SYSTEM AND NON-TRANSITORY COMPUTER READABLE MEDIUM FOR VISUALIZING HEALTH DATA - Patent application

Abstract

To provide systems and methods for generating graphical display of analyte data and / or health information.SOLUTION: In some implementations, the graphical display is generated based on a self-referential dataset modifiable based on identified portions of the data. The modified graphical display can indicate features in the analyte data of a receptor.SELECTED DRAWING: Figure 1A

Description

[Technical field]

[0001] INCORPORATION BY REFERENCE OF RELATED APPLICATIONS Any and all priority claims identified in the Application Data Sheet, or any corrections thereto, are incorporated herein by reference pursuant to the provisions of 37 CFR 1.57. This application claims the benefit of U.S. Provisional Patent Application No. 62 / 374,539, filed August 12, 2016. The aforementioned application is incorporated herein by reference in its entirety and expressly made a part hereof.

[0002] The present disclosure relates generally to continuous monitoring of analyte values ​​received from an analyte sensor system and, more particularly, to systems, methods, apparatus, and devices for generating dynamic data structures and graphical displays. [Background technology]

[0003] Diabetes mellitus is a disease in which the pancreas cannot produce enough insulin (type I or insulin-dependent) and / or in which insulin is ineffective (type 2 or non-insulin-dependent). In the diabetic state, the victim suffers from hyperglycemia, which causes a series of physiological deformities associated with the deterioration of small blood vessels (kidney failure, skin ulcers, or bleeding into the vitreous of the eye). A hypoglycemic reaction (hypoglycemia) can be induced by an accidental overdose of insulin or after normal administration of insulin or glucose-lowering agents accompanied by abnormal exercise or inadequate food intake.

[0004] Traditionally, diabetics carry self-monitoring blood glucose (SMBG) monitors, which typically require an uncomfortable finger-prick method. Due to lack of comfort and convenience, diabetics typically measure their blood glucose levels only two to four times per day. Unfortunately, these time intervals are now widening, and diabetics are more likely to be alerted to hyperglycemic or hypoglycemic conditions too late, resulting in dangerous side effects. In fact, not only are diabetics less likely to take SMBG readings in a timely manner, but due to limitations of the traditional method, they will not know if their blood glucose levels are rising (higher) or falling (lower).

[0005] As a result, a variety of non-invasive, transcutaneous (e.g., transdermal) and / or implantable electrochemical sensors have been developed to continuously detect and / or quantify blood glucose levels. Continuous glucose monitors have become popular as a simple method for monitoring blood glucose levels. Traditionally, patients sample blood glucose levels several times throughout the day, such as in the morning, around lunchtime, and in the evening. Blood glucose levels can be measured by taking a small blood sample from the patient and measuring the blood glucose level with a test strip or blood glucose meter. However, this technology has drawbacks because patients would prefer not to have to take blood samples and the user does not know what the blood glucose level is between samples throughout the day.

[0006] One potentially dangerous time frame is at night, as a patient's blood glucose levels can become dangerously low while they are sleeping. As a result, continuous glucose monitors have gained popularity by providing a sensor that continuously measures a patient's blood glucose levels and wirelessly transmits the measured blood glucose levels to a display. This allows the patient or the patient's caregiver to monitor the patient's blood glucose levels throughout the day and even set alarms for when the blood glucose levels reach predetermined levels or experience defined changes.

[0007] First, a continuous blood glucose monitor wirelessly transmits blood glucose levels and related data to a dedicated display. A dedicated display is a medical device designed to display blood glucose levels, trend patterns, and other information to a user. However, with the growing popularity of smartphones and software applications (apps) that run on smartphones, some users prefer not to have to carry a dedicated display. Instead, some users prefer to monitor their blood glucose levels using a dedicated software application that runs on a mobile computing device, such as a smartphone, tablet, or a wearable device such as a smart watch or smart glasses. Still other users may prefer the flexibility of having access to glucose and glucose-related data on other mobile or stationary computing devices in addition to a dedicated display. Summary of the Invention [Means for solving the problem]

[0008] One embodiment includes a system including a continuous analyte sensor configured to obtain analyte measurements of a receptor; a wireless transmitter configured to receive analyte measurements from the continuous analyte sensor and at least partially process the analyte measurements to generate one or more datasets of analyte data, each dataset including analyte concentration values ​​associated with a time for one or more of the analyte measurements, the wireless transmitter including 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 datasets from the wireless transmitter to generate a graphical display on the mobile computing device, the graphical display including an array of analyte concentration values ​​over a plurality of time intervals graphically modified to indicate one or more patterns in the analyte data.

[0009] In one aspect of the system, the analyte data processing module is further configured to aggregate the analyte data sets, flag the analyte data sets based on additional information corresponding to one or more graphical representations, sequence the flagged sets of analyte concentration values, and generate a self-referencing data set from the sequenced sets of analyte concentration values.

[0010] In one aspect, generating the self-referencing dataset further includes one or more of flagging the analyte data based on one or more high and low thresholds of the analyte in the receptor, flagging the analyte data based on performing a statistical analysis of the analyte data, and flagging the analyte data based on contextual data associated with when the analyte data was obtained.

[0011] In one aspect, the contextual data includes one or more physical locations from which the analyte data was obtained, the relationship of the receptor to the physical locations, the frequency with which the physical locations are visited, meals consumed, type and intensity of exercise, type and amount of insulin administered, and data indicative of the likelihood that the receptor was asleep or awake when the analyte data was obtained.

[0012] In another aspect, the specimen data processing module is further configured to generate a graphical display on the mobile computing device by receiving user input including a user desired graphical display, receiving display configuration data, regenerating the self-referencing dataset when the self-referencing dataset does not include data for forming the desired graphical display, and reformatting the self-referencing dataset based on the user input and the display configuration data.

[0013] In some aspects, the specimen data processing module is further configured to modify the graphical display by scanning the self-referencing dataset for a threshold flag and modifying the graphical display based on the threshold flag, scanning the self-referencing dataset for a statistical analysis flag and modifying the graphical display based on the statistical analysis flag, and scanning the self-referencing dataset for a specimen contextual data flag and modifying the graphical display based on the contextual data flag.

[0014] In one aspect, modifying the graphical display includes introducing or using one or more of color, color or shade gradients, transparency, opacity, buffer areas, graphic icons, arrows, animations, text, numbers, and gradual fading.

[0015] In one aspect, the array comprises a spatiotemporal organization of analyte concentration values ​​where 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 levels of the analyte concentration values ​​are configured with one or more of a shape, color, shading, or size based on the magnitude of the analyte level.

[0016] In one embodiment, the first direction and the second direction are linear directions.

[0017] In another embodiment, the first direction is a curved direction and the second direction is a radial direction.

[0018] In some embodiments, the first time scale is hourly and the second time scale is daily.

[0019] In one embodiment, the first time scale is hourly and the second time scale is daily, and the graphical modification includes analyte level traces superimposed across the graphical display such that higher analyte levels are closer to the outer curved region of the graphical display and lower analyte levels are closer to the inner curved region of the graphical display, or vice versa.

[0020] In one embodiment, 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.

[0021] In one embodiment, the analyte level trace comprises an average analyte level for the daily analyte concentration values.

[0022] In one aspect, the analyte level trace comprises the current analyte level over an hourly time scale.

[0023] In another aspect, modifying the graphical display includes displaying color clustering, color or shade gradients, alignment of regions, or lighter or darker shades of overlapping regions to modify the sequence of analyte concentration values ​​over multiple time intervals.

[0024] In one embodiment, the one or more patterns indicate analyte concentration values ​​relative to a high analyte level threshold and a low analyte level threshold for a receptor.

[0025] In one embodiment, the multiple time intervals comprise 24 hour periods over a 7 day period.

[0026] In one embodiment, the graphical display includes an isometric graph plotted over a 24 hour period over a seven day period.

[0027] In one embodiment, the isometric graph can be displayed in a three-dimensional view.

[0028] In one aspect, the graphical display includes concentric rings.

[0029] In another aspect, the graphical display includes a sector graph.

[0030] In one embodiment, the graphical display includes one or more line graphs.

[0031] Another embodiment includes a computer-implemented method including receiving, on a mobile computing device, analyte data obtained from a continuous analyte sensor device, the analyte data including analyte concentration values ​​each associated with a measurement of time; processing the analyte data on the mobile computing device to generate an array of analyte concentration values ​​over a plurality of time intervals; generating a graphic of the array of analyte concentration values; modifying the graphic to indicate one or more patterns in the analyte data; and displaying the modified graphic on the mobile computing device.

[0032] In some embodiments, the processing further includes aggregating the analyte data sets, flagging the analyte data sets based on additional information corresponding to one or more graphical representations, ordering the flagged sets of analyte concentration values, and generating a self-referencing data set from the ordered sets of analyte concentration values.

[0033] In one aspect, generating the self-referencing dataset further includes one or more of flagging the analyte data based on one or more high and low thresholds of the analyte in the receptor, flagging the analyte data based on performing a statistical analysis of the analyte data, and flagging the analyte data based on contextual data associated with when the analyte data was obtained.

[0034] In one embodiment, the contextual data may include one or more physical locations from which the analyte data was obtained, the relationship between the receptor and the physical locations, the frequency with which the physical locations are visited, meals consumed, type and intensity of exercise, type and amount of insulin administered, and data indicative of the likelihood that the receptor was asleep or awake when the analyte data was obtained.

[0035] In another aspect, generating the graphic of the array of analyte concentration values ​​further includes receiving user input including a user desired graphical display, receiving display configuration data, regenerating the self-referencing dataset when the self-referencing dataset does not include data for forming the desired graphical display, and reformatting the self-referencing dataset based on the user input and the display configuration data.

[0036] In another aspect, modifying the graphic to indicate one or more patterns in the specimen data may include scanning the self-referencing dataset for a threshold flag, modifying the graphic based on the threshold flag, scanning the self-referencing dataset for a statistical analysis flag, modifying the graphic based on the statistical analysis flag, scanning the self-referencing dataset for a specimen contextual data flag, and modifying the graphic based on the contextual data flag.

[0037] In one aspect, modifying the graphics includes introducing or using one or more of color, color or shade gradients, transparency, opacity, buffer areas, graphic icons, arrows, animations, text, numbers, and gradual fading.

[0038] In one aspect, the array comprises a spatiotemporal organization of analyte concentration values ​​where 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 levels of the analyte concentration values ​​are configured with one or more of a shape, color, shading, or size based on the magnitude of the analyte level.

[0039] In one embodiment, the first direction and the second direction are linear directions.

[0040] In another embodiment, the first direction is a curved direction and the second direction is a radial direction.

[0041] In one embodiment, the first time scale is hourly and the second time scale is daily.

[0042] In another embodiment, the first time scale is hourly and the second time scale is daily, and the modified graphic includes analyte level traces superimposed across the modified graphic such that higher analyte levels are near the outer curved region of the graphic and lower analyte levels are near the inner curved region of the graphic, or vice versa.

[0043] In one embodiment, 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.

[0044] In one embodiment, the analyte level trace comprises an average analyte level for the daily analyte concentration values.

[0045] In another aspect, the analyte level trace comprises the current analyte level over an hourly time scale.

[0046] In some aspects, modifying the graphic may include modifying the arrangement of analyte concentration values ​​over multiple time intervals, color clustering, color or shade gradients, alignment of regions, or lighter or darker shading of overlapping regions.

[0047] In some embodiments, the one or more patterns indicate analyte concentration values ​​relative to a high analyte level threshold and a low analyte level threshold for a receptor.

[0048] In one embodiment, the multiple time intervals comprise 24 hour periods over a 7 day period.

[0049] In one embodiment, the graphic comprises an isometric graph plotted over a 24 hour period over a seven day period.

[0050] In another embodiment, the isometric graph can be displayed in a three-dimensional view.

[0051] In one aspect, the graphic includes concentric rings.

[0052] In one aspect, the graphic includes a sector graph.

[0053] In another embodiment, the graphic includes one or more line graphs.

[0054] Another embodiment includes a system including a continuous analyte sensor configured to obtain receptor glucose data; and 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 further configured to receive the receptor insulin data, the receptor glucose data, and the receptor event data and to generate a graphical display on a mobile computing device, the processing module further modifying the graphical display to display a visual representation showing one or more relationships of the insulin data, glucose data, and event data to each other or over time.

[0055] In one embodiment, the event data includes one or more of insulin administration, carbohydrate intake, or exercise.

[0056] In one aspect, the insulin data includes a value for remaining insulin and the visual representation includes a colored ring indicating remaining insulin and an estimated time remaining for remaining insulin.

[0057] In one aspect, the visual representation includes a trend graph of the glucose data and an interactive callout window associated with an area or feature of the trend graph that is presented when a user selects an area or feature of the trend graph on the graphical display, the presented callout window including at least some of the insulin data and / or the event data.

[0058] In another aspect, the presented callout window is configured to display a graphical array of insulin data including one or more of bolus or basal insulin, bolus insulin administration time, basal insulin administration time, or remaining insulin value.

[0059] In one aspect, the presented callout window is configured to display a graphical array of event data including one or more of carbohydrate intake, amount of time spent exercising, amount of calories burned, or heart rate reaching a threshold or time associated therewith.

[0060] In one aspect, the visual representation includes an arrow corresponding to the insulin data and a glucose reading including a glucose trend corresponding to the glucose data, the arrow being displayed adjacent to the trend graph and modified to show the effect of the insulin data on the glucose data.

[0061] In some aspects, the visual representation includes a trend graph of the historical glucose data and the future glucose data, where the future glucose data is determined based on the insulin data and the receptor operation data.

[0062] In another aspect, the visual representation includes a first graphical display illustrating 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, where the second graphical display may interact with the first graphical display to illustrate a potential impact of the amount of insulin on the indication of the future trend of the glucose data.

[0063] In one aspect, the processing module is further configured to generate one or more data sets each based on the receptor behavior and a prediction of the glucose data trend based on the receptor behavior, and the visual representation includes a scrollable list including one or more modified graphs each based on the one or more data sets.

[0064] In another aspect, the processing module is further configured to compare the current glucose value to a high glucose threshold and a low glucose threshold and generate a glucose score, compare the current remaining insulin to a high insulin threshold and a low insulin threshold and generate an IOB score, generate an insulin status by multiplying the glucose score and the IOB score, and rank the insulin score in one of a plurality of categories.

[0065] In one aspect, the plurality of categories includes good, caution, and bad.

[0066] In one aspect, the visual representation includes a color-coded display, where each of a plurality of categories is associated with a different color, and the colors associated with the ranked insulin scores are illustrated.

[0067] In another aspect, generating the insulin status further comprises multiplying the trend value.

[0068] In one embodiment, generating the insulin status further comprises multiplying one or more scores based on location, food intake, and exercise.

[0069] In one aspect, the visual representation includes a numerical display of the current glucose value and a graphic representing a prediction of the future trend of the glucose value.

[0070] In some aspects, the system includes a look-ahead module configured to receive receptor input data associated with future event data, and the visual representation includes a glucose trend graph, and upon modifying the input data, the visual representation is modified accordingly.

[0071] In some embodiments, the visual representation includes a glucose trend graph where the area between the trend graph and the high glucose threshold is a first color and the area between the trend graph and the low threshold is a second color.

[0072] In some aspects of the system, the processing module is configured to generate the graphical display by forming one or more datasets including at least some of the insulin data, glucose data, and event data, flagging or embedding additional information into at least some of the one or more datasets to generate a self-referencing dataset, and generating a graphical display in the array graphically modified to indicate one or more features in the data.

[0073] One embodiment includes a computer-implemented method including obtaining receptor glucose data by a glucose monitoring device, transmitting the receptor glucose data by a wireless transmitter, receiving receptor insulin data, receptor glucose data, and receptor event data, generating a graphical display on a mobile computing device, the graphical display including a display of one or more of the insulin data, glucose data, or event data, and modifying the graphical display to display a visual representation indicating one or more relationships of the insulin data, glucose data, or event data to each other or with time, wherein the visual representation is shaped and configured or scaled so as not to obscure the display of the insulin data, glucose data, or event data, and wherein the visual representation is displayed overall within the display of the insulin data, glucose data, or event data.

[0074] In some embodiments, the event data includes one or more of insulin dosing, carbohydrate intake, or exercise.

[0075] In one aspect, the insulin data includes a value for remaining insulin and the visual representation includes a colored ring indicating remaining insulin and an estimated time remaining for remaining insulin.

[0076] In some aspects, the visual representation includes a trend graph of the glucose data and an interactive callout window associated with an area or feature of the trend graph that is presented when a user selects an area or feature of the trend graph on the graphical display, the presented callout window including at least some of the insulin data and / or the event data.

[0077] In another embodiment, the presented callout window includes a graphical array of insulin data including one or more of bolus or basal insulin, administration time of bolus insulin, administration time of basal insulin, or remaining insulin value.

[0078] In one embodiment, the presented callout window includes a graphical arrangement of event data including one or more of carbohydrate intake, amount of time spent exercising, amount of calories burned, or heart rate reaching a threshold or time associated therewith.

[0079] In some aspects, the visual representation includes an arrow corresponding to the insulin data and a glucose reading including a glucose trend corresponding to the glucose data, the arrow being displayed adjacent to the trend graph and modified to show the effect of the insulin data on the glucose data.

[0080] In one aspect, the visual representation includes a trend graph of historical glucose data and future glucose data, where the future glucose data is determined based on the insulin data and the performance data of the receptor.

[0081] In another aspect, the visual representation includes a first graphical display illustrating 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, where the second graphical display may interact with the first graphical display to illustrate a potential impact of the amount of insulin on the indication of the future trend of the glucose data.

[0082] In some embodiments, the method further includes generating one or more data sets each based on the receptor behavior and predicting the glucose data trend based on the receptor behavior, and the visual representation includes a scrollable list including one or more modified graphs each based on the one or more data sets.

[0083] In other aspects, the method further includes comparing the current glucose value to a high glucose threshold and a low glucose threshold and generating a glucose score, comparing the current remaining insulin to a high insulin threshold and a low insulin threshold and generating an IOB score, generating an insulin status by multiplying the glucose score and the IOB score, and ranking the insulin score into one of a plurality of categories.

[0084] In one aspect, the plurality of categories includes good, caution, and bad.

[0085] In another aspect, the visual representation includes a color-coded display, where each of a plurality of categories is associated with a different color, and the colors associated with the ranked insulin scores are illustrated.

[0086] In one aspect, generating the insulin status further comprises multiplying the trend value.

[0087] In another embodiment, generating the insulin status further comprises multiplying one or more scores based on location, food intake, and exercise.

