. The graphical displays 3110 and 3112 are modified graphical displays reporting the status of the system 302. For example, the graphical display 3110 illustrates a situation in which a signal loss from the glucose sensor is encountered. The signal loss can be indicated via text and graphical display elements 3150. The analyte graph 3124 no longer displays the current analyte value point 3126. Other information such as the current analyte concentration 3116 and the analyte trend indicator 3118 are also not displayed. The signal loss is indicated with text, graphical displays, icons, and symbols 3150 and alerts the user. In the graphical display 3112, the sensor is not detected, and text, graphical symbols, and / or icons 3152 are used to indicate that there is no analyte sensor and to invite the user to connect an analyte sensor.

[0336] For ease of explanation and illustration, in some instances the DETAILED DESCRIPTION describes exemplary systems and methods in terms of a continuous glucose monitoring environment; however, it should be understood that the scope of the present application is not limited to the particular environment and that it should be understood by those skilled in the art that the systems and methods described herein can be implemented in various forms. Accordingly, any structural and / or functional details disclosed herein are not to be interpreted as limiting the systems and methods, but rather as providing representative embodiments and / or arrangements of attributes for teaching one or more ways in which the systems and methods can be beneficially employed in other contexts.

[0337] By way of example, and without limitation, the described monitoring systems and methods can include measuring one or more analytes (e.g., glucose, lactate, potassium, pH, cholesterol, isoprene, and / or hemoglobin) and / or other blood or body fluid components or concentrations related thereto of a subject and / or another party.

[0338] By way of example, and without limitation, the monitoring systems and methods embodiments described herein can include a finger stick blood sample, a blood analyte test strip, a non-invasive sensor, a wearable monitor (e.g., a smart wristband, a smart watch, a smart ring, a smart necklace or pendant, an exercise monitor, a fitness monitor, a health and / or medical monitor, a clamp-on monitor, etc.), an adhesive sensor, a smart textile and / or garment incorporating a sensor, a shoe insert and / or insole including a sensor, a transdermal (i.e., transcutaneous) sensor, and / or a swallowed, inhaled, or implantable sensor.

[0339] In some embodiments, and without limitation, the monitoring systems and methods can include other sensors for measuring information of and / or related to a subject and / or another party in addition to or instead of the sensors described herein, such as an inertial measurement unit including an accelerometer, a gyroscope, a magnetometer, and / or a barometer; a motion, altitude, location, and / or positioning sensor biometric sensor; an optical sensor including, for example, an optical heart rate monitor, a photoplethysmogram (PPG) / pulse oximeter, a fluorescence monitor, and a video camera; a wearable electrode; an electrocardiogram (EKG or ECG), electroencephalography (EEG), and / or electromyography (EMG) sensor; a chemical sensor; a flexible sensor, such as for measuring stretch, displacement, pressure, weight, or impact force; a galvanic sensor, a capacitive sensor, an electric field sensor, a temperature / thermal sensor, a microphone, a vibration sensor, an ultrasonic sensor, a piezoelectric / piezoresistive sensor, and / or a transducer.

[0340] In this document, the terms “computer program medium,” “computer-usable medium,” and “computer-readable medium,” and variations thereof, are used to generally refer to transient or non-transitory media, such as main memory, memory cell interfaces, removable storage media, and / or channels. These and other various forms of computer program media or computer-usable / readable media may relate to loading one or more sequences of one or more instructions onto a processing device for execution. These instructions implemented on the medium may be generally referred to as “computer program code,” “computer program product,” or “instructions” (which may be grouped as computer programs or other groups). When executed, such instructions may cause a computing module or its processor, or a processor connected thereto, to perform the features or functions of this disclosure as discussed herein.

[0341] Various embodiments have been described with reference to specific example features of the embodiments. However, it will be apparent that various modifications and changes can be made to the specification without departing from the broader spirit and scope of the various embodiments set forth in the appended claims. Therefore, this specification and drawings should be viewed in an illustrative rather than restrictive sense.

[0342] Although the invention has been described above with respect to various exemplary embodiments and implementations, it should be understood that the applicability of the various features, aspects, and functionalities described in one or more of the individual embodiments is not limited to the specific embodiments described therewith, but can be applied individually or in various combinations to one or more other embodiments of this application, whether or not such embodiments are described and whether or not such features are presented as part of the described embodiments. Therefore, the breadth and scope of this application should not be limited by any of the foregoing exemplary embodiments.

[0343] Unless otherwise expressly stated, all terms and phrases used in this application, and their variations thereof, should be interpreted as open-ended, contrary to limitation. Examples of the foregoing: the term “comprising” should be understood to mean “including but not limited to”, etc.; the term “example” is used to provide illustrative examples of the items discussed, not an exhaustive or limiting list thereof; the term “a” should be understood to mean “at least one,” “one or more,” etc.; and adjectives such as “conventional,” “traditional,” “usual,” “standard,” “known,” and similar terms should not be interpreted as limiting the described items to items available within a given time period or at a given time, but should actually be understood to cover conventional, traditional, usual, or standard techniques now known or available at any time in the future. Similarly, while this document refers to techniques that would be obvious or known to a person skilled in the art, such techniques encompass those techniques that are obvious or known to a person skilled in the art now or at any time in the future.

[0344] In some instances the presence of broadening words and phrases such as "one or more," "at least," "but not limited to," or other similar phrases should not be understood as implying that more narrow instances are intended or required where such broadening phrases are not present. The use of the term "module" does not imply that the components or functions described or claimed as part of the module are all configured in one common package or housing. Indeed, any or all of the various components of a module, whether control logic or other components, can be combined in a single package or separately maintained and can further be distributed in multiple groupings or packages or across multiple locations.