[0088] In another aspect, the visual representation includes a numerical display of the current glucose value and a graphic representing a prediction of the future trend of the glucose value.

[0089] In one aspect, the method further includes receiving receptor input data associated with future event data, and the visual representation includes a glucose trend graph, and upon modifying the input data, the visual representation is modified accordingly.

[0090] In one embodiment, the visual representation includes a glucose trend graph where the area between the trend graph and the high glucose threshold is a first color and the area between the trend graph and the low threshold is a second color.

[0091] In some aspects of the method, generating the graphical display includes forming one or more data sets including at least some of the insulin data, glucose data, and event data, flagging or embedding additional information into at least some of the one or more data sets to generate a self-referencing dataset, and generating a graphical display within the array graphically modified to indicate one or more features in the data.

[0092] In one aspect, the processing module is further configured to receive the diabetes-related data of the recipient and generate an interactive graphical display on the mobile computing device, where a viewer can interact with the interactive graphical display.

[0093] In one aspect, the interactive graphical display includes a trend graph of glucose data with an area between the trend graph and a glucose threshold value with different colors for areas exceeding a high threshold and areas exceeding a low threshold, the high and low thresholds being adjustable by a viewer's interaction with the interactive graphical display.

[0094] In another aspect, a viewer can interact with an interactive graphical display through a collapsible design layout.

[0095] In some embodiments, the interactive graphical display further includes one or more animations to convey information.

[0096] In another aspect, a viewer can interact with the interactive graphical display by selecting a personalized background image.

[0097] In some embodiments, the viewer can interact with the interactive graphical display by inputting numerical values ​​via a graphical scroll wheel.

[0098] In one aspect, the method includes receiving diabetes-related data of a recipient and generating an interactive graphical display on a mobile computing device, wherein a viewer can interact with the interactive graphical display.

[0099] In one aspect, the interactive graphical display includes a trend graph of glucose data with an area between the trend graph and a glucose threshold value with different colors for areas exceeding a high threshold and areas exceeding a low threshold, the high and low thresholds being adjustable by a viewer's interaction with the interactive graphical display.

[0100] In another aspect, a viewer can interact with an interactive graphical display through a collapsible design layout.

[0101] In some embodiments, the interactive graphical display further includes one or more animations to convey information.

[0102] In one aspect, a viewer can interact with the interactive graphical display by selecting a personalized background image.

[0103] In one embodiment, the viewer can interact with the interactive graphic display by inputting numerical values ​​via a graphical scroll wheel.

[0104] In one aspect of the system, the graphical display further includes an indication of the receptor at which the analyte measurement is taken.

[0105] One embodiment includes a system including a continuous analyte sensor configured to obtain an analyte measurement of a receptor, a wireless transmitter configured to receive the analyte measurement from the continuous analyte sensor, and an analyte data processing module operable on a mobile computing device in wireless communication with the wireless transmitter, where the analyte data processing module is configured to receive at least a portion of the analyte measurement, generate a self-referencing data set based in part on the analyte measurement, generate one or more graphical displays based on the self-referencing data set, modify the self-referencing data set, and display the one or more modified graphical displays based on the modified self-referencing data set.

[0106] In one aspect, the analyte data processing module is further configured to generate high and low thresholds for analyte concentrations at the receptor based in part on one or more of health data obtained from the receptor, statistical analysis of the analyte measurements, contextual data associated with the analyte measurements, health data derived from the receptor profile, or health data obtained from one or more health data databases; determine a time for the analyte measurement of the receptor to reach the high or low threshold; modify one or more of the high or low thresholds when the time is equal to or less than a predetermined safe time; and regenerate the self-referencing data set and display an animation illustrating the change in threshold.

[0107] In one aspect, the modified graphical display includes a graphic of the analyte measurement value versus time, and the animation includes moving a flashing threshold line from a first value of the receptor to the current analyte value.

[0108] In one aspect, one or more of the desired graphical displays includes a line graph of the analyte measurements versus time, and the analyte data processing module is further configured to determine one or more expected ranges for the analyte values ​​and modify the self-referencing data set to display the analyte measurements based on the expected ranges of analyte values.

[0109] In certain embodiments, the expected range of the analyte value is based on one or more of input from a receptor, contextual data associated with the analyte measurement, or health data from a medical institution or authority.

[0110] In some embodiments, the self-referencing data set is modified to use color, line style, animation, shading, gradient, or other visual differentiators to display analyte measurements relative to expected ranges.

[0111] In one aspect, the expected range of analyte values ​​includes a target range, a caution range, and an outside target range.

[0112] In another aspect, the self-referencing data set is modified to subtract analyte values ​​within the target range and display only analyte values ​​outside the caution and target ranges.

[0113] In some embodiments, the expected range of analyte values ​​is revised based on event data obtained from the receptor.

[0114] In some embodiments, one or more of the modified graphical displays include a numeric display of the current value of the analyte measurement, an indication of a forecast of the future trend of the analyte measurement, a text phrase indicating the current status and future forecast of the analyte measurement, a graph of the analyte measurement versus time, one or more lines indicating high and low thresholds for analyte concentration in the receptor, and a graphical representation of the analyte on the graph indicating the current value of the analyte measurement.

[0115] In one aspect, the self-referencing dataset is dynamically modified based on the analyte measurement value, and the self-referencing dataset is further modified to indicate the current analyte measurement value reaching or exceeding a threshold analyte concentration value in the receptor, and an indication of a prediction of the future trend of the analyte measurement value, a threshold line associated with the threshold being reached or exceeded, and a graphical representation of the current analyte value against the analyte graph change style and vibrate in unison.

[0116] In another embodiment, the analyte data processing module is further configured to generate one or more auditory alarms when an analyte threshold value is reached or exceeded.

[0117] In one embodiment, the self-referencing data set is modified to display one or more system status messages.

[0118] In another aspect, the self-referencing data set is modified to display a dark background.

[0119] Further aspects of the present disclosure will be more readily understood by considering the following detailed description of the various disclosed embodiments in conjunction with the accompanying drawings. [Brief description of the drawings]

[0120] [Figure 1A] 1 illustrates aspects of an example system that may be used in connection with implementing embodiments of the present disclosure. [Figure 1B] 1 illustrates aspects of an example system that may be used in connection with implementing embodiments of the present disclosure. [Figure 2A] FIG. 1 is a perspective view of an exemplary housing that may be used in connection with implementing embodiments of the analyte sensor system. [Figure 2B] FIG. 1 is a side view of an exemplary housing that may be used in connection with implementing embodiments of the analyte sensor system. [Figure 3A] 1 illustrates aspects of an example system that may be used in connection with implementing embodiments of the present disclosure. [Figure 3B] 1 illustrates aspects of an example system that may be used in connection with implementing embodiments of the present disclosure. [Figure 4A] 1 is an illustration of a modified graphical display in which analyte concentration values ​​are arranged and presented over multiple time intervals. [Figure 4B] 4B is a modified graphical representation constructed from an aerial view of the graphic of FIG. 4A. [Diagram 5]1 is an illustration of an exemplary graphical display in which analyte concentration values ​​are arranged and presented over multiple time intervals in a ring-shaped graph. [Figure 6] 1 illustrates a modified graphical display corresponding to a data structure and array of analyte concentration values ​​over a time interval. [Figure 7] 1 is an illustration of a modified graphical display generated by a data structure and arrangement of analyte data over multiple time intervals. [Figure 8] 1 is an illustration of a modified graphical display generated by a data structure and arrangement of analyte data over multiple time intervals. [Figure 9] 1 is an illustration of a modified graphical display generated by a data structure and arrangement of analyte data over multiple time intervals. [Figure 10] 10 is an illustration of the modified graphical display of FIG. 9. [Figure 11] FIG. 11 is a modified graphical display of FIG. 10 providing daily analysis results of analyte values. [Figure 12] 1 is an illustration of an exemplary graphical display in which analyte concentration values ​​are shown on a clock dial graphic. [Figure 13A] 5 illustrates a flow chart of an exemplary method by which the disclosed system can generate and display a modified graphical display. [Figure 13B] 13B illustrates a flowchart of an exemplary method for implementing the process identified in the process of FIG. 13A. [Figure 13C] 13B illustrates a flowchart of an exemplary method for implementing the process identified in the process of FIG. 13A. [Figure 13D] 13B illustrates a flowchart of an exemplary method for implementing the process identified in the process of FIG. 13A. [Figure 14] 1 is an illustration of a data structure and a modified graphical display generated from an array of insulin data. [Figure 15]1 illustrates a modified graphical display that includes visual representations showing one or more relationships of insulin data, analyte data, and event data to one another and / or to or associated with time periods. [Figure 16] 1 illustrates a modified graphical display that includes visual representations showing one or more relationships of insulin data, analyte data, and event data to one another and / or to or associated with time periods. [Figure 17] Illustrated are the insulin key charts of Figures 15 and 16. [Figure 18] 1 illustrates a modified graphical display of a trend graph of specimen data. [Figure 19A] 1 illustrates a graphical display that is modified based on historical analyte values, current analyte values, and predicted analyte values. [Figure 19B] 1 illustrates a graphical display that is modified based on historical analyte values, current analyte values, and predicted analyte values. [Figure 20] 1 illustrates a modified graphical display in which the effect of insulin dose on analyte data is shown. [Figure 21] 13 illustrates a modified graphical display in which a scrollable list of user performance data and future analyte value trends are illustrated. [Figure 22] 13 illustrates a modified graphical display illustrating relationships between multiple variables associated with analyte data trends and user actions. [Figure 23] 1 illustrates a glucose trend graph in which deviations beyond high and low thresholds are distinguished visually. [Figure 24A] 1 illustrates a modified graphic display in which a scalable design layout is utilized. [Figure 24B] 1 illustrates a display screen that presents modifiable graphics based on a user interacting with the display screen. [Figure 24C] 1 illustrates a display screen that presents modifiable graphics based on a user interacting with the display screen. [Diagram 25]1 illustrates a modified graphical display that can use animation to communicate health-related information. [Figure 26] 1 illustrates a modified graphical display that allows a user to customize a background image. [Figure 27] 1 illustrates a modified graphical display that allows a user to enter numerical data using a scroll wheel. [Figure 28] 1 illustrates an exemplary modified display in which a user's identifier is incorporated within the modified display. [Figure 29] 1 illustrates a display that communicates analyte threshold changes via animation. [Diagram 30] 1 illustrates an analyte graph illustrating an analyte measurement value relative to an expected range of analyte values. [Diagram 31] Illustrated are exemplary modified graphic displays that convey information about the concentration of an analyte value in a receptor, thresholds, associated analyte graphs, and / or status and reports of an analyte monitoring system. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0121] The figures are described in more detail in the following description and examples and are provided for illustrative purposes only, merely illustrating typical or exemplary embodiments of the present disclosure. The figures are not intended to be exhaustive or to limit the disclosure to the precise form disclosed. It should also be understood that the present disclosure may be practiced with modification or alteration, and that the present disclosure may be limited only by the claims and their equivalents.

[0122] Embodiments of the present disclosure are directed to systems, methods, and devices for generating dynamic data structures and graphical displays. In various arrangements described herein, the analyte data is glucose data generated by an analyte sensor system configured to interface with a display device or the like. As described in detail herein, aspects of the present disclosure may be implemented to modify the graphical display of the analyte data in a manner that conveniently and efficiently indicates patterns in the analyte data. Additionally, aspects of the present disclosure may be implemented to conveniently indicate one or more relationships between glucose data, insulin data, and user actions. In particular, such aspects of the present disclosure relate to, for example, generating a self-referential data structure and modifying a graphical display based on the data structure to communicate information related to diabetes management.

[0123] Details of some exemplary embodiments of the disclosed systems, methods, and devices are described in this description and, possibly, elsewhere in this disclosure. Other features, objects, and advantages of the present disclosure will be apparent to one of ordinary skill in the art upon review of the disclosure, description, figures, examples, and claims. All such additional systems, methods, devices, features, and advantages are intended to be included (either explicitly or by reference) within this description, be within the scope of this disclosure, and be protected by one or more of the accompanying claims.

[0124] overview In some embodiments, a system for continuous measurement of an analyte in a receptor is provided. The system may include a continuous analyte sensor configured to continuously measure a concentration of an analyte in a receptor, 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 data stream associated with the analyte concentration measured by the continuous analyte sensor to generate sensor information including, for example, raw sensor data, converted sensor data, and / or any other sensor data. The sensor electronics module may be further configured to generate sensor information customized for each display device such that different display devices may receive different sensor information.

[0125] As used herein, the term "analyte" is a broad term and should be given its ordinary and customary meaning to those of skill in the art (and is not limited to any special or customized meaning), and further refers to, without limitation, a substance or chemical constituent in a biological fluid (e.g., blood, interstitial fluid, cerebrospinal fluid, lymphatic fluid, urine, sweat, saliva, etc.) that can be analyzed. Analytes can include naturally occurring substances, man-made substances, metabolic products, and / or reaction products. In some implementations, the analyte for measurement by a method or device is glucose. However, the following may be used without limitation: acarboxyprothrombin; acetoacetate; acetone; acetyl-CoA; acylcarnitine; adenine phosphoribosyltransferase; adenosine deaminase; albumin; α-fetoprotein; amino acid profile (arginine (Krebs cycle), histidine / urocanic acid, homocysteine, phenylalanine / tyrosine, tryptophan); andrenostenenedione; antipyrine; arabinitol enantiomers; arginase; benzoylecgonine (cocaine); biotinidase; biopterin; c-reactive protein; carnitine; carnosinase; CD4; ceruloplasmin; chenodeoxycholic acid; chloroquine; cholesterol; cholinesterase; β-conjugated 1-hydroxycholic acid; cortisol; creatine kinase; creatine kinase MM isoform zyme;cyclosporine A;d-penicillamine;d-ethylchloroquine;dehydroepiandrosterone sulfate;DNA (acetyltransferase polymorphism, alcohol dehydrogenase, alpha1-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, Leber hereditary optic neuropathy, MCAD, RNA, PKU, Plasmodium vivax, gonadal differentiation, 21-deoxycortisol);desbutylhalofantrine;dihydropteridine reductase;diphtheria / tetanus antitoxin;erythrocyte arginase;erythrocyte protoporphyrin;esterase D;fatty acids / acylglycines;Triglycerides;Glycerol;Free β-human chorionic gonadotropin;Free erythrocyte porphyrin;Free thyroxine (FT4);Free triiodothyronine (FT3);Fumarylacetoacetate;Galactose / gal-1-phosphate;Galactose-1-phosphate uridyltransferase;Gentamicin;Glucose-6-phosphate dehydrogenase;Glutathione;Glutathione peroxidase;Glycocholate;Glycosylated hemoglobin;Halofantrine;Hemoglobin variants;Hexosaminidase A;Human erythrocyte carbonic anhydrase I;17 -α-hydroxyprogesterone;hypoxanthine phosphoribosyltransferase;immunoreactive trypsin;ketone bodies;lactate;lead;lipoproteins ((a), B / A-1, β);lysozyme;mefloquine;netilmicin;phenobarbitone;phenytoin;phytanic acid / pristanic acid;progesterone;prolactin;prolidase;purine nucleoside phosphorylase;quinine;reverse triiodothyronine (rT3);selenium;serum pancreatic lipase;sisomicin;somatomedin C;specific antibodies (adenovirus, antinuclear antibodies, antizeta antibodies, alveolar Breast cancer virus, Aujeszky's disease virus, Dracaena worm, Echinococcus granulosus, Entamoeba histolytica, Enterovirus, Giardia lamblia, Helicobacter pylori, Hepatitis B virus, Herpes virus, HIV-1, IgE (atopic disease), Influenza virus, Isoprene (2-methyl-1,3-butadiene), Leishmania donovani, Leptospira, Measles / Mumps / Rubella, Mycobacterium leprae, Mycoplasma pneumoniae, Myoglobin, Onchocerca volvulus, Parainfluenza virus, Plasmodium falciparum, Poliovirus, Pseudomonas aeruginosa, Respiratory syncytial virus, Rickettsia (Skull) typhus), Schistosoma mansoni, Toxoplasma gondii, Treponema pallidum, Trypanosoma cruzi / Langer, vesicular stomatitis virus, Bancroftian filariasis, Flaviviruses (e.g., deer tick, dengue, Powassan, West Nile, yellow fever, or Zika virus); specific antigens (hepatitis B virus, HIV-1), succinylacetone, sulfadoxine, theophylline, thyrotropin (TSH), thyroxine (T4), thyroxine-binding globulin, trace elements, transferrin; UDP-galactose-4-epimerase; urea;Other analytes are contemplated as well, including uroporphyrinogen I synthase; vitamin A; white blood cells; and zinc protoporphyrin. Salts, sugars, proteins, fats, vitamins, and hormones naturally occurring in blood or interstitial fluids can also constitute analytes in certain implementations. Analytes can be naturally occurring in biological fluids, such as metabolites, hormones, antigens, antibodies, and the like. Alternatively, analytes can be endogenous or exogenous, such as imaging contrast agents, radioisotopes, chemical agents, fluorocarbon-based synthetic blood, or other substances, including, but not limited to, insulin; glucagon, ethanol; cannabis (marijuana, tetrahydrocannabinol, hashish); inhalants (nitrous oxide, amyl nitrite, butyl nitrite, chlorohydrocarbons, hydrocarbons); cocaine (crack cocaine); stimulants (amphetamine, methamphetamine, ritalin, silate, preludin, direx, prestate, borane, sandrex, pregeen); depressants (barbiturates, methaqualone, barbiturates, methacrylamide ... Analytes that can be introduced into drugs or pharmaceutical compositions include tranquilizers such as sedatives, ... Analytes such as neurochemicals and other chemicals produced in the body, such as ascorbic acid, uric acid, dopamine, noradrenaline, 3-methoxytyramine (3MT), 3,4-dihydroxyphenylacetic acid (DOPAC), homovanillic acid (HVA), 5-hydroxytryptamine (5HT), and 5-hydroxyindoleacetic acid (FHIAA), as well as intermediates in the citric acid cycle, can also be analyzed;

[0126] Alerts In certain embodiments, one or more alerts are associated with the sensor electronics module. For example, each alert may include one or more alert conditions indicating when the respective alert was triggered. For example, a hypoglycemia alert may include an alert condition indicating a minimum blood glucose value. The alert conditions may also be based on trend data and / or transformed sensor data, such as sensor data from multiple different sensors (e.g., the alert may be based on sensor data from both a glucose sensor and a temperature sensor). For example, a hypoglycemia alert may include an alert condition indicating a minimum demand trend in the recipient's blood glucose value that must exist before triggering the alert. As used herein, the term "trend" generally refers to data that indicates some attribute of data acquired over time, such as, for example, calibrated or filtered data from a continuous glucose sensor. Trends may indicate the amplitude, rate of change, acceleration, direction, etc. of data, such as sensor data, including transformed or raw sensor data.