[0345] In addition, various embodiments presented herein are described in terms of example block diagrams, flow charts and other illustrations. As those skilled in the art will readily appreciate, the shown embodiments and their various alternatives can be implemented without departing from the spirit or scope of the described embodiments. For example, the block diagrams and their accompanying descriptions should not be construed as requiring a particular architectural configuration or configuration.

Claims

1. A computer-implemented method, comprising: The mobile computing device receives analyte data from a continuous analyte sensor device, wherein the analyte data includes analyte concentration values ​​associated with measurements over time. An arrangement for processing the analyte data at the mobile computing device to generate analyte concentration values ​​at multiple time intervals; A graph of the arrangement that produces the concentration values ​​of the analyte; Modify the graph to indicate one or more patterns in the analyte data; as well as The modified graphics are displayed on the mobile computing device; The process further includes: Aggregate the grouping of aggregated analysis data; The groups of analyte data are flagged based on additional information corresponding to one or more graphical displays; The flagged groups for analyte concentration values; and The group of analyte concentration values ​​is generated from the reference dataset; The generation of the self-reference dataset further includes one or more of the following: Flag the analyte data based on one or more high and low thresholds for the analytes in the subject; Flagging of the analyte data based on statistical analysis performed on the analyte data; and The analyte data is flagged based on contextual data related to the time when the analyte data was obtained.

2. The method of claim 1, wherein the context data includes: Data indicating one or more physical locations from which analyte data is obtained, the relationship between the subject and the physical location, the frequency of access to the physical location, meals, type and intensity of exercise, type and amount of insulin administered, and the likelihood that the subject was asleep or awake when the analyte data was obtained.

3. The method according to claim 1 or 2, wherein the graphic arrangement that generates the analyte concentration value further comprises: Receive user input, including the user's desired graphical display; Receive display configuration data; The self-reference dataset is regenerated when it does not contain data useful for forming the desired graphical display. as well as The self-reference dataset is reformatted based on the user's input and the display configuration data.

4. The method of claim 1, wherein modifying the graph to indicate one or more patterns in the analyte data comprises: Scan the self-reference dataset to obtain threshold flags and modify the graph based on the threshold flags; Scan the self-reference dataset to obtain statistical analysis flags and modify the graph based on the statistical analysis flags; as well as The self-reference dataset is scanned to obtain the context data flags for the analyzed object, and the graph is modified based on the context data flags.

5. The method of claim 1, wherein modifying the graphic includes introducing or using one or more of the following: different colors, gradients of shadows, transparency, buffers, graphic icons, animations, text, numbers, or gradual fading.

6. The method of claim 1, wherein modifying the graphic includes introducing or using one or more of the following: different colors, gradients of shadows, opacity, buffers, graphic icons, animations, text, numbers, or gradual fading.

7. The method of claim 1, wherein modifying the graphic includes introducing or using one or more of the following: different colors, gradients of shadows, transparency, buffers, arrows, animations, text, numbers, or gradual fading.

8. The method of claim 1, wherein modifying the graphic includes introducing or using one or more of the following: color gradient, shadow gradient, transparency, buffer, graphic icon, animation, text, or numbers.

9. The method of claim 1, wherein the arrangement comprises a spatial-temporal organization of the analyte concentration values, wherein the analyte concentration values ​​are positioned along a first direction according to a first time scale and along a second direction according to a second time scale, and the analyte level of the analyte concentration values ​​is constituted by one or more of shape, color, shading, or size based on the magnitude of the analyte level.

10. The method of claim 9, wherein the first direction and the second direction are linear directions.

11. The method of claim 9, wherein the first direction is a bending direction and the second direction is a radial direction.

12. The method according to any one of claims 9 to 11, wherein the first time scale is hourly and the second time scale is daily.

13. The method of claim 9, wherein the first time scale is hourly and the second time scale is daily, wherein the modified graph includes analyte level traces overlaid on the modified graph such that higher analyte levels are closer to the outer curvature of the graph and lower analyte levels are closer to the inner curvature of the graph, or vice versa.

14. The method of claim 13, wherein the higher analyte level is a first color, the lower analyte level is a second color, and the analyte level between the higher and lower analyte levels is a third color.

15. The method of claim 13, wherein the analyte level trace comprises the average analyte level of the daily analyte concentration values.

16. The method of claim 13, wherein the analyte level trace includes the current analyte level on the hourly timescale.

17. The method of claim 1, wherein modifying the graphic comprises: The arrangement of the analyte concentration values ​​at the plurality of time intervals is modified by the clustering of colors, the gradient of shadows, the arrangement of zones, or the lighter or darker shadows of overlapping zones.

18. The method of claim 1, wherein modifying the graphic comprises: The arrangement of the analyte concentration values ​​at the plurality of time intervals is modified by the gradient of color, the gradient of shadow, the arrangement of areas, or the lighter or darker shadows of overlapping areas.

19. The method of claim 1, wherein the one or more modes indicate the analyte concentration values ​​relative to high and low analyte level thresholds of the subject.

20. The method of claim 1, wherein the plurality of time intervals comprises a 24-hour cycle over a 7-day period.

21. The method of claim 1, wherein the graph comprises an isometric curve plotted over a 24-hour period over 7 days.

22. The method of claim 21, wherein the isometric graph can be displayed in a three-dimensional view.

23. The method of claim 1, wherein the pattern comprises concentric rings.

24. The method of claim 1, wherein the graph comprises a sector graph.

25. The method of claim 1, wherein the graph comprises one or more line graphs.

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