[0127] In certain embodiments, each alert is associated with one or more actions to be performed in response to triggering the alert. An alarm action may include activating an alarm, such as, for example, displaying information on a display of the sensor electronics module or activating an audio or vibration alarm coupled to the sensor electronics module, and / or transmitting data to one or more external display devices external to the sensor electronics module. For any distribution action associated with a triggered alert, one or more distribution options define the content and / or format of the data to be transmitted, the device to which the data should be transmitted, when the data should be transmitted, and / or a communication protocol for the distribution of the data.

[0128] In certain embodiments, multiple distribution actions (e.g., having respective distribution options) may be associated with a single alert, such that displayable sensor information having different content and formatting is sent to respective display devices, e.g., in response to triggering of a single alert. For example, a mobile phone may receive a data package including minimal displayable sensor information (which may be specifically formatted for display on a mobile phone), while a desktop computer may receive a data package including most (or all) of the displayable sensor information generated by the sensor electronics module in response to triggering of a common alert. Beneficially, the sensor electronics module is not coupled to a single display device, but rather is configured to communicate with multiple different display devices directly, systematically, simultaneously (e.g., via broadcast), periodically, periodically, randomly, on demand, in response to an inquiry, based on an alert or alarm, and / or the like.

[0129] In some embodiments, a clinical risk alert is provided that includes an alert condition that combines intelligent and dynamic estimation algorithms to estimate current or predicted danger with greater accuracy, faster timing of pending danger, 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 risks, statistical probabilities, known physiological constraints, and / or individual physiological patterns, thereby providing appropriate, clinically safe, and patient-friendly alarms. U.S. Patent Publication No. 2007 / 0208246, incorporated herein by reference in its entirety, describes several 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 respond to his / her condition. Additionally, the clinical risk alert can be deactivated upon leaving the clinical risk area to avoid annoying the patient with repetitive clinical alarms (e.g., visual, auditory, or vibration) when the patient's condition is improving. In some embodiments, the dynamic and intelligent estimation determines the likelihood that the patient will avoid clinical risk based on the analyte concentration, rate of change, and other aspects of the dynamic and intelligent estimation algorithm. If there is minimal or no likelihood of avoiding clinical risk, a clinical risk alert will be triggered. However, if there is a likelihood of avoiding clinical risk, the system is configured to wait a predetermined amount of time and reanalyze the likelihood of avoiding clinical risk. In some embodiments, if there is a likelihood of avoiding clinical risk, the system is further configured to provide targets, treatment recommendations, or other information that can help the patient proactively avoid the clinical risk.

[0130] In some embodiments, the sensor electronics module is configured to search for one or more display devices within communication range of the sensor electronics module and to wirelessly communicate sensor information (e.g., a data package including the displayable sensor information, one or more alarm conditions, and / or other alarm information). Thus, the display device is configured to display at least some of the sensor information and / or alarm a recipient (and / or caregiver), and the alarm mechanism is located on the display device.

[0131] 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 package indicating that an alarm should be initiated (e.g., sequentially and / or simultaneously) by one or more display devices. In certain embodiments, the sensor electronics module simply provides a data field indicating that an alarm condition exists, and the display device may determine to trigger an alarm upon reading the data field indicating the existence of an alarm condition. In some embodiments, the sensor electronics module determines which of the one or more alarms to trigger based on the one or more alerts that are triggered. For example, if the alert trigger indicates severe hypoglycemia, the sensor electronics module may perform multiple actions, such as activating an alarm on the sensor electronics module, sending a data package to the monitoring device indicating activation of the alarm on the display, and sending the data package as a text message to the care provider. As an example, the text message may appear on a custom monitoring device, cell phone, pager device, and / or the like, including displayable sensor information indicating the recipient's condition (e.g., "severe hypoglycemia").

[0132] In some embodiments, the sensor electronics module is configured to wait a period of time for the receptor to respond to the triggered alert (e.g., by pressing or selecting a snooze and / or off 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 the alarm condition (e.g., hypoglycemia), such as an insulin pump, where the stop alert triggers the cessation of insulin delivery via the pump.

[0133] In some embodiments, the sensor electronics module is configured to transmit alarm information directly, systematically, simultaneously (e.g., via broadcast), periodically, periodically, randomly, on demand, in response to a query (from the display device), based on an alert or alarm, and / or the like. In some embodiments, the system further includes a repeater that can increase the wireless communication range of the sensor electronics module, for example, to 10, 20, 30, 50, 75, 100, 150, or 200 meters or more, the repeater configured to repeat wireless communication from the sensor electronics module to a display device located remotely from the sensor electronics module. The repeater can be useful for families with diabetic children, for example, allowing the parent to carry or place the display device in a stationary location, such as in a large house where the parent sleeps at a distance from the child.

[0134] Display Device In some embodiments, the sensor electronics module is configured to search and / or attempt wireless communication with a display device from a list of display devices. In some embodiments, the sensor electronics module is configured to search and / or attempt wireless communication with a list of display devices, for example, in a predetermined and / or programmable order (e.g., grading and / or escalation), where a failed attempt to communicate and / or alarm with a first display device triggers an attempt to communicate and / or alarm with a second display device, etc. In one exemplary embodiment, the sensor electronics module is configured to search for and attempt to alarm a recipient or caregiver sequentially using a list of display devices, such as: (1) a default display device or a custom analyte monitoring device, (2) a cell phone via audio and / or visual representation methods such as a text message to the recipient and / or caregiver, a voice message to the recipient and / or caregiver, and / or 911), (3) a tablet, (4) a smart watch or bracelet, and / or (5) smart glasses or other wearable display device.

[0135] In some embodiments, the one or more display devices that receive the data package from the sensor electronics module are "dummy displays" and display the displayable sensor information received from the sensor electronics module without additional processing (e.g., processing of future algorithms necessary for real-time display of the sensor information). In some embodiments, the displayable sensor information includes transformed sensor data that does not require processing by the display device prior to display of the displayable sensor information. Some display devices may include software including display instructions configured to enable display of the displayable sensor information (software programming including instructions configured to display the displayable sensor information and, optionally, query the sensor electronics module to obtain the displayable sensor information). In some embodiments, the display device may be programmed with the manufacturer's display instructions and may include security and / or authentication to avoid theft of the display device. In some embodiments, the display device is configured to display the displayable sensor information via a downloadable program (e.g., Java Script downloadable via the Internet), so any display device that supports program downloads (e.g., any display device that supports Java applets) may be configured to display the displayable sensor information (e.g., cell phone, tablet, PDA, PC, etc.).

[0136] In some embodiments, a particular display device may wirelessly communicate directly with the sensor electronics module, although intermediate network hardware, firmware, and / or software may be included in the direct wireless communication. In some embodiments, a repeater (e.g., a Bluetooth® repeater) may be used to retransmit the transmitted displayable sensor information to locations further away than the immediate range of the telemetry module of the sensor electronics module, the repeater enabling direct wireless communication when no substantial processing of the displayable sensor information occurs. In some embodiments, a receiver (e.g., a Bluetooth® receiver) may be used to retransmit the transmitted displayable sensor information, possibly in a different format such as a text message on a TV screen, the receiver enabling direct wireless communication when no substantial processing of the sensor information occurs. In some 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 device without intermediate processing of the displayable sensor information.

[0137] In certain embodiments, one or more display devices include a built-in authentication mechanism whereby authentication is required for communication between the sensor electronics module and the display device. In some embodiments, a challenge-response protocol, such as password authentication, is provided to authenticate data communication between the sensor electronics module and the display device, 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 with the display device can be accomplished by a user and / or manufacturer via the password. This may sometimes be referred to as two-way authentication.

[0138] In some embodiments, one or more display devices are configured to query the sensor electronics module for displayable sensor information, and the display device acts as a master device that requests sensor information from the sensor electronics module (e.g., a slave device) on demand, e.g., in response to a query. In some embodiments, the sensor electronics module is configured to periodically, systematically, periodically, and / or periodically (e.g., every 1, 2, 5, or 10 minutes or more) transmit sensor information to one or more display devices. In some embodiments, the sensor electronics module is configured to transmit data packages associated with triggered alerts (e.g., triggered by one or more alert conditions). However, any combination of the data transmission conditions described above can be implemented with any combination of paired sensor electronics modules and display device(s). For example, one or more display devices can be configured to query the sensor electronics module database and receive alarm information triggered by one or more alarm conditions being met. Additionally, the sensor electronics module can be configured to periodically transmit the sensor information to one or more display devices (the same or different display devices as described in the previous example), and the system may include display devices that function differently with respect to how the sensor information is obtained.

[0139] In some embodiments, the display device is configured to query a data storage memory in the sensor electronics module for certain types of data content, including directly querying a database in the memory of the sensor electronics module and / or requesting a configured or configurable package of data content therefrom, i.e., data stored in the sensor electronics module is configurable, searchable, pre-determined, and / or pre-packaged based on the display device with which the sensor electronics module is in communication. In some further or alternative embodiments, the sensor electronics module generates displayable sensor information based on its knowledge of which display device should receive a particular transmission. Additionally, some display devices are capable of obtaining calibration information and automatically inputting calibration information, automatically delivering calibration information, and / or wirelessly transmitting calibration information to the sensor electronics module, such as through an integrated reference analyte monitor incorporated in the display device. U.S. Patent Publication Nos. 2006 / 0222566, 2007 / 0203966, 2007 / 0208245, and 2005 / 0154271, all of which are incorporated herein by reference in their entireties, describe systems and methods for providing an integrated reference analyte monitor integrated into a display device and / or other calibration methods that can be implemented using the embodiments disclosed herein.

[0140] In general, a number of display devices (e.g., custom analyte monitoring devices (which may also be referred to as analyte display devices), mobile phones, tablets, smart watches, reference analyte monitors, medication delivery devices, medical devices, and personal computers) can be configured to wirelessly communicate with the sensor electronics module. The number 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 converted sensor data, such as analyte concentration values, rate of change information, trend information, alert information, sensor diagnostic information, and / or calibration information.

[0141] Analyte Sensors With reference to FIG. 1A, in some embodiments, the analyte sensor 10 comprises a continuous analyte sensor, e.g., a subcutaneous, transcutaneous (e.g., transdermal), or intravascular device. In some embodiments, such a sensor or device can analyze multiple intermittent blood samples. Although the present disclosure includes glucose sensor embodiments, such embodiments may be used for other analytes as well. Glucose sensors may use any method of glucose measurement, including enzymatic, chemical, physical, electrochemical, spectrophotometric, polarimetric, calorimetric, iontophoretic, radiometric, immunochemical, etc.

[0142] The glucose sensor can provide a data stream indicative of the glucose concentration in the recipient using any known method, including invasive, minimally invasive, and non-invasive sensing techniques (e.g., fluorescence monitoring). The data stream is typically a raw data signal that is converted into a calibrated and / or filtered data stream that is used to provide a useful glucose value to a user, such as a patient or caregiver (e.g., a parent, relative, guardian, teacher, doctor, nurse, or other individual interested in the recipient's welfare).

[0143] The glucose sensor may be any device capable of measuring the concentration of glucose. According to one exemplary embodiment described below, an implantable glucose sensor may be used. However, it should be understood that the devices and methods described herein may be applied to any device capable of detecting the concentration of glucose and providing an output signal representative of the concentration of glucose (e.g., in the form of analyte data).

[0144] In a particular embodiment, the analyte sensor 10 is an implantable glucose sensor such as described with reference to U.S. Patent No. 6,001,067 and U.S. Patent Publication No. US-2005-0027463-A1. In an embodiment, the analyte sensor 10 is a transcutaneous glucose sensor such as described with reference to U.S. Patent Publication No. US-2006-0020187-A1. In an embodiment, the analyte sensor 10 is configured to be implanted within a recipient tract or externally, as described in U.S. Patent Publication No. US-2007-0027385-A1, filed October 4, 2006, co-pending U.S. Patent Publication No. US-2008-0119703-A1, filed March 26, 2007, and U.S. Patent Application No. US-2007-0197890-A1, filed February 14, 2007. In an embodiment, the continuous glucose sensor includes a transcutaneous sensor, for example, as described in U.S. Patent No. 6,565,509 to Say et al. In an embodiment, the analyte sensor 10 is a continuous glucose sensor including a subcutaneous sensor such as described with reference to U.S. Patent No. 6,579,690 to Bonnecaze et al. or U.S. Patent No. 6,484,046 to Say et al. In an embodiment, the continuous glucose sensor includes a refillable subcutaneous sensor such as described with reference to U.S. Patent No. 6,512,939 to Colvin et al. The continuous glucose sensor may include an intravascular sensor such as described with reference to U.S. Patent No. 6,477,395 to Schulman et al. The continuous glucose sensor may include an intravascular sensor such as described with reference to U.S. Patent No. 6,424,847 to Mastrototaro et al.

[0145] 2A and 2B are perspective and side views of a housing 200 that may be used in connection with implementing an embodiment of an analyte sensor system 8 according to certain aspects of the present disclosure. The housing 200, in certain embodiments, 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 therewithin. In some embodiments, the mounting unit 214, also referred to as a housing or sensor pod, includes a base 234 adapted to be secured to a recipient or user's skin. The base 234 may be formed from a variety of rigid or flexible materials and may include a low profile to minimize protrusion of the device from the recipient during use. In some embodiments, the base 234 is at least partially formed from a flexible material, which may provide numerous advantages over other transcutaneous sensors that may unfortunately suffer from motion-related artifacts associated with movement of the recipient as the recipient uses the device. The mounting unit 214 and / or the sensor electronics module 12 may be positioned over the sensor insertion site to protect the site and / or provide a minimal footprint (utilization of receptor skin surface area).

[0146] In some embodiments, a removable connection between the mounting unit 214 and the sensor electronics module 12 is provided, which allows for improved productivity, i.e., the potentially less expensive mounting unit 214 can be disposed of when retrofitting or maintaining the analyte sensor system 8, and the more expensive sensor electronics module 12 can be reused with multiple sensor systems. In some embodiments, the sensor electronics module 12 is configured with signal processing (programming) configured to, for example, filter, calibrate, and / or perform other algorithms useful for calibrating and / or displaying sensor information. However, an integrated (non-detachable) sensor electronics module can be configured.

[0147] In some embodiments, the contacts 238 are mounted on or within a subassembly, hereafter referred to as the contact subassembly 236, configured to fit within the base 234 of the mounting unit 214 and a hinge 248 that allows the contact subassembly 236 to pivot between a first position (for insertion) and a second position (for use) relative to the mounting unit 214. As used herein, the term "hinge" is a broad term and is used in its ordinary sense to include and refer to any of a variety of pivoting, articulating, and / or hinge mechanisms, such as, but not limited to, adhesive hinges, sliding joints, etc., and the term hinge does not necessarily imply a fulcrum or fixed point around which articulation occurs. In some embodiments, the contacts 238 are formed from a conductive elastomeric material, such as a carbon black elastomer, through which the sensor 10 extends.

[0148] 2A and 2B, in certain embodiments, the mounting unit 214 includes an adhesive pad 208 disposed on the back surface of the mounting unit and includes a peelable backing layer. Thus, the mounting unit 214 is adhered to the recipient's skin by removing the backing layer and finally pressing at least a portion of the base 234 of the mounting unit 214 against the recipient's skin. Additionally or alternatively, an adhesive pad may be placed over some or all of the analyte sensor system 8 and / or sensor 10 to ensure adhesion and optionally secure an airtight or watertight seal around the wound exit site (or sensor insertion site) (not shown) after sensor insertion is complete. A suitable adhesive pad may be selected and designed to stretch, stretch, conform, and / or vent an area (e.g., the recipient's skin). The embodiments described with reference to FIGS. 2A and 2B are described in more detail with reference to U.S. Pat. No. 7,310,544, which is incorporated herein by reference in its entirety. The configuration and arrangement may provide water-resistant, waterproof, and / or sealing properties associated with the mounting unit / sensor electronics module embodiments described herein.

[0149] Various methods and devices suitable for use in conjunction with aspects of some embodiments are disclosed in U.S. Patent Publication No. US-2009-0240120-A1, which is incorporated by reference in its entirety for all purposes.

[0150] Exemplary Configurations Referring again to FIG. 1A, a system 100 is illustrated that may be used in connection with implementing aspects of an analyte sensor system. In some cases, the system 100 may be used to implement various systems described herein. The system 100 in an embodiment includes an analyte sensor system 8 and display devices 110, 120, 130, and 140 in accordance with certain aspects of the present disclosure. The analyte sensor system 8 in the illustrated embodiment includes a sensor electronics module 12 and a continuous analyte sensor 10 associated with the sensor electronics module 12. The sensor electronics module 12 may wirelessly communicate (e.g., directly or indirectly) with one or more of the display devices 110, 120, 130, and 140. In an embodiment, the system 100 also includes a medical device 136 and a server system 134. The sensor electronics module 12 may also wirelessly communicate (e.g., directly or indirectly) with the medical device 136 and the server system 134. In some examples, the display devices 110 - 140 may also be in wireless communication with the server system 134 and / or the medical device 136 .

[0151] In certain embodiments, the sensor electronics module 12 includes electronic circuitry associated with measuring and processing the continuous analyte sensor data, including future algorithms associated with processing and calibrating the sensor data. The sensor electronics module 12 may be physically connected to the continuous analyte sensor 10 and may be integral (non-releasably attached) or releasably attached to the continuous analyte sensor 10. The sensor electronics module 12 may include hardware, firmware, and / or software that enables the measurement of the level of the analyte via the glucose sensor. For example, the sensor electronics module 12 may include a potentiostat, a power supply for powering the sensor, other components useful for signal processing and data storage, and a telemetry module that transmits data from the sensor electronics module to one or more display devices. The electronics may be affixed to a printed circuit board (PCB) or the like, and may take a variety of forms. For example, the electronics may take the form of integrated circuits (ICs), such as application specific integrated circuits (ASICs), microcontrollers, and / or processors.

[0152] Sensor electronics module 12 may include sensor electronics configured to process sensor information, such as sensor data, and to generate transformed sensor data and displayable sensor information. Examples of systems and methods for processing sensor analyte data are described in more detail herein, and in U.S. Pat. Nos. 7,310,544 and 6,931,327, as well as U.S. Patent Application 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 incorporated by reference in their entirety for all purposes.

[0153] 1A , display devices 110, 120, 130, and / or 140 are configured to display (and / or alarm) displayable sensor information (e.g., in customized data packages sent to the display devices based on their respective preferences) that may be transmitted by sensor electronics module 12. Each of display devices 110, 120, 130, or 140 may include a display, such as touch screen display 112, 122, 132, and / or 142, for displaying sensor information and / or analyte data to a user and / or for receiving input from a user. For example, a graphical user interface may be presented to the user for such purposes. In some embodiments, the display device may include other types of user interfaces, such as a voice user interface, instead of or in addition to a touch screen display, for communicating sensor information to a user of the display device and / or for receiving user input. In some embodiments, one, some, or all of the display devices are configured to display or otherwise communicate the sensor information as it is communicated from the sensor electronics module (e.g., in a data package transmitted to the respective display device) without any additional future processing required for calibration and real-time display of the sensor data.

[0154] The medical device 136 may be a passive device in an exemplary embodiment of the present disclosure. For example, the medical device 136 may be an insulin pump for administering insulin to a user, as shown in FIG. 1B. For various reasons, it may be desirable for such an insulin pump to receive and track glucose values ​​transmitted from the analyte sensor system 8. One reason is to provide the insulin pump with the ability to stop or activate insulin administration when the glucose value falls below a threshold. One solution to allow a passive device (e.g., the medical device 136) to receive analyte data (e.g., glucose values) without being coupled to the analyte sensor system 8 is to include the analyte data in an advertising message transmitted from the analyte sensor system 8. The data included in the advertising message may be encoded such that only a device having an identity associated with the analyte sensor system 8 can decode the analyte data. In some embodiments, the medical device 136 includes a sensor device 136b that is attachable or wearable, for example by a user, in wired or wireless communication with 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 the operation of the sensor device and / or data processing.

[0155] With further reference to FIG. 1A, the display devices may include custom display devices specifically designed to display a particular type of displayable sensor information (e.g., in some embodiments, numbers and arrows) associated with the analyte data received from the sensor electronics module 12. The analyte display device 110 is an example of such a custom device. In some embodiments, one of the display devices is a smart phone, such as a mobile phone 120 based on an Android, iOS or other operating system, and configured to display a graphical representation of continuous sensor data (e.g., including current and historical data). Other display devices may include a tablet 130, a smart watch 140, a medical device 136 (e.g., an insulin delivery device or a blood glucose meter), and / or other handheld devices, such as a desktop or laptop computer.

[0156] Because different display devices provide different user interfaces, the content of the data package (e.g., amount, format, and / or type of data displayed, alarms, etc.) can be customized (e.g., programmed differently by the manufacturer and / or end user). Thus, in the embodiment of FIG. 1A, multiple different display devices can wirelessly communicate directly with the sensor electronics module (e.g., on-skin sensor electronics module 12 physically connected to the continuous analyte sensor 10, etc.) during a sensor session to enable multiple different types and / or levels of display and / or functionality associated with the displayable sensor information, as described in more detail elsewhere herein.

[0157] 1A , the system 100 may also include a wireless access point (WAP) 138 that may be used to interconnect one or more of the analyte sensor system 8, the plurality of display devices, the server system 134, and the medical device 136. For example, the WAP 138 may provide Wi-Fi and / or cellular connectivity within the system 100. Near field communication (NFC) may also be used between the devices of the system 100. The server system 134 may be used to collect analyte data from the analyte sensor system 8 and / or the plurality of display devices, for example, to perform analyses thereon, generate universal or individualized models of blood glucose levels and profiles, etc.

[0158] Referring now to Figure 3A, there is illustrated a system 300 that may be used in connection with implementing embodiments of the disclosed systems, methods, and devices. By way of example, various below-described components of Figure 3A may be used between an analyte sensor system, such as that shown in Figure 1A, and multiple display devices, medical devices, servers, etc., to provide wireless communication of glucose data.

[0159] 3A, the system 300 may include an analyte sensor system 308 and one or more display devices 310. Additionally, in the illustrated embodiment, the system 300 includes a server system 334 including a server 334a which is in turn coupled to a processor 334c and a storage device 334b. The analyte sensor system 308 may be coupled to the display device 310 and / or the server system 334 via a communication medium 305.

[0160] As described in detail herein, the analyte sensor system 308 and the display device 310 may exchange messaging over a communication medium 305, which may also be used to deliver analyte data to the display device 310 and / or the server system 334. As mentioned above, the display device 310 may include various electronic computing devices, such as, for example, a smartphone, a tablet, a laptop, a wearable device, etc. The display device 310 may also include the analyte display device 110 and the medical device 136. It will be noted here that the GUI of the display device 310 may perform the functions of accepting user input and displaying menus, as well as information derived from the analyte data. The GUI may be provided by various operating systems known in the art, such as, for example, iOS, Android, Windows Mobile, Windows, Mac OS, Chrome OS, Linux, Unix, gaming platform OS (e.g., Xbox, PlayStation, Wii), etc. In various embodiments, the communication medium 305 may 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.

[0161] In various embodiments, elements of system 300 may be used to perform various processes described herein and / or perform various operations described herein with respect to one or more of the disclosed systems and methods. Upon review of this disclosure, one of ordinary skill in the art will appreciate that system 300 may include multiple analyte sensor systems, a communication medium 305, and / or a server system 334.

[0162] As discussed above, the communication medium 305 may be used to connect or communicatively couple the analyte sensor system 308, the display device 310, and / or the server system 334 to one another or to a network, and the communication medium 305 may be implemented in various forms. For example, the communication medium 305 may include an Internet connection, such as a local area network (LAN), a wide area network (WAN), an optical fiber network, the Internet over power lines, a wired connection (e.g., a bus), or the like, or any other type of network connection. The communication medium 305 may be implemented using any combination of routers, cables, modems, switches, optical fibers, wires, radio (e.g., microwave / RF links), and the like. Additionally, the communication medium 305 may be implemented using various wireless standards, such as Bluetooth, BLE, Wi-Fi, 3GPP standards (e.g., 2G GSM / GPRS / EDGE, 3G UMTS / CDMA2000, or 4G LTE / LTE-U), etc. After reading this disclosure, one of ordinary skill in the art will recognize other ways to implement the communications medium 305 for communications purposes.

[0163] The server 334a may receive, collect, or monitor information including analyte data and related information from the analyte sensor system 308 and / or display device 310, such as input responsive to analyte data or input received in association with an analyte monitoring application running on the analyte sensor system or display device 310. In such a case, the server 334a may be configured to receive such information via the communication medium 305. This information may be stored in the storage device 334b ​​and / or processed by the processor 334c. For example, the processor 334c may include an analytics engine that may perform analytics on information collected, received, etc. by the server 334a via the communication medium 305. In an embodiment, the server 334a, the storage device 334b, and / or the processor 334c may be implemented as a distributed computing network, such as a Hadoop® network, or as a relational database, etc.

[0164] The server 334a may include, for example, an internet server, a router, a desktop or laptop computer, a smartphone, a tablet, a processor, a module, etc., and may be implemented in a variety of forms including, for example, an integrated circuit or collection thereof, a printed circuit board or collection thereof, or a separate housing / package / rack or multiples thereof. In an embodiment, the server 334a at least partially directs communications that occur over the communication medium 305. Such communications include broadcasting and / or messaging (e.g., advertisements, instructions, or other messaging) and analyte data. For example, the server 334a may process and exchange messages between the analyte sensor system 308 and the display device 310 related to frequency bands, timing of transmissions, security, alarms, etc. The server 334a may update information stored on the analyte sensor system 308 and / or the display device 310, for example, by broadcasting applications thereto. The server 334a may transmit / receive information to / from the analyte sensor system 308 and / or the display device 310 in real-time or sporadically. Additionally, the server 334a may implement cloud computing capabilities for the analyte sensor system 308 and / or the display device 310.

[0165] FIG. 3B illustrates a system 302 including examples of additional aspects of the present disclosure that may be used in connection with implementing an analyte sensor system. As illustrated, the system 302 may include an analyte sensor system 308. As shown, the analyte sensor system 308 may include an analyte sensor 375 (which may also be designated, for example, by the numeral 10 in FIG. 1A ) coupled to a sensor measurement circuit 370 for processing and managing sensor data. The sensor measurement circuit 370 may be coupled to a processor / microprocessor 380 (which may be, for example, part of item 12 in FIG. 1A ). In some embodiments, the processor 380 may perform some or all of the functions of the sensor measurement circuit 370 to obtain and process sensor measurements from the sensor 375. The processor 380 may further be coupled to a wireless unit or transceiver 320 (which may be, for example, part of item 12 in FIG. 1A ) for transmitting sensor data and receiving requests and commands from an external device, such as a display device 310, which may be used to display or otherwise provide the sensor data (or analyte data) to a user. As used herein, the terms "wireless unit" and "transmitter / receiver" are used interchangeably and generally refer to a device capable of wirelessly transmitting and receiving data. The analyte sensor system 308 may further include a storage device 365 (which may be part of, for example, item 12 in FIG. 1A) for storing and tracking sensor data and a real time clock (RTC) 380 (which may be part of, for example, item 12 in FIG. 1A).

[0166] As mentioned above, a wireless communication protocol may be used to transmit and receive data between the analyte sensor system 308 and the display device 310 over the communication medium 305. Such a wireless protocol may be designed for use in a wireless network optimized for periodic, small data transmissions (which may be transmitted at low speeds if necessary) to and from multiple devices (e.g., a personal area network (PAN)) over short distances. For example, one such protocol may be optimized for periodic data transfers where the transceiver may be configured to transmit data at short intervals and then enter a low power mode at longer intervals. This protocol may have low overhead requirements for both normal data transmissions and for initial setup of the communication channel (e.g., by reducing overhead) to reduce power consumption. In some embodiments, a burst broadcast scheme (e.g., one-way communication) may be used. This may eliminate the overhead required for acknowledgement signals and allow for less power-consuming periodic transmissions.

[0167] The protocol may further be configured to establish communication channels with multiple devices while implementing interference avoidance schemes. In some embodiments, the protocol may utilize an adaptive isochronous network topology that defines various time slots and frequency bands for communication with several devices. Thus, the protocol may modify transmission windows and frequencies in response to interference and to support communication with multiple devices. Thus, the wireless protocol may use a scheme based on time and frequency division multiplexing (TDMA). The wireless protocol may also use direct sequence spread spectrum (DSSS) and frequency hopping spread spectrum schemes. Various network topologies may be used to support short-range and / or low-power wireless communications, such as peer-to-peer, start, tree, or mesh network topologies, such as Wi-Fi, Bluetooth, and Bluetooth Low Energy (BLE). The wireless protocol may operate in various frequency bands, such as open ISM bands, such as 2.4 GHz. Furthermore, to reduce power usage, the wireless protocol may adaptively configure data rates depending on power consumption.

[0168] 3B, the system 302 may include a display device 310 communicatively coupled to the analyte sensor system 308 via a communication medium 305. In the illustrated embodiment, the display device 310 includes a connection interface 315 (which in turn includes a transceiver 320), a storage device 325 (which in turn stores the analyte sensor application 330 and / or additional applications), a processor / microprocessor 335, a graphic user interface (GUI) 340 that may be presented using a display 345 of the display device 310, and a real time clock (RTC) 350. A bus (not shown herein) may be used to interconnect the various elements of the display device 310 and to transfer data between these elements.

[0169] The display device 310 may be used to alert and provide sensor information or analyte data to a user and may include a processor / microprocessor 335 for processing and managing sensor data. The display device 310 may include a display 345, a storage device 325, an analyte sensor application 330, and a real-time clock 350 for displaying, storing, and tracking sensor data. The display device 310 may further include a wireless unit or transceiver 320 coupled to other elements of the display device 310 via a connection interface 315 and / or a bus. The transceiver 320 may be used to receive sensor data and send requests, commands, and / or data to the analyte sensor system 308. The transceiver 320 may further use a communication protocol. The storage device 325 may also be used to store an operating system for the display device 310 and / or custom (e.g., proprietary) applications designed for wireless data communication between the transceiver and the display device 310. The storage device 325 may be a single memory device or multiple memory devices and may be volatile or non-volatile memory for storing data and / or instructions for software programs and applications. The instructions may be executed by the processor 335 to control and manage the transceiver 320.

[0170] In some embodiments, where a standardized communication protocol is used, commercially available transceiver circuits may be available that incorporate processing circuitry for handling low level data communication functions such as managing data encoding, transmission frequency, handshaking protocols, etc. In these embodiments, the processor 335, 380 need not manage these activities, but rather provides desired data values ​​for transmission, manages higher level functions such as powering up or down, sets the rate at which messages are transmitted, etc. Instructions and data values ​​for performing these higher level functions may be provided to the transceiver circuitry via a data bus and transfer protocol established by the manufacturer of the transceiver 320, 360.

[0171] Components of the analyte sensor system 308 may need to be replaced periodically. For example, the analyte sensor system 308 may include an implantable sensor 375 that may be attached to a sensor electronics module that includes a sensor measurement circuit 370, a processor 380, a storage device 365, and a transceiver 360, as well as a battery (not shown). The sensor 375 may require periodic replacement (e.g., every 7-30 days). The sensor electronics module may be configured to be powered and function for much longer than the sensor 375 (e.g., 3-6 months or more) before the battery needs to be replaced. Replacing these components may be difficult and requires the assistance of trained personnel. Reducing the need to replace such components, especially the battery, greatly improves the convenience and cost of using the analyte sensor system 308, including for users. In some embodiments, when the sensor electronics module is first used (or is restarted once the battery has been replaced in some cases), it may be connected to the sensor 375 and a sensor session may be established. As described further below, there may be a process to initially establish communication between the display device 310 and the sensor electronics module when the module is first used or rebooted (e.g., when 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 may communicate periodically and / or continuously over the life of several sensors 375, for example, until a battery needs to be replaced. Each time a sensor 375 is replaced, a new sensor session may be established. A new sensor session may be initiated via a process completed using the display device 310, which may be triggered by notification of a new sensor via communication between the sensor electronics module and the display device 310, which may persist for the duration of the sensor session.

[0172] The analyte sensor system 308 typically aggregates analyte data from the sensor 375 and transmits it to the display device 310. Data points regarding the analyte value may be aggregated and transmitted over the life of the sensor 375 (e.g., in the range of 1 day to 30 days or more). New measurements may be transmitted frequently enough to adequately monitor the blood glucose level. Rather than having transmitting and receiving circuitry in each of the analyte sensor system 308 and the display device 310 that cause the analyte sensor system 308 and the display device 310 to be in continuous communication, the analyte sensor system 308 and the display device 310 may periodically and / or periodically establish a communication channel between them. Thus, the analyte sensor system 308 may communicate with the display device 310 (e.g., a handheld computing device, a medical device, or a proprietary device) via wireless transmission, in some cases at predetermined time intervals. The duration of the predetermined time interval may be selected to be long enough so that the analyte sensor system 308 does not consume too much power by transmitting data more frequently than necessary, but frequent enough to provide substantially real-time sensor information (e.g., values ​​or analyte data) for display on the display device 310 and output to a user (e.g., via the display 345). The predetermined time interval is every 5 minutes in some embodiments, although it will be understood that this time interval may be modified to be any desired length of time.

[0173] 3B, the connection interface 315 interfaces the display device 310 to the communication medium 305 such that the display device 310 may be communicatively coupled to the analyte sensor system 308 via the communication medium 305. The transceiver 320 of the connection interface 315 may include multiple transceiver modules capable of operating with different wireless standards. The transceiver 320 may be used to receive analyte data and associated commands and messages from the analyte sensor system 308. Additionally, the connection interface 315 may include additional components for controlling wireless and / or wired connections, such as baseband and / or Ethernet modems, audio / video codecs, etc.

[0174] The storage device 325 may include volatile memory (e.g., RAM) and / or non-volatile memory (e.g., flash storage), and may include any of EPROM, EEPROM, cache, or some combination / variation thereof. In various embodiments, the storage device 325 may store user input data and / or other data collected by the display device 310 (e.g., input from other users aggregated via the analyte sensor application 330). The storage device 325 may also be used to store large amounts of analyte data received from the analyte sensor system 308 for later retrieval and use, for example, to determine trends and trigger alerts. Additionally, the storage device 325 may store the analyte sensor application 330, which when executed using the processor 335, receives input (e.g., via conventional hard / soft keys or touch screen, voice detection, or other input mechanisms) and allows a user to interact with the analyte data and associated content via the GUI 340, as described in more detail herein.

[0175] In various embodiments, a user may interact with the analyte sensor application 330 via a GUI 340, which may be provided by a display 345 of the display device 310. By way of example, the display 345 may be a touch screen display that receives various hand gestures as input. The application 330 may process and / or present analyte-related data received by the display device 310 and present such data via the display 345 according to various operations described herein. Additionally, the application 330 may 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.

[0176] The application 330 may be downloaded, installed, and initially configured / setup on the display device 310. For example, the display device 310 may obtain the application 330 from the server system 334 or from another source accessed via a communication medium (e.g., communication medium 305), such as an application store, etc. After installation and setup, the application 330 may be used to access and / or interface with analyte data (e.g., whether stored on the server system 334, in the storage device 325 or locally, or from the analyte sensor system 308). By way of illustration, the application 330 may present a menu including various controls or commands that may be executed in connection with the operation of the analyte sensor system 308 and one or more display devices 310. The application 330 may also be used to interface with or control other display devices 310, e.g., to distribute or make available analyte data, including by receiving / transmitting analyte data directly to the other display devices 310 and / or transmitting instructions to the analyte sensor system 308 and other display devices 310 to be connected, as described herein. In some implementations, the application 330 may interact with other application(s) of the display device to retrieve or provide relevant data, such as, for example, other health data.

[0177] The analyte sensor application 330 may include various code / functionality modules, such as, for example, a display module, a menu module, a list module, etc., as will become apparent in light of the description of the various functions herein (e.g., in conjunction with the disclosed methods). These modules may be implemented separately or in combination. Each module may include a computer readable medium and may have computer executable code stored thereon (e.g., as described herein with respect to various operations, flowcharts, etc.), such that the code may be operably coupled to and / or executed by the processor 335 (e.g., may include circuitry for such execution) to perform a particular function related to interfacing with analyte data and performing tasks associated therewith. As described further below, the display module may present various screens to the user (e.g., via the display 345), along with screens containing graphical representations of information provided by the application 330. In further embodiments, the application 330 may be used to display to the user an environment for viewing and interacting with various display devices that may be connectable to the analyte sensor system 308, as well as the analyte sensor system 308 itself. The sensor application 330 may include a native application modified with a software design kit (eg, depending on the operating system) to perform the functions / features described herein.

[0178] 3B, the display device 310 also includes a processor 335. The processor 335 may include processor sub-modules including, for example, an application processor that interfaces with and / or controls other elements of the display device 310 (e.g., the connection interface 315, the applications 330, the GUI 340, the display 345, the RTC 350, etc.). The processor 335 may include a controller and / or microcontroller that provides various controls (e.g., a button and switch interface) associated with device management, such as, for example, a list of available or previously paired devices, information associated with measurements, information associated with network conditions (e.g., link quality, etc.), information associated with the timing, type, and / or structure of messages exchanged between the analyte sensor system 308 and the display device 310, etc. Additionally, the controller may include various controls associated with user input, such as a user fingerprint (e.g., for authenticating a user's access to data or for use in authenticating / encrypting data including analyte data, etc.), as well as aggregation of analyte data.

[0179] The processor 335 may include circuits such as logic circuits, memory, battery, and power circuits, as well as other circuit drivers for peripheral and audio components. The processor 335 and any sub-processors thereof may include logic circuits for receiving, processing, and / or storing data received and / or input to the display device 310, as well as data to be transmitted or distributed by the display device 310. The processor 335 may be coupled to the display 345 as well as the connection interface 315 and the storage device 325 (including the application 330) by a bus. Thus, the processor 335 may receive and process electrical signals generated by these respective elements, and thus perform various functions. As an example, the processor 335 may access stored content from the storage device 325 at the direction of the application 330, and process the stored content for display and / or output by the display 345. Additionally, the processor 335 may process the stored content for transmission to the other display device 310, the analyte sensor system 308, or the server system 334 via the connection interface 315 and the communication medium 305. Display device 310 may include other peripheral components not shown in detail in FIG. 3B.

[0180] In further embodiments, the processor 335 may further acquire, detect, calculate, and / or store data input by a user via the display 345 or GUI 340 or data received from the analyte sensor system 308 (e.g., analyte sensor data or related messages) over a period of time. The processor 335 may use this input to measure the user's physical and / or mental responses in response to the data and / or other factors (e.g., time of day, location, etc.). In various embodiments, the user's responses or other factors may indicate preferences regarding the use of a particular display device 310 under certain conditions and / or the use of a particular connection / transmission scheme under various conditions, as described in further detail herein.

[0181] It should be noted at this point that similarly named elements between the display device 310 and the analyte sensor system 308 may include similar features, structures, and / or capabilities. Thus, with respect to such elements, the description of the display device 310 above may also apply to the analyte sensor system 308, in some cases.

[0182] In some aspects according to the systems, devices, and methods of the present disclosure, health-related and non-health-related data are aggregated, structured, and / or transformed to intelligently generate outputs including new analyte data structures, displays, and control of the devices of the system and other devices of the system. Such health-related information can include glucose and related data (e.g., insulin, diet, activity, etc.), and non-health-related data can include location data, user demographic data, etc. It is recognized that implementations according to such aspects of the present technology 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 be stored and operated, and thereby accelerating the performance of the system as described herein. Furthermore, it is envisioned that implementations according to such aspects of the present technology improve the user's ability to manage their diabetes or other diseases with continuous analyte monitoring. Examples of techniques and tools for generating such outputs related to glucose status, trends, history, context, and insights to help users make informed decisions in managing their diabetes are disclosed below. The disclosed techniques, systems, devices, and tools can also be applied to other health disorders.

[0183] In managing diabetes, an increasing number of diabetic CGM system users want to see more glucose data in the context of their lives over time, such as how blood glucose levels fluctuate during their eating habits (generally specific to a particular meal), their lifestyle (e.g., during the workday and time at home or play), physical activity, etc. However, display screens are limited in size, resolution, and other technical parameters. Furthermore, even larger display screens, cramming more data onto the screen, do not necessarily improve the effectiveness of the data display or aid the user's understanding of the data presented on the screen. To address such limitations in CGM systems, data displays should be intelligently designed and constructed to avoid information overload and confusion, which can lead to misinterpretation of data, confusion, missing information, etc., or even worse, poor decision-making. For example, poor data display can ultimately lead to poor decision-making by the user, which can be detrimental to their glucose management and health.

[0184] Additionally, while more contextual and meaningful data is required, manufacturers of CGM systems must be mindful of regulations and standards set forth by regulatory agencies, e.g., the Federal Drug Administration (FDA). In some cases, data displayed within an "actionable time period," such as within three hours of real time, may be subject to certain limitations or requirements that may affect the classification of CGM devices and associated software apps. These regulations and limitations also impact the cost of those covered products, software, or services.

[0185] Users of CGM devices and related software need more meaningful displays and graphics that can efficiently and intelligently present their health-related data to enable safe and wise decision-making to manage their glucose and health. Using data visualization techniques and modified graphics as described herein, information about the user's glucose status, trends, history, and corresponding context can be intelligently presented, thereby resolving technical and situational challenges (e.g., legal or regulatory) and benefiting the end user both directly (such as providing decision support) and indirectly (such as saving the user time in their daily life while managing their diabetes).

[0186] Visualization of glucose patterns As discussed above, the analyte data collected by the analyte sensor system 308 may include raw sensor data. An unmodified graphical representation of the raw sensor data may be of little value to a user, as the user may potentially miss important information buried in the clutter of the bulk or unmodified raw sensor data. As a result, embodiments described herein include systems and methods for constructing a data structure or arrangement of the analyte data whose features facilitate the display of the analyte data in a modified graphical representation to conveniently show patterns and / or information valuable to the user's health.

[0187] In some embodiments, the analyte sensor system 308 may generate one or more data sets of analyte data corresponding to analyte measurements over one or more time intervals. For example, in some embodiments, the analyte sensor system 308 may generate a data set corresponding to an analyte measurement every five minutes. Other time intervals are possible. The analyte sensor system 308 may generate an analyte concentration value for each analyte data set. The display device 310 may receive the raw analyte concentration values ​​and generate a data structure or array of analyte data, which may then generate a modifiable graphic display. The modifiable graphic display may be efficiently adjusted to modify one or more features that may conveniently indicate patterns or other valuable health information to a viewer.

[0188] In some example implementations, the analyte sensor system 308 or the display device 310 processes the data set to generate a graphical display displayable on the display device 310, the graphical display including an array of analyte concentration values ​​over multiple time intervals that are graphically modified, for example, to show one or more patterns in the analyte data. In some examples, the array of analyte concentration values ​​for the graphical display includes a spatio-temporal organization of analyte concentration values ​​in which the analyte concentration values ​​are located along a first direction according to a first time scale and along a second direction according to a second time scale. The analyte levels of the analyte concentration values ​​are modifiable and are represented in the graphical display by one or more of the following modifications in the graphical display: shape, color, shading, color or shading gradients, different shading, transparency, opacity, buffer areas, graphical icons, arrows, animations, text, numbers, or various intensities or contrasts of gradual fading based on various health parameters, magnitude of the analyte level, and / or statistical metrics associated with the analyte level or groups of analyte levels. In some implementations, an analyte application 330 operable on the display device 310 processes the data set to generate a graphical representation that is displayed on the display 345, which may be modified or adjusted according to the magnitude and / or metric of the analyte level(s).

[0189] FIG. 4A is an illustration of a modified graphic display in which analyte concentration values ​​are arranged and presented over multiple time intervals so that a viewer can easily detect patterns in the analyte data over the multiple time intervals. The data structure or arrangement of analyte data generated by the embodiments described herein may generate a modified graphic display using color, shape, shading, size, or other visual representation to make it easier for a viewer to detect patterns in the analyte data. The analyte application 330 may receive intermittent analyte concentration values ​​corresponding to a raw data set and generate a data structure or arrangement of analyte data that can generate a modified graphic display such as graph 400A. Graph 400A illustrates analyte concentration values ​​over a first direction 402 according to a first time scale. Graph 400A also illustrates analyte concentration values ​​along a second direction 404 according to a second time scale. In the example shown in FIG. 4A, the first time scale is an hourly time scale over a day (24 hours) showing analyte concentration values ​​over a daily time scale across one or more days. The second time scale is a daily time scale over a week (7 days), showing analyte concentration values ​​over an entire week or multiple weeks over a weekly time scale. In the exemplary graph 400A, 24-hour analyte value concentrations over a week are shown, but other time intervals can be used. For example, the first dimension 402 can be an hourly time scale over a daily period, and the second dimension 404 can be a monthly period (e.g., several days in a particular month), a weekday period (e.g., 5 days Monday-Friday), a weekend period, or other selected period including a period selected by a user on a user interface of the display device 310. Averaging or other numerical / statistical techniques can be used to expand or include additional data. For example, in the daily scale 404, the average or other statistically driven data of analyte concentration values ​​of a particular day over a particular period can be represented as the analyte concentration value for that day (e.g., analyte concentration values ​​on Sundays over the past three months).Thus, graph 400A or other 7 day / 24 hour graphs are not limited to only the past 7 day values, but rather amalgamation of data over any period of user or system choice can be used to implement graph 400A and other graphical displays described herein.

[0190] The exemplary graph 400A may be an isometric graph in which the magnitude of the analyte concentration values ​​is represented by shapes along a vertical axis perpendicular to the first and second directions 402 and 404. The size of each shape may correspond to the magnitude of the analyte concentration value. In some implementations, color may 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 shades may be used to identify different magnitudes of the analyte concentration values. For example, shades 406, 408, 410, 412, 414, 4116, 418, or, if color is used, yellow, may be used for areas of the graph 400A where the analyte concentration values ​​exceed a high threshold. Shades 420, 422, 424, and 426 may be used to indicate areas of the graph 400A where the analyte concentration values ​​fall below a low threshold. If color is used, red may be used to indicate areas where the analyte concentration values ​​fall below a low threshold. In the array of analyte concentration values ​​in the exemplary graph 400A, a viewer can determine at a glance when the analyte concentration values ​​exceed the high threshold by observing a peak in the data, or if color is used, the viewer can observe the yellow areas to quickly determine when the analyte concentration values ​​exceed the high threshold. The array of analyte data as shown in the exemplary graph 400A allows the viewer to easily observe patterns in the analyte data. For example, in the exemplary graph 400A, the regions 406, 408, 410, 412, 414, 416, and 418 corresponding to analyte concentration values ​​at about 6:00 PM may show a peak, or if shading is used, the regions 406, 408, 410, 412, 414, 416, and 418 may be shown in a darker color (relative to the other regions) indicating that the analyte concentration values ​​tend to rise around 6:00 PM for the period shown. If color is used, a similar pattern may be observed. By observing such patterns in analyte concentration values, a patient or the patient's caregiver can make better decisions in managing the patient's health care.

[0191] 4B is a graphical representation comprised of an aerial view of graph 400A, shown as graph 400B. Using graph 400B, a user can easily observe patterns in the analyte data. In some implementations, graph 400A may be displayed on display 345 in an interactive manner that allows a user to rotate, twist, yaw, and / or zoom in or out of the displayed graph 400A to manipulate the view of graph 400A. In this regard, display 345 presents graph 400A and allows a user to change the view to graph 400B. As in graph 400A, graph 400B is modified to represent the magnitude of analyte concentration values ​​by shape on the planar graph (e.g., along one or both of first and second directions 402 and 404) to identify features in the analyte data, such as high analyte concentration levels illustrated by an expanded width of the plot for each day at a particular time, and low analyte concentration levels illustrated by a contracted width of the plot for each day at a particular time. Similar to graph 400A, graph 400B may also be modified to present shading or other visual representations associated with features that create an effect that allows a viewer to determine at a glance the times when analyte concentration values ​​exceed or fall below high or low thresholds, for example, by observing modifications to the graphical display within the data.

[0192] FIG. 5 is an illustration of an exemplary graphical display in which analyte concentration values ​​are arranged and presented over multiple time intervals in a ring-shaped graph 500. In such an implementation, a viewer can easily and simply detect one or more patterns in the analyte data over multiple time intervals based on the features generated by the graph 500. The graph 500 includes concentric rings, each ring representing analyte concentration values ​​over a first direction 502 according to a first time scale. The concentric ring-shaped structure of the graph 500 allows for the illustration of analyte concentration values ​​along a radial direction 504 according to a second time scale. In the example graph 500 shown in FIG. 5, the first time scale along the first direction 502 is an hourly time scale over a day (24 hours), which may, for example, indicate hourly analyte concentration values, and the second time scale along the second second time direction 504 is a daily time scale over a week (7 days), which may, for example, indicate daily analyte concentration values. In the exemplary graph 500, 24 hour analyte concentration values ​​over a week are shown. Other time intervals may also be used.

[0193] In the exemplary graph 500, each ring may be shaded or, if color is used, color-coded to represent the magnitude of the analyte concentration value relative to the high threshold, low threshold, and target region. For example, for a ring 506 representing an exemplary display of 24-hour analyte concentration values ​​for a Sunday (or in some embodiments, a fusion of Sundays over a period of time), a first shading 506-1 may be used to indicate times when the analyte concentration value was below the low threshold, a second shading 506-2 may be used to indicate times when the analyte concentration value was within the target range, and a third shading 506-3 may be used to indicate times when the analyte concentration value exceeded the high threshold. In some implementations, colors may be used in addition to or instead of the shadings 506-1, 506-2, and 506-3. For example, red may indicate times when the analyte concentration value was below the low threshold, white may indicate times when the analyte concentration value was within the target range, and yellow may indicate times when the analyte concentration value exceeded the high threshold. In some embodiments, one or more dashed lines may be used in the display of graph 500 to indicate the presence of unreliable or spurious data.

[0194] The arrangement of the analyte data as shown in the exemplary graph 500 allows a viewer to observe patterns in the analyte data. For example, by glancing at the exemplary graph 500, a viewer can quickly observe that for several days within a week, the analyte concentration values ​​exceed a high threshold around 12:00 AM.

[0195] In some embodiments, the data structure or array of analyte concentration values ​​may be configured to generate a modified graphical display in the central region 508 of the graph 500. For example, one or more additional visual representations may be included in the central region 508 to indicate whether the data corresponds to a day or night time. As described above, the GUI 340 of the display device 310 may be configured to receive input from a user of the system 302, for example, via a touch-sensitive display. If such input is present, the user may touch or indicate a point on any of the concentric rings in the graph 500. A measurement of the analyte concentration value corresponding to the touched point may then be displayed in the central region 508. In some embodiments, if no input data is received from the user, an average or other statistically driven representative data value corresponding to the entire period shown in the graph 500 may be displayed in the central region 508. For example, if the user does not indicate a point on the graph 500, a weekly average of the analyte concentration values ​​may be shown. In some examples, one or more additional graphical icons may be shown in the central region 508 to indicate additional information about the analyte concentration values ​​represented in the graph 500. The graphic icon may indicate whether the data relates to daytime, nighttime, weekend, workday, or other time indicator of the graphed data.

[0196] In some embodiments, the user can obtain additional information about a given day by providing input to the analyte sensor app 330, for example, by touching one of the rings of the graph 500. An additional graph showing more details of the day corresponding to the touched ring may be shown instead of or in addition to the graph 500. FIG. 6 illustrates a modified graphical display corresponding to a data structure and array of analyte concentration values ​​over a time interval. The data structure and array of analyte concentration values ​​may generate a graph 600A or 600B in which the analyte concentration values ​​are shown in shapes relative to high and low thresholds and target regions. The time interval shown in the graph 600A or 600B may be a 24-hour period corresponding to the touched ring in the graph 500. Other time intervals may also be used. The graph 600A or 600B may be displayed in parallel, instead of, or in conjunction with the graph 500 when the user indicates a point on the graph 500. Additionally, a user may indicate a different point along the graph 600A using a pointing device or touch screen, and the graph 600A may be updated and modified to display analyte data corresponding to the user's indicated point in the central area 614 of the graph 600A. The updated analyte data may include the analyte concentration value, time, and date corresponding to the point indicated by the user. In the example shown in the graph 600A, the user indicates a desire to view analyte data corresponding to 5:00 a.m. on June 24th 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 indicates a desire to view analyte data values ​​corresponding to 9:00 a.m. on June 24th. The analyte concentration values ​​and corresponding times are modified accordingly and updated in the central area 614.

[0197] In the graph 600A or 600B, analyte concentration values ​​that exceed a high threshold may be indicated by a protrusion extending outward from the outer periphery of the ring of the graph 600A or 600B. Some examples of high threshold protrusions may include outer protrusions 602, 604, and 606. Analyte concentration values ​​that fall below a low threshold may be indicated by a protrusion extending inward from the inner periphery of the graph 600A or 600B. Some examples of low threshold protrusions may include inner protrusions 608, 610, and 612. As described above, in some embodiments, a user may touch a point 616 on or along the ring-shaped graph 600A, and a measurement of the analyte concentration value corresponding to the touched point may be shown in the central region 614 of the graph 600A.

[0198] In some embodiments, the graph 600A or 600B may utilize shading, gradients, or colors that correspond to the magnitude of the analyte concentration values. For example, the graph 600A or 600B may be generated or modified to utilize various intensities and / or contrasts of shading to indicate the analyte concentration values. Shadings 602, 604, 606 and similar shadings may be used to indicate where the analyte concentration values ​​exceed a high threshold. The intensity of the shading may correspond to the magnitude of the analyte concentration values. Shadings 608, 610, 612 and similar shadings may be used in areas of the graph 600A or 600B where the analyte concentration values ​​are below a low threshold. Neutral shadings, such as shade 618, may be used to indicate analyte concentration values ​​within a target range. One skilled in the art may appreciate that the shadings as described above are exemplary and that other visual representations, including other shadings, textures, gradients, and / or colors, may be used.

[0199] 7 is an illustration of a modified graphical display generated by the data structure and arrangement of analyte data over multiple time intervals. The data structure and arrangement of analyte concentration values ​​may generate a cross-sectional graph 700 in which analyte concentration values ​​are plotted in a curved direction and a radial direction in one or more sections. In such an implementation, a viewer may easily and simply detect one or more patterns in the analyte data over multiple time intervals based on the features generated by the graph 700. The graph 700 illustrates analyte concentration values ​​over a first direction 702. The first direction 702 may be a curved direction according to a first time scale. The graph 700 also illustrates analyte concentration values ​​along a second direction 704 according to a second time scale. The second direction 704 may be a radial direction.

[0200] In the example graph 700 of FIG. 7, the first time scale is a daily time scale along a first direction 702 over a week (7 days), which may show, for example, daily analyte concentration values ​​in seven sections. The second time scale is an hourly time scale over a day (24 hours), which may show, for example, hourly analyte concentration values. Other time intervals may also be used. Each section of the graph 700 may represent hourly analyte concentration values ​​over a 24 hour period, with analyte concentration values ​​of the other 24 hours shown adjacent to it. In some embodiments, the sections of the graph 700 may optionally be separated by one or more buffer regions 706. The analyte data represented in the graph 700 need not be limited to analyte data over a seven day period. A fusion of analyte data for each day displayed may also be used to generate the graph 700.

[0201] Graph 700 may be shaded or color coded, as described above in connection with the embodiments of FIGS. 5 and 6, to convey additional information about the analyte concentration values.

[0202] A user can click on any section of graph 700 to obtain an exclusive view of the time interval corresponding to that section. In some embodiments, upon selection of a section, the graphical display 700 can be modified to show that the remaining sections shrink to the selected section, and only the selected section is then modified to provide a graphical display focused on the selected section. High and low graphs corresponding to the analyte data for the high and low thresholds can also be displayed in conjunction with graph 700 while the remaining sections are in the shrinking motion.

[0203] 8 is an illustration of a modified graphical display generated by the data structure and arrangement of analyte data over multiple time intervals. The data structure and arrangement of analyte concentration values ​​may generate a graph 800 in which analyte concentration values ​​are shown over multiple time intervals across a time scale 802. The magnitude of the analyte concentration values ​​may be represented on a vertical axis 804. The time scale 802 may represent a 24 hour period. However, other time periods may be constructed and displayed. Each line graph 806, 808, 810, etc. represents analyte concentration values ​​over a different 24 hour period. For example, analyte concentration values ​​over a week may be represented by line graphs 806, 808, 810, etc. A fusion of the analyte data for each day displayed may also be used to generate the line graphs 806, 808, 810, etc. Each line graph may utilize areas under the curves shaded with different opacities to visually distinguish the analyte concentration values ​​for different time intervals. A user can point to a point on the graph 800 with a pointing device or via a touch screen, and a callout window 812 can be displayed that contains a measured analyte concentration value that corresponds to the selected point on the graph 800.

[0204] In some embodiments, one or more side tabs may be utilized to separate the visual presentation of the analyte data to present a more focused view. For example, if line graphs 806, 808, 810, etc. represent a week of analyte data, a set of side tabs or buttons 806-1, 808-1, ..., 810-1 may be used, where activation of side tab or button 806-1 will cause line graph 806 and its corresponding area to be displayed more prominently, below the curves and opacity of the other displayed analyte data. Non-selected analyte data may be displayed in a less prominent shade. Side tab or button 814 may activate and prominently display all analyte data.

[0205] In some embodiments, one or more buttons or icons may be used to separate the analyte data for the high and low thresholds. For example, in the graph 800, a user may point to the high threshold button 816 via a pointing device or by touching a touch screen. The graph 800 may be modified to visually distinguish regions of the analyte data having a magnitude higher than one or more high thresholds. The visually distinguishing may be created by using different shading, gradients, or, if color is used, by using different intensities or gradients of color. Similarly, a user may point to the low threshold button 818 via a pointing device or by touching a touch screen. The graph 800 may be modified to visually distinguish regions of the analyte data having a magnitude lower than one or more low thresholds. The buttons or icons 816 and 818 may be displayed when pressed, thereby activating their corresponding displays, or may be displayed when not pressed, thereby deactivating their corresponding displays. In some embodiments, cumulative information about the analyte data corresponding to the analyte data captured by the graph 800 may be shown. For example, one or more icons or visual representations may be shown indicating the percentage of analyte data above a high threshold, below a low threshold, and within the high and low thresholds, respectively. The percentage icons may be shown simultaneously when the corresponding high or low threshold buttons are pressed. In one embodiment, the percentage icons may be circular in shape, with the thickness, color intensity, or opacity of the circle being determined based on the percentage shown at the center of the circle.

[0206] The high and low thresholds may be entered by a user or may be derived from the patient data or data available to the system 302. Multiple thresholds may be entered, defined, or derived for different time intervals, periods of time, or dates. The graph 800 may be rendered in color, as described above in connection with the embodiments of Figures 5 and 6.

[0207] 9 is an illustration of a modified graphical display generated by the data structure and arrangement of analyte data over multiple time intervals. The data structure and arrangement of analyte concentration values ​​may generate a graph 900 in which analyte concentration values ​​are shown over multiple time intervals across a time scale 902. The magnitude of the analyte concentration values ​​may be represented on a vertical axis 904. The time scale 902 may represent a 24 hour period. However, other time periods may be constructed and displayed. Each of the exemplary line graphs 906, 908, 910, etc. represent analyte concentration values ​​over a different 24 hour period. For example, analyte concentration values ​​over a week may be represented by line graphs 906, 908, 910, etc. A user may point to any portion of the graph 900 via a pointing device, for example, by moving a mouse pointer across the graph 900 or by touching a touch screen display displaying the graph 900. An icon or overlay graphical display, callout window 912, etc. may be shown on the graph 900 where the user points, and the callout window may display the analyte data measurement corresponding to the point selected by the user. If the user clicks or points to a portion of the graph 900 where overlapping or future data is detected, a graphical display 914 may appear within the area of ​​the graph 900 directing the user to click for more information. When the user clicks on the graphical display 914, an additional graphical display, for example a text box 916, may appear within the area of ​​the graph 900 to provide the user with additional information.

[0208] In some embodiments, the line graphs 906, 908, 910, etc. may be rendered in different lines or styles depending on the confidence level of the underlying analyte data they represent. For example, a dashed line style may indicate uncertain analyte data. A continuous line may indicate reliably tracked analyte data. A dotted line 924 may indicate predicted future analyte data. A graph key 918 may be included in the display of the graph 900 along with a description of each line graph style.

[0209] In some embodiments, one or more buttons or icons may be used to separate the analyte data for the high and low thresholds. For example, in the graph 900, a user may point to a high threshold button or other virtual menu or button option via a pointing device or by touching a touch screen. The graph 900 may be modified to visually distinguish regions 920 of analyte data having magnitudes higher than one or more high thresholds. The visual distinction may be created by using different shading, gradients, or, if color is used, by using different intensities or gradients of color. Similarly, a user may point to a low threshold button or other virtual menu or button option via a pointing device or by touching a touch screen. The graph 900 may be modified to visually distinguish regions 922 of analyte data having magnitudes lower than one or more low thresholds. The buttons or icons may be displayed when pressed, thereby activating their corresponding displays, or may be displayed when not pressed, thereby deactivating their corresponding displays.

[0210] FIG. 10 is an illustration of a modified graphical display of FIG. 9. Graphic 1000 is similar to graph 900 when a threshold visibility button or other virtual menu or button option is pressed or activated. Regions that exceed one or more high thresholds 1002 and 1004 are visually distinguished by a first style of shading to indicate the time when the analyte data values ​​exceeded the high thresholds 1002 and 1004. Regions that fall below one or more low thresholds 1006 and 1008 are visually distinguished by a second style of shading to indicate the time when the analyte data values ​​fell below the low thresholds 1006 and 1008. As discussed above in connection with FIG. 9, other means of visually distinguishing between high and low deviations in the analyte data may be used. For example, if color is used, a gradient of color or different intensities of color may be used.

[0211] The exemplary graph 1100 as shown in FIG. 11 may be used to provide any of the line graphs 906, 908, 910, etc. from graph 900, as well as a daily analysis of features 602, 604, 606, 608, etc. from graph 600A or 600B. Alternatively, other time intervals may be used. The exemplary graph 1100 uses a bar graph to view a daily analysis of the analyte data. The axis 1102 indicates time. The magnitude of the analyte concentration values ​​may be represented on the vertical axis 1104. A user may trigger the display of the graph 1100 by indicating a particular line graph 906, 908, or 910 via a pointing device or by touching a touch screen. One or more lines may indicate a range of average analyte concentration values ​​of the underlying analyte data used to generate the graph 1100 and / or the threshold levels. In the example shown in FIG. 11, upper threshold levels 1002 and 1004 and lower threshold levels 1006 and 1008 are displayed on a graph 1100 .

[0212] 12 is an illustration of an exemplary graphical display in which analyte concentration values ​​are arranged and presented over multiple time intervals and shown on a clock dial graph 1200, allowing a viewer to easily detect one or more patterns in the analyte data over the multiple time intervals. In one implementation, the graph 1200 may utilize different shading, each corresponding to analyte concentration values ​​above a high threshold, below a low threshold, or within a target value. Analyte concentration values ​​for several time intervals (e.g., several days) may be overlaid to construct the graph 1200. In this scenario, a slope may be generated to indicate a pattern over the multiple time intervals illustrated in the graph 1200. For example, a darker shading 1208 may be used to indicate analyte concentration values ​​below a low threshold, and the slope of the shading 1208 for the time between 3:00 a.m. and 6:00 a.m. may indicate a decline in the analyte value during that time over the seven days. A user can conveniently align this pattern to the analyte data over a seven day period and take appropriate action to better manage their health. In some embodiments, an analyte trend value graphic may also be included in the graph 1200 using a line graph 1202 to show the change in analyte concentration values.

[0213] In some implementations, the line graph 1202 may be an analyte level trace superimposed on a clock dial graph 1200 such that higher analyte levels are closer to the outer curved region of the graph 1200 and lower analyte levels are closer to the inner curved region of the graph 1200, or vice versa. As described, the graph 1200 may use various gradients and / or contrasting shading to represent various analyte level values. Higher analyte levels may be in a first shade 1206, lower analyte levels may be in a second shade 1204, and analyte levels between the higher and lower analyte levels may be in a third shade 1208. The analyte level trace 1202 may include an average analyte level for the daily analyte concentration values, or alternatively, a current analyte level over an hourly time scale.

[0214] In some implementations, the most recently detected analyte concentration value or an average of the analyte concentration values ​​may be displayed in the center 1204 of the graph 1200. In some implementations, an additional icon may indicate whether the data illustrated in the graph 1200 corresponds to day or night time values.

[0215] In some embodiments, the implemented graphical display 1200 can be rendered on the display 345. The display device 310 can receive input from a user (e.g., a tap on the touch screen 345) and invert the graph 1200 to show a display graphic illustrating the percentage of time that the user experienced an analyte concentration value that exceeded a high threshold, fell below a low threshold, or was within two thresholds for the period of time illustrated in the graph 1200.

[0216] 13A illustrates a flowchart 1300 of an example method by which the system 302 can generate and display modified graphical displays 400A, 400B, 500, 600, 700, 800, 900, 1000, 1100, and 1200 according to some embodiments. The process 1300 begins at block 1302. At block 1304, the analyte sensor application 330 may receive analyte data obtained from the continuous analyte sensor device 375 or from the sensor measurement circuitry 370 at the display device 310. The analyte data received at the analyte sensor application 330 may include analyte concentration values ​​associated with analyte measurements over a period of time. At block 1306, the analyte sensor application 330 may cause the processor 335 to process the analyte concentration values ​​at the display device 310 to generate an array of analyte concentration values ​​over a number of time intervals. At block 1308, the analyte sensor application 330 may cause the processor 335 to generate a graphic of the array of analyte concentration values. At block 1310, the analyte sensor application 330 may cause the processor 335 to modify the graphic to indicate one or more characteristics of the analyte concentration values. For example, the graphic may be modified to indicate one or more patterns of analyte concentration values ​​by modifying the graphic to indicate one or more characteristics in the analyte concentration values. At block 1312, the analyte sensor application 330 may cause the processor 335 to display the modified graphic on the display 345 of the display device 310. The method ends at block 1314.

[0217] 13B illustrates a flow chart 1306 of an exemplary method for implementing the process identified in block 1306 of FIG. 13A to process analyte data, such as analyte concentration values, to generate an array of analyte concentration values ​​over a plurality of times. While this exemplary method is described in which the processor 335 of the display device 310 implements the method, it is understood that other devices of the system may be configured to implement the method. The process 1306 begins at block 1316. In some implementations, in block 1318, the processor 335 aggregates analyte concentration value groups based on their time values ​​for a certain time. For example, a day, week, month, or other period of analyte data may be aggregated based on 5, 10, 15, or other time points throughout the day, such as analyte concentration values ​​grouped at, for example, 12:00 PM, 12:10 PM, 12:20 PM, 12:30 PM, etc. In some cases, the analyte concentration values ​​may not all coincide with time values ​​for the same time, such as 12:00 PM, 12:01 PM, 11:59 PM, etc. In such cases, the processor 335 may associate the analyte concentration values ​​with a particular time (e.g., 12:00 PM) for all values ​​within a range, e.g., ±5 minutes.

[0218] In block 1320, the processor 335 may flag or populate the analyte data with additional data used to generate the graphic in block 1308 of FIG. 13A or to generate the modified graphic in block 1310. The graphics may include the graphical representations described above associated with graphs 400A, 400B, 500, 600, 700, 800, 900, 1000, 1100, and 1200, among other graphics. The additional data may include flagging or aggregating the analyte data based on one or more time scales, one or more sets of high and low thresholds for the analyte data in receptors or receptor groups, relationship of the tagged or tabulated analyte data, contextual information associated with the aggregated analyte data collected in block 1318, and any other information that may be later recalled or otherwise used to generate or modify the graphical representation of the graph described above. In some implementations, after analyzing the data, a process is performed to flag or embed additional data with the analyte data, as shown in block 1322.

[0219] At block 1322, the processor 335 analyzes the grouped analyte concentration values. In some implementations, the processor 335 may determine a maximum and / or minimum value(s) of the grouped values. In some implementations, the processor 335 may determine a mean, median, standard deviation, or other statistical metric of the grouped values. Additionally, the processor 335 may perform Fourier transforms, Laplace transforms, and / or sampling techniques on the grouped analyte concentration values ​​to help form a modified graphical display showing patterns in the analyte data, for example, at block 1310 of FIG. 13A. In some implementations, the process at block 1320 is performed on the analyzed group of analyte concentration values ​​after block 1322, which may flag or embed additional data for use in modifying the graphic at block 1310. For example, the analyzed group of analyte concentration values ​​may have a mean, median, standard deviation, etc. that exceeds a predetermined threshold or is outside a predetermined range, and the additional data may be flagged or embedded.

[0220] At block 1324, the processor 335 arranges the analyses of analyte concentration values ​​based on spatial or temporal parameters associated with the modified graphic types as described above associated with graphs 400A, 400B, 500, 600, 700, 800, 900, 1000, 1100, and 1200. For example, if the graphic includes a second time scale, the processor 335 may arrange the analyses of analyte concentration values ​​according to their time of day values ​​relative to the second time scale, such as days of the week, days of the month, selected days of the period (such as work days, vacation days, or other user selected time frame), etc.

[0221] At block 1326, processor 335 forms a dataset of the sequenced analyte data. The dataset is configured such that it can be processed by processor 335 as a basis for forming a graphical display displayable on display 345, for example, at block 1308 of FIGURE 13A. As described above, the dataset generated at block 1326 is self-referential and includes information for generating the graphic at block 1308 of FIGURE 13A or the modified graphic at block 1310 of FIGURE 13A.

[0222] Some advantages of the method and system may include the following: The self-referential data set (SRDS) generated in block 1326 eliminates the need for the processor 335 to search and call up necessary information from various parts of the system 302 to generate the graphics of blocks 1308 and 1310. Otherwise, for example, without the self-referential data set generated in block 1326, the processor 335 would have to search, query, and / or call up various parts of the system 302 each time a user requested a different graphic or requested modification of a displayed graphic. In this manner, the self-referential data set generated in block 1326 improves the operation of the system 302 by reducing the complexity in data processing and data transmission between various parts of the system 302. For example, with the SRDS, the system does not need to store or process additional algorithms, such as, for example, pattern recognition algorithms, to generate an output, such as a display to convey pattern information to a user. Additionally, the self-referential data set generated in block 1326 may reduce the amount and frequency of data that must be transmitted for purposes of generating the graphic displays of blocks 1308 and 1310 of FIG. 13A. Therefore, the associated processing or graphics algorithms that have to be stored and operated are also reduced, and the performance of the system 302 is improved.

[0223] The process 1306 ends at block 1328, with further processing continuing at block 1308 of FIG. 13A.

[0224] 13C illustrates a flow chart 1308 of an exemplary method for implementing the process identified in block 1308 of FIG. 13A to generate a graphic of an array of analyte concentration values. Although this exemplary method is described in which the processor 335 of the display device 310 implements the method, it is 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 associated with the user's desired graphical display. These may include the type of graphical display desired (e.g., a chart such as text, bar, pie, or other chart, and / or graphical displays such as 400A, 400B, 500, 600, 700, 800, 900, 1000, 1100, and 1200, or other graphical display), and / or the range over which the user desires to view the graphical display for one or more time scales over which the data set of process 1306 is being formed.

[0225] At block 1334, the processor 335 may receive hardware or software data associated with the display device 310 or display 345. The display data may include, for example, available viewing areas, available orientations, and available input device sizes, dimensions, or resolutions. At block 1336, the processor 335 may determine whether the self-referencing data set formed at block 1326 includes all the information necessary to generate the user's desired graphics. As an example, the user may be requesting the display of analyte data that is outside the range captured in the self-referencing data set. In these cases, the process 1306 may be repeated and a more comprehensive self-referencing data set may be formed. In most cases, however, the self-referencing data set is formed in such a way that it includes all the information and data necessary to generate the user's desired graph.

[0226] At block 1338, the processor 335 reformats the self-referencing dataset based on the user input data and the display device data, and generates a formatted self-referencing dataset. For example, if the user's desired display range is smaller than the range of data captured in the self-referencing dataset, the processor 335 at block 1338 may filter out the undesired or out-of-range data by erasing that data from the self-referencing dataset. At block 1340, the processor 335 generates a graphic of the array of analyte concentration values ​​based on the formatted self-referencing dataset. The processing involved in block 1340 may depend on the type of graphic and display device data selected by the user. For example, if the user desires a graph 400A as described above in connection with FIG. 4A, the processor 335 may determine the correct scale for generating the graph 400A based on the available viewing area and the orientation of the display device 345.

[0227] The process 1308 ends at block 1342, with further processing continuing at block 1310 of FIG. 13A.

[0228] FIG. 13D illustrates a flow chart 1310 of an exemplary method for implementing the process identified in block 1310 of FIG. 13A to modify a graphic to indicate one or more features in the analyte concentration values. Although this exemplary method is described in which the processor 335 of the display device 310 implements the method, it is understood that other devices of the system may be configured to implement the method. In response to a graphical representation selected by a user, the processor 335 may modify the graphic generated by process 1308 to indicate one or more features and / or patterns in the analyte data. Furthermore, the modified graphic may present the data in a form that reduces information overload and possible user misinterpretation of the presented data. For example, if a user selects a three-dimensional graph, such as graphical representation 400A, certain portions of the graphed analyte data may block other portions of the graphed data. Process 1310 may detect such instances and modify the graphed data accordingly, for example, by making portions of the graphed analyte data transparent in the overlapping areas.

[0229] Process 1310 may use color to modify the graphics generated by process 1308. For example, process 1310 may add various shades of color to the graphed analyte data associated with one or more sets of high and low thresholds. Process 1310 may utilize flagged or additional embedded information obtained in block 1320 of process 1306 to color-code the graphed data. For example, processor 335 may detect portions of the graphed data that correspond to analyte values ​​that are 20%-30% higher than the high threshold. A yellow color or shade may be used to modify the graphed analyte data to indicate these values. If the graphed analyte data in another portion is 40%-50% higher than the high threshold, a contrasting shade (e.g., a darker shade of a gray gradient, or a darker shade of yellow, if color is used) may be used to indicate that portion of the analyte data. Processor 335 may detect and modify portions of the graphed data associated with high and low thresholds by referencing flags or additional embedded data in the self-referencing data set.

[0230] In some examples, process 1310 can utilize the statistical analysis obtained in block 1322 of process 1306 to modify the graphics generated by process 1308. For example, the self-referencing data set (SRDS) can include flags or embedded data indicating which analyte values ​​are outside of acceptable multiples of the standard deviation value of the analyte data or which analyte values ​​are statistically unreliable. The processor 335 can modify the graphed data based on the statistically derived flags in the SRDS.

[0231] In some implementations, the SRDS may include flags or embedded information based on the context of the analyte data. The context of the analyte data may be obtained or derived from a variety of sources. For example, if analyte values ​​obtained on a particular day of the week are consistent with the mobile display device 310 being detected at a restaurant, the SRDS may include flags or embedded information indicating this correlation. The frequency of detected correlations between the analyte data and the context of the data may also be included within the SRDS. The processor 335 may modify the graphed data to include features according to the context-based flags found within the SRDS to provide a visual representation of a pattern of the user's behavior related to the analyte data over a period of time. The user may make health or diabetes related decisions based in part on the modified graphed analyte data and the features described herein.

[0232] In some implementations, the processor 335 may modify the graphed data, where the modifications are made based on detecting patterns in the flags or embedded information in the SRDS. For example, the SRDS may include flags indicating peaks and valleys in the analyte data. The processor 335 may detect that in a two-dimensional graph with many concentrated peaks, different sections of the graphed analyte data may visually blend together, making identification of these peaks difficult for the viewer. In such cases, the processor 335 may increase or introduce buffer regions between various sections of the graphed analyte data to remedy this scenario. The processor 335 may reference the flags or additional embedded data in the SRDS to detect peaks and valleys in the data, determine whether a pattern exists in which peaks are graphed too close together, and modify the graphed data to include new or increased buffer regions to aid in easier visual interpretation of the graphed data.

[0233] The process 1310 begins at block 1344. The process 1310 then proceeds with a series of decisions followed by modification of the graphed data to show characteristics of the analyte data. For example, the graphed data may be modified to show one or more patterns in the analyte concentration values ​​by modifying the graphics to show one or more characteristics in the analyte concentration values. Those skilled 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 may be devised and implemented without departing from the spirit of the present technology. Also, not all of the disclosed decision-making and modification steps may be required in all implementations. Depending on the user's desired graphical display, one or more decision-making and modification steps may be removed, or other steps may be added.

[0234] At decision block 1346, the processor 335 scans the SRDS to detect whether there are flags or additional embedded data associated with a relationship between the analyte data and one or more high and low thresholds. The SRDS may contain a variety of such flags or additional embedded information. For example, the analyte data in the SRDS may be flagged or correlated to thresholds where different time scales within the analyte values ​​of the SRDS may have their own associated thresholds. The analyte data in the SRDS may be flagged based on the percentage or extent to which the analyte data exceeds or falls below a high or low threshold. At block 1348, depending on the configuration of the threshold flags and the type of graphics requested by the user, the processor 335 modifies the graphed data to show characteristics and / or patterns of the analyte data.

[0235] In some implementations, the modification may include using color, gradient color, shading, varying degrees of transparency or opacity, and varying the color, gradient, or transparency based on overlap and underlying area to enable visual representational detection of features and / or patterns in the sample data as described above associated with modified graphical representations 400A, 400B, 500, 600, 700, 800, 900, 1000, 1100, and 1200.

[0236] In block 1350, the processor 335 scans the SRDS to detect whether there is a flag or embedded additional data in the SRDS that is associated with the statistical analysis performed in process 1306. The processor 335 can modify the graphed data based on the flag or embedded additional data in the SRDS, where the flag or embedded additional data is based on the statistical analysis. For example, the analyte data in the SRDS can be flagged based on the relationship of the analyte data to a standard deviation value, a mean value, a variance value, or other statistical parameter associated with the underlying analyte data. In some implementations, the analyte data in the SRDS can be flagged if it is outside of an acceptable multiplier of the standard deviation value of the analyte data. The corresponding graphic modification of the graphed analyte data can be based on these flags. Or, the analyte data within two multipliers of the standard deviation value of the analyte data can be flagged to later modify the graphed data with color.

[0237] If the SRDS includes statistically based flags or embedded information and their corresponding graphical modifications, the processor 335 may modify the graphed data accordingly, at block 1352. In some implementations, the modifications may include using colors, color gradients, shading, and varying degrees of transparency or opacity to enable visual representational detection of features and / or patterns in the analyte data as described above with respect to the modified graphical representations 400A, 400B, 500, 600, 700, 800, 900, 1000, 1100, and 1200.

[0238] In block 1354, the processor 335 may scan the SRDS to detect whether there is a flag or additional data embedded that is associated with the context of the analyte data. Some examples of the context of the analyte data may include contextual information regarding the user's location when the analyte data was collected (e.g., whether the user was at a restaurant, gym, home or work or school, and how often the user appeared 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 participated in an exercise session, or was awake or asleep, whether insulin was taken, and how much). The contextual analyte data may be obtained automatically without user intervention, or may be entered by the user.

[0239] The 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 may be flagged, embedded, or otherwise referenced in the SRDS. In block 1356, the processor 335 can modify the graphed data based on the contextual flags or embedded data in the SRDS. Various graphic modifications corresponding to different contexts can be programmed in the process 1310. The contextual modifications can include the use of colors, color gradients, shading, various degrees of transparency or opacity to enable visual representational detection of features and / or patterns in the analyte data as described above in connection with the modified graphic representations 400A, 400B, 500, 600, 700, 800, 900, 1000, 1100, and 1200.

[0240] The graphical modifications of process 1310 are not limited to the examples listed above. A variety of graphics can be used for the modifications to indicate features, patterns, or trends in the analyte data and to conveniently alert or communicate health or diabetes related data to the user. Processor 335 can use graphics or graphical techniques such as graphic icons, animations, text or text boxes, fonts and stylized text or numbers, arrows, graduated fading, or other techniques to modify the data graphed in process 1310.

[0241] In block 1358, the processor 335 may scan the flags in the SRDS and the graphic generated by process 1308 to determine whether other modifications to the graphed data can further improve readability, reduce clutter, and better show features and / or patterns in the analyte data. For example, as described above, if the processor 335 detects a large number of concentrated peaks in the graphed data and associated flags in the SRDS based on the type of data graphed, then in block 1360 the processor 335 may modify the graphed data by introducing or adding one or more buffer regions to improve readability and better show features and / or patterns in the analyte data. The processor 335 may also analyze the graphed data generated by process 1308 and the flagged data in the SRDS to detect whether overlapping regions are rendered in a manner that reduces the conveyance of information in the graphed data. In block 1360, the processor 335 may modify the color, shading, gradient, spacing, or transparency within the overlapping regions to visually distinguish the overlapping regions and improve the ability of the graphed data to communicate features, patterns, or trends in the analyte data. One of ordinary skill in the art may readily determine additional analysis of the flags and graphed data and their associated modifications to improve communication of health or diabetes related data. Process 1310 ends at block 1362, with further processing passing to block 1312 of FIG. 13A.

[0242] Although in some implementations, the process of generating the SRDS, the graphed data, and the modified graphed data are described in connection with historical or collected analyte data, the systems and methods of the present technology may be used with future or predicted analyte data, or a combination of historical collected and future analyte data.

[0243] Insulin visualization The embodiments described herein are not limited to generating data structures based on analyte data. Raw data for other compounds associated with the patient's health may also be received, and the system may generate data structures and data arrays capable of generating modified graphic displays based on such data. For example, the system may receive data corresponding to a patient's residual insulin (IOB) level, and generate a data structure or data array capable of generating modified graphic displays to conveniently show useful information about the patient's health. The methods associated with Figures 13A-13D may be implemented to generate modified graphic displays associated with insulin data.

[0244] FIG. 14 is an illustration of a modified graphical display 1400 generated from the data structure and the array of insulin data. The display 1400 may include a ring 1402, where a full circle ring may represent the duration of insulin action (DIA). An overlay ring 1404 may represent the time remaining relative to the amount of remaining insulin. The size of the overlay ring 1404 may be determined as a fraction of the full circle DIA. For example, if one hour of a four hour DIA remains, the remaining time would be one quarter of the total DIA. In this case, the overlay ring 1404 may overlap only one quarter of the ring 1402. When the user takes a dose of insulin, the overlay ring 1404 overlaps the entire ring 1402. As time passes and the insulin is metabolized, the overlay ring 1404 gradually decreases. In some embodiments, the ring 1402 and the overlay ring 1404 may each be rendered in a different shade to better visually distinguish the two. In some embodiments, color is used to visually distinguish between the two. A graphical representation 1406 corresponding to the time remaining may be shown in the center of the ring 1402. In some embodiments, the graphical representation 1406 includes a number representing the amount of remaining insulin.

[0245] If the overlay ring 1404 is gradually decreased over an extended period of time, the gradual decrease may be difficult for some viewers to discern. In some embodiments, when the graphical display 1400 is generated, the overlay ring 1404 is initially shown completely overlapping the ring 1402, and the graphical representation 1406 is shown to correspond to the DIA. Over a short period of time, the overlay ring 1404 is quickly reduced in size to correspond to the time remaining for the current amount of remaining insulin. Over the same amount of time, the graphical representation 1406 may be shown decreasing to settle on the current amount of remaining insulin. For example, if a number is used for the graphical display 1406, the number may decrease similar to a quick counter counting down and settle on the current amount of remaining insulin. Showing such graphics for the overlay ring 1404 and the graphical representation 1406 for a short period of time may help the viewer discern which information the graphical display 1400 conveys.

[0246] The SRDS generated based on the insulin data can be flagged to include appropriate triggers for animation, overlay graphs, and text information, as described above, according to some embodiments of process 1306. In some implementations, when the graphical display 1400 is initiated, processes 1308 and 1310 parse the SRDS for flags associated with the generation of the graphic 1400 and modify the graphic generated by process 1308 to generate the modified graphic 1400.

[0247] In some embodiments, the analyte sensor app 330 can be configured to receive event data, which may include information about user behavior and activities related to health care or diabetes. For example, the event data may include meals consumed, type, duration and intensity of exercise, and amount and type of insulin taken. The analyte sensor app 330 can be configured to generate data structures and arrangements of the analyte data that can then generate modified graphical displays that can visually represent one or more relationships of the analyte data, insulin data, and event data to one another and / or to or in relation to a period of time. For example, based on the visual representation arrangements generated from the SRDS, a user of the system 302 can conveniently make health-related decisions or detect features and / or patterns without undue mental activity.

[0248] 15 and 16 illustrate modified graphical displays 1500 and 1600 generated from data structures and arrangements of data according to embodiments, where the graphical displays 1500 and 1600 include visual representations showing one or more relationships of insulin data, analyte data, and events with each other and / or with or related to a period of time. In various implementations of the modified graphical displays 1500 and 1600, the displays can include displays of one or more of insulin data, analyte data, or event data, which can be modified to further display visual representations showing one or more associations of the insulin data, analyte data, or event data with each other or with a period of time. The visual representations can be shaped and configured or scaled so as not to obscure the display of the insulin data, analyte data, or event data. Additionally, the visual representations can be displayed in their entirety within the display of the insulin data, glucose data, or event data.

[0249] The graphical display 1500 may include a analyte trend graph 1502. On the horizontal axis 1504, time is represented. On the vertical axis 1506, magnitude of the analyte data is represented. The analyte trend graph 1502 may be represented in relation to high and low thresholds 1508 and 1510. Although not all embodiments are shown, the analyte trend graph 1502 may be rendered with various colors, line styles, or shading associated with the high and low thresholds 1508 and 1510 to visually indicate the relationship between the analyte data and the high and low thresholds 1508 and 1510. The graphical display 1500 may further include an event data display area 1512. In the example of FIG. 15, event data is not shown in the event data display area 1512, but may also be displayed therein. An example of event data is shown later in FIG. 16, where various icons and graphical representations are shown in the event data display area 1512. Referring back to FIG. 15 , the graphical display 1500 may further include a graph of insulin data 1514. The horizontal axis 1516 may represent time. The vertical axis 1518 may represent the magnitude of the insulin data. The user may zoom in or zoom out on the time period over which the analyte trend graph 1502 and the insulin graph 1514 are displayed via different time tabs 1520. The graphical display or icon 1522 may indicate to the user that by changing the orientation of the mobile computing device from portrait to landscape or vice versa, the user may obtain different visual representations of the relationships between the analyte data, the insulin data, the event data, and time. The event display area 1512 may include a display of a graphical arrangement of event data, including one or more of carbohydrate intake, amount of time spent exercising, amount of calories burned, or heart rate reaching those thresholds or times.

[0250] 16, the graphical display 1600 is similar to the graphical display 1500. The event data display area 1612 may allow easy access to indicators of when a user took actions that may be considered relevant to the user's diabetes management. For example, a meal intake may be indicated by a label or graphic icon 1616, or an exercise session may be indicated by a label or graphic icon 1618. The event display area 1612 may be generated and shown to the patient's caregiver for quick access to patient actions related to diabetes management. In some implementations, a user may be presented with a series of graphic icons of actions that may be related to diabetes management, and the user may drag and drop them onto the analyte trend graph 1602 or the event display area 1612 to indicate when the user took those actions. For example, the user may drag the meal event graphic icon 1616 and drop it onto the analyte trend graph 1602 at approximately 12:00 PM. The event display area 1612 may then be updated to show the graphic icon 1616 corresponding to the user having a meal at approximately 12:00 PM. Similarly, the user may add an exercise icon at approximately 6:30 p.m. In some embodiments, the user may also enter event information via voice recognition or keyboard entry, and the event display area 1612 may automatically update based on the user's input showing associated icons, such as a meal icon 1616 and an exercise icon 1618.

[0251] A user may also utilize a pointing device or touch screen to point to or touch a point on the analyte trend graph 1602 to activate a callout window 1620. The callout window 1620 may include more detailed information related to the event data displayed in the event data display area 1612. The callout window 1620 may include, for example, a timestamp, the type or amount of food the user ate, the type, intensity, and duration of any exercise the user performed, some indication of the user's general mood, and the type and amount of insulin the user took. The callout window 1620 may include a graphical array of insulin data, including one or more of the following: bolus or basal insulin, time of bolus insulin administration, time of basal insulin administration, or remaining insulin value.

[0252] Some implementations of the graphical display 1500 or 1600 may include a chart key. Figure 17 illustrates an example of an insulin chart key 1700 that may optionally be generated and displayed along with the graphical display 1500 or 1600. The chart key 1700 may include graphical displays 1702, 1704, 1706, 1708, and 1710 that correspond to different types of insulin a user may take, which may include, for example, basal body temperature, bolus, extended bolus, combo bolus, and basal.

[0253] 18 illustrates a modified graphical display 1800 generated from a data structure and an arrangement of data according to an embodiment where the graphical display 1800 includes a visual representation showing one or more relationships between insulin data and analyte data. The modified graphical display 1800 may include an analyte trend graph 1802. Time is represented on a horizontal axis 1804. A magnitude of analyte data is represented on a vertical axis 1806. One or more amounts of remaining insulin (IOB) data may be represented on or above the analyte trend graph 1802 by utilizing one or more arrows 1808 and 1810, the size of the arrows 1808 and 1810 corresponding to the amount of remaining insulin (IOB). Optionally, one or more numerical representations of the amount of remaining insulin (IOB) may be displayed on or above the arrows 1808 and 1810, for example as text.

[0254] In an illustrative example of the use of the modified graphical display 1800, the data set structure may be formed to allow for an intuitive visual representation of the meaning or effect of the IOB data it contains and displays. For example, instead of just a number, remaining insulin is visually represented as a downward arrow on top of a glucose trend chart. This may be intuitive, since it is understood that physiologically, insulin pushes glucose down. The more remaining insulin, the larger the arrow (the more force it pushes). The number of units may also be optionally displayed with the arrow. In the case of an exemplary use where the user has eaten and taken insulin, the user does not necessarily need to take more insulin again because the insulin did not work, which may then prevent insulin stacking, may be a useful reminder. In the case of the opposite use, for example, if the user forgets to take insulin, the absence of an arrow (or a small arrow) may be a reminder that they forgot.

[0255] Algorithm visualization and decision support Diabetes can be a complex disease in which patients must make frequent treatment decisions. As such, the mental demands and stress of managing diabetes can be a heavy burden on patients. The system 302 can utilize available data to present graphical displays illustrating one or more relationships between analyte data and the user's past, present, and future actions to aid in the analysis and health management of the patient.

[0256] 19A and 19B illustrate modified graphical displays 1900A and 1900B generated from the data structure and arrangement of data according to an embodiment where the graphical displays 1900A and 1900B include visual representations showing one or more relationships of insulin data and analyte data based on historical, current, and predicted analyte values. The modified graphical display 1900A may include an analyte trend graph 1902. On the horizontal axis, time is represented and on the vertical axis, the magnitude of the analyte data is represented. The graphical display 1900A may include a current value of the analyte data 1912. The graphical display 1900A may be a predictive trend graph based on actions and may include one or more predictive graph lines 1904, 1906, and 1908 based on the actions of the user. These actions may include, for example, eating, exercising, or not performing an action. The predictive graph lines 1904, 1906, and 1908 may be based on actions the user has already taken or may be based on actions the user is considering. Alternatively, the predictions may be illustrated as ranges 1910 as illustrated in graphical display 1900B. Depending on the one or more confidence parameters, the underlying prediction algorithm, the graphical displays 1900A and 1900B may be displayed as general range predictions similar to a hurricane projected path visualization, or the graphical displays 1900A and 1900B may be displayed as single or multiple lines. The graphical displays 1900A and 1900B may be modified according to process 1310 as described above based on flags in the SRDS corresponding to parameters associated with the certainty or confidence of the prediction. Modifications may include fading out prediction ranges where one or more confidence parameters fall. The graphical display of the predictions may visually convey the relationship between the user's actions and their potential effect on the analyte data, thereby reducing the patient's stress when making treatment decisions.

[0257] In another implementation, the predicted bolus calculator may be used to visually inform the user of the effect of administration of a bolus on the future trend of the analyte value at the receptor. FIG. 20 may include modified graphical displays 2002, 2004, and 2006, where a recommended (or intended) bolus amount is represented by graphical display 2008. Graphic display 2010 may illustrate a current value of the analyte data and an indication of the future trend of the analyte data. Through user interaction with graphical display 2008 or by an initiating action of the system 302, graphical displays 2008 and 2010 may interact. Graphic display 2010 may be modified based on the effect of the recommended (or intended) amount of the bolus on the future trend of the analyte value at the receptor. After modification, graphical display 2012 may illustrate the predicted trend of the analyte value resulting from administration of the recommended (or intended) bolus. In graphical representation 2006, graphical representations 2014 and 2016 may be restored to their previous shapes 2008 and 2010, respectively.

[0258] FIG. 21 illustrates a modified graphical display 2100 according to an embodiment in which a scrollable list of user behavior data and trends of future analyte values ​​are illustrated. In some implementations, the user may be provided with a graphical interface module including a button 2102 to allow the user to add events (e.g., actions taken by the user, including meals, boluses, exercise, stress, etc.). The system 302 may generate a modified graphical display to display a scrollable list view of entered events (e.g., meal event 2104 or meal + exercise event 2106) for the current time or recent time frame, and one or more snapshots of analyte trend values ​​2108 and 2110 for a period after the event time. The user may visualize the causal relationship between his / her behavior (entered events) and his / her analyte levels. The user's clinical team may recognize the patterns and react accordingly to better manage the user's health. Optionally, in some implementations, an algorithm may be used to infer or automatically suggest and / or link multiple events according to patterns in the analyte data to determine one or more trends in the future analyte data.

[0259] FIG. 22 illustrates a modified graphical display illustrating relationships between multiple complex variables in a simplified display 2200. Diabetic patients often must consider multiple complex variables and consider those relationships when making decisions about their diabetes management. The modified graphical display 2200 simplifies the mental processes associated with analyzing multiple complex variables that inform the diabetic patient's decision making. In some implementations, the current analyte value may be compared to high and low analyte thresholds to generate an analyte score. The amount of remaining insulin may be compared to high and low remaining insulin thresholds to generate an IOB score. An insulin status score may be generated by multiplying the analyte score and the IOB score. In some implementations, other diabetes parameters may be analyzed and a score for each may be determined. The scores may become part of the insulin status score as additional multipliers. These diabetes parameter scores may include, for example, analyte propensity scores, GPS location-based scores (e.g., bars or restaurants or physical locations where historical data may indicate the impact of location on analyte values), food-related scores, physical activity scores, and others.

[0260] The insulin status scores may be ranked and classified based on the ranked scores. In some implementations, the three categories of insulin status scores may simply be good (indicating that the patient is in good condition as far as the diabetic parameters are concerned), caution (indicating that the patient should proceed with caution, continue to monitor the diabetic parameters, and make appropriate decisions), and poor (indicating that corrective action may be required to improve the situation). The display visual representation 2200 may include a visual representation behavior similar to a traffic light, including three circles 2202, 2204, and 2206. Each circle may be filled with a different color, shade, or gradient than the other circles. Depending on the ranked insulin scores, one of the shades in the traffic light 2200 may be illustrated to be more prominent, similar to the behavior of a traffic light. For example, the shade within the circle 2206 in the traffic light 2200 may indicate good conditions, the shade within the circle 2204 in the traffic light 2200 may indicate caution, and the shade within the circle 2202 in the traffic light 2200 may indicate poor conditions.

[0261] In some implementations, the look-ahead module allows a user to selectively increase or decrease data related to the current amount or type of insulin, exercise (intensity, type, etc.), food intake (composition, amount, etc.), stress, or other parameters that affect a diabetic patient's health management and glucose values. For example, a user may use a sliding motion on a touch screen or otherwise indicate an increase or decrease in an entered current or future event, activity, or glucose-related parameter and see the projected effect on a glucose trend graph in real time. The predicted effect may be generated using a model based on a population of patients and their glucose-related data and / or may be based on machine learning over time for a particular user. The look-ahead module helps a user make better diabetes-related decisions by observing predictions based on the cumulative effect of a combination of factors on glucose values. For example, a patient may observe a current glucose value of 100 mg / dL and contemplate eating a snack, going for a run, or taking a small dose of insulin. The look-ahead module will allow the user to play around with snack size / content, exercise type, duration or intensity, and insulin dose type and size to find the desired combination for proper glucose control. The look-ahead module can work in conjunction with other devices. For example, Time Travel on the Apple Watch can trigger a prediction.

[0262] 23 illustrates an example of a modified graphical display 2300 that efficiently provides information about a user's diabetes-related data. FIG 23 illustrates a glucose trend display 2302 in which deviations other than the high and low thresholds 2304 and 2306 are visually differentiated by using one or more shaded regions 2310 and 2312 under the analyte trend curve 2308. If different shading and colors are used, the different colors may be used to differentiate deviations above the high threshold 2304 from deviations below the low threshold 2306.

[0263] In some implementations, instead of or in addition to a trend graph of the analyte value 2308, a simpler graphical representation of the current and future analyte values ​​2314 may be illustrated. For example, a numerical display of the current analyte value 2316 and a graphic 2318 of a prediction of the future trend in the analyte value may be illustrated. In some implementations, the graphic 2314 may be in the shape of a teardrop. The graphic showing the prediction may be a triangle 2318. The direction or orientation that the triangle 2318 is pointing may correspond to the prediction of the future analyte value. For example, a triangle 2318 pointing sharply in an upward direction may indicate a prediction of an imminent rise in the concentration of the analyte. A triangle 2318 pointing moderately in an upward direction may indicate a prediction of a moderate rise in the concentration of the analyte. A triangle 2318 pointing horizontally may indicate a prediction of no significant change in the concentration of the analyte. A triangle 2318 pointing moderately downward may indicate a prediction of a moderate drop in the concentration of the analyte. The triangle 2318 pointing sharply downward may indicate a prediction of a significant or significant drop in the concentration of the analyte. The same or similar correlation between the orientation of the triangle 2318 and the prediction of the concentration of the analyte may also be envisioned by one of skill in the art.

[0264] The analyte trend display 2304 may convey analyte concentration values ​​over a 24 hour period or other time interval selected by the user or automatically selected by the system 302. A line graph of the magnitude of the analyte concentration values ​​versus time may be utilized to generate the analyte trend graph 2320. The trend graph 2320 may be illustrated in relation to a high threshold 2321 and a low threshold 2322. Deviations above the high threshold 2321 may be illustrated by shading the area under the curve between the trend graph 2320 and the high threshold line 2321. In the display 2304, examples of above threshold shading of the area under the curve include areas 2324 and 2326. Deviations below the low threshold line 2322 may be illustrated by shading the area under the curve between the trend graph 2320 and the low threshold line 2322. In the display 2304, examples of below threshold shading of the area under the curve include areas 2328 and 2330.

[0265] Interactive UI display Some graphical displays illustrating glucose, insulin, or diabetes-related data can be overly cluttered with scientific looking graphics and displays. The techniques of the present invention contemplate modified graphical displays that are friendly, uncluttered, and easy to understand.

[0266] FIG. 24A illustrates a modified graphical display in which a collapsible design layout is utilized when a user desires to see more detail. A user may display one or more modified graphical displays one at a time or multiple times as desired. For example, modified graphical display 2402 illustrates a three-hour analyte trend graph 2410 in a zoomed-in view and IOB data 2412 in a zoomed-out view. A user may click or touch the zoomed-out IOB view 2412 to obtain an expanded IOB view 2414 in modified display 2404. A user may click or touch the expanded analyte trend graph 2410 to obtain a zoomed-out view 2416 in modified display 2406 or a zoomed-out view 2420 in modified display 2408. Some illustrations of data may cycle through various display forms to illustrate the same data in multiple easy-to-understand formats. For example, a user may click on the expanded IOB view 2414 to obtain a different graphical representation 2418 of the IOB data as shown in modified graphical display 2408. A subsequent user click or touch may cause IOB view 2418 to collapse back to IOB view 2412, as shown in modified display 2402.

[0267] 24B and 24C illustrate display screens presenting graphics that may be generated and modified by embodiments of the disclosed methods and systems. In the example shown in FIG. 24B, display screens 2422, 2424, 2426, and 2428 include exemplary graphical displays presenting current glucose 2430, glucose trend graph 2434, or remaining insulin 2432 information among other health-related information. The features of display 2422 allow for user interaction to receive user input (e.g., through touching certain graphical features of the display) and generate additional information based on the feature selected. For example, if a user were to select IOB feature 2432, display 2422 can be modified to generate display 2428, which would present an enhanced view of the IOB data (e.g., formatted differently in some implementations and / or enlarged in some implementations) including explanatory information about what remaining insulin is and what it means, e.g., within the context of the user's current glucose information. In the example shown in FIG. 24C, a display screen including a graphical representation may be operational via a software application icon (eg, icon 2436) and / or an event or notification display screen 2438 of an operating system of the mobile computing device.

[0268] The modified graphic display of the present technology may utilize animation to better communicate information. In some implementations, various animations, including pulsating and blinking, may be used in combination with the graphic display as described above. FIG. 25 illustrates a modified graphic display that may use animation to communicate health-related information. Pulsating or blinking at various rates and speeds may be used to communicate different information. For example, pulsating in a heartbeat pattern may indicate that the modified graphic display illustrates live data. By utilizing such animations, the graphic display may be presented in a more dynamic, lifelike, and human-like light, thereby eliminating or reducing the possibility of user error due to misinterpretation of the graphic display. In some implementations, the arrows in the modified graphic display including the magic glass 2502 (the numerical value of the current glucose concentration value at the center of the circle with a small arrow within the circumference of the circle pointing to the future trend of the glucose value) may pulse at different rates to indicate information. For example, pulsating at a high rate may indicate urgency. In some implementations, various points on the glucose trend graphs 2504, 2506, and 2508 may pulse at different rates to indicate additional information. For example, the latest point 2510 on the trend graph 2504 may pulse to indicate the current value. The pulsation may be different at different times, e.g., pulsating at a slower rate at night while the user is sleeping. The graphical display may also be modified with animation to reassure the user that the system is running and the monitoring is up to date. Alternatively, a lack of animation may indicate to the user that the system is offline or the data illustrated may be out of date.

[0269] If the modified graphical display includes personalized customizations from the user, the user is more likely to interact with the modified graphical display with interest and attention. FIG. 26 illustrates modified graphical displays 2602, 2604, 2606, and 2608 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 user-selected theme. The background in display 2602 is customized with a Star Wars® theme background. The background in display 2604 is customized with a nature, religious, or motivational theme. The background in display 2606 is modified to reflect or support studying for the SAT exam. The background in display 2608 is customized to reflect a retro look and feel. The SRDS may be generated with the customized background image or other user customizations. Once one or more of the graphical displays as described above are modified, the customized background image or the user's selected theme may be incorporated into the modified graphical display and presented to the user.

[0270] Various graphical user input interfaces may be used to improve the user's ability to input data into the system. In some implementations, a graphic 2702 showing a numeric keypad may be used. FIG. 27 illustrates a modified graphical display that allows a user to input numeric data into the system 302 using a scroll wheel 2704 and by gestures interacting with the scroll wheel 2704. The scroll wheel 2704 may be programmed to cycle through only the allowable numeric range. Moving the finger in a clockwise direction 2706 on the scroll wheel 2704 may increase the entered numeric value, and moving the finger in a counterclockwise direction 2708 on the scroll wheel 2704 may decrease the entered numeric value.

[0271] In a home where multiple analyte sensor systems 308 or displays 310 are present, the user needs to be able to identify their respective devices. Some diabetes monitoring and management systems currently in use do not provide visual representational assistance other than requiring the home to use different colored cases to distinguish between different units. The technology of the present invention may enable modified graphic displays where an indication of the source of collected analyte, glucose, or insulin data may be generated and flagged in the appropriate SRDS, and then incorporated as part of one or more of the modified graphic displays described above and presented to the correct user. FIG. 28 illustrates an exemplary modified display that incorporates the user's initials into the display to identify the source of the analyte data.

[0272] In some implementations, 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 unique identifiable mark, such as initials, screen background, color theme, screen saver, animation, or a combination of the above. The user's selection may be displayed as part of the modified graphic display as described above. If an initial is selected, for example, initial 2804 in modified display 2802 of FIG. 28, the initial 2804 may be displayed in a corner of screen 2802 or in status bar 2806 of modified display 2808. If the screen is not displaying the modified graphic display, a screen saver may be applied. The selected theme may be applied to the entity's font, background, etc., when flagged in the SRDS to generate the modified graphic display as described above. The selected animation may also be flagged and referenced in the SRDS to be displayed when generating the modified graphic display as described above.

[0273] Other example graphic displays generated from SRDS FIG. 29 illustrates a modified graphical display 2900 according to an embodiment in which the graphical display 2900 may be automatically modified when a user's health condition is predicted to approach an undesirable condition. In the context of diabetes management, for example, a CGM reading from a user may indicate that the user is approaching a hyperglycemic or hypoglycemic condition for which an alert may be generated. An undesirable health condition, such as hyperglycemia or hypoglycemia, may be detected when the magnitude of the analyte concentration value exceeds a hyperglycemic value threshold or falls below a hypoglycemic value threshold. When the analyte concentration value exceeds a high threshold or falls below a low threshold, an alarm condition may be triggered. The high and low thresholds that may generate an alarm condition may be user-defined, defined by a member of the patient's support team, or automatically defined by the system 302 based on the user's data, profile, habits, past glucose trend values, or other parameters associated with diabetes management. The graphical display 2900 may be initially generated to convey diabetes health management data such as a magic glass 2902 and a glucose trend graph 2904 associated with predefined or default high and low threshold lines 2908 and 2906. In some cases, predefined alarm thresholds may take too long to notify the user. For example, predefined alarm thresholds may be based on the user's health data that is out of date or no longer applicable. In such cases, the user may potentially approach a severe condition and experience adverse health consequences before the user is notified. To encourage the user to take immediate corrective action, it may be desirable to automatically modify the associated thresholds linked to the alarm condition and generate one or more alarms accordingly. In some embodiments, the system 302 may determine the rate at which the concentration of the analyte value is approaching a high or low threshold and determine the time at which the analyte concentration value may reach the threshold. If the determined time is less than or equal to the predetermined safe time, the system 302 may automatically modify the threshold value linked to the alarm state from the user's previously set value to the current analyte value to immediately trigger the alarm state, notify the user, and prompt for corrective action.

[0274] For example, a hypoglycemia alarm condition may be pre-set to trigger an alarm when 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 to illustrate the analyte trend graph 2904 and low threshold line 2906, as well as other relevant diabetes management data such as a magic glass 2902. The blood glucose readings and other data obtained regarding the user's condition may enable the system 302 to predict that a correction of a previously set alarm condition is desirable. For example, the user analyte measurement and event data may suggest 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 may reach the 70 mg / dL alarm level in approximately 20 minutes. In some cases, it may be undesirable or unsafe to postpone corrective action for 20 minutes. For example, a safe time of 20 minutes or more may be required to effectively take corrective action and realize results before the analyte concentration value reaches an unhealthy range. If the system 302 determines that the user will reach the threshold in less than the safe time, it may override the existing threshold linked to the alarm state, trigger the alarm state, and notify the user immediately. The system 302 may modify the graphical display 2900 as described above to raise the low threshold level 2906 to a new low threshold level 2910, which corresponds to a current blood glucose level of 110 mg / dL. An alarm is immediately generated and the user is notified. The user may take corrective action to avoid a serious condition.

[0275] Modifications to the graphical display 2900 and threshold 2906 may be accompanied by an audio alarm and a visual cue to draw attention and inform the user of the changes made. For example, the low threshold line 2906 may move upward to its new position 2910, and the movement of the threshold line may be accompanied by an audio alarm and a flashing or sweeping motion of the line 2906 to its new position 2910. An arrow 2912 points in the direction of the movement and may flash, pulsate, or otherwise call attention to the change.

[0276] FIG. 30 illustrates modified graphical displays 3002, 3004, 3006, 3008, and 3010 generated from a data structure and an array of data according to an embodiment in which the graphical displays 3002, 3004, 3006, 3008, and 3010 include visual representations showing ranges of the analyte data. The system 302 can define various ranges of concentrations of the analyte data automatically by default or via user input. For example, a target range of analyte concentrations can be defined as when the analyte concentration value is a value between a desired high threshold and a low threshold. A caution range can be defined as when the analyte concentration value is a value between a desired high threshold and a low threshold, but is close to one of these thresholds such that the analyte concentration value may briefly exceed the desired high threshold or fall below the desired low threshold. An outside of the target range can be defined as when the concentration of the analyte value exceeds the high threshold or falls below the low threshold. The high and low thresholds used to determine the range of the analyte data can be edited based on other users' anonymous data and / or analyte data similarly placed on the user. The target ranges, caution ranges, and out-of-target ranges may be user defined or automatically defined by the system 302 based on guidelines from a medical institution or authority. For example, the target ranges may be defined from American Diabetes Association (ADA) guidelines as fasting glucose levels below 100 mg / dL and 2-hour post-prandial glucose levels below 140 mg / dL. In some implementations, analyte concentration values ​​that exceed 20% of the ADA guidelines may be considered to be within the caution range. For example, analyte concentration values ​​below 80 mg / dL while fasting are considered to be within the target range, analyte concentration values ​​between 80 mg / dL and 100 mg / dL while fasting are considered to be within the caution range, and analyte concentration values ​​above 100 mg / dL are considered to be outside the target range.

[0277] The graphical displays 3002, 3004, 3006, 3008, and 3010 illustrate the magnitude of the analyte data on the vertical axis and time on the horizontal axis. When generating the graphical displays 3002, 3004, 3006, 3008, and 3010, various visual representation techniques can be used to modify the analyte data to indicate the range of the analyte data. The graphical display 3002 illustrates a modified graphical display of a graph of the magnitude of the analyte concentration value versus time, where the graphic is modified to illustrate the range of the analyte data with varying contrast or line style. In other implementations, color coding may be used to distinguish target ranges, caution ranges, and out of target ranges. The self-referencing dataset generating the display 3002 may be modified if the analyte data is flagged with an indication of its range (e.g., target range, caution range, and out of target range). When generating the graphical display 3002, each flag may be given a line style, contrast, thickness, or other distinguishable visual indicator based on which subsequent pixels may be generated on the display 3002. In the exemplary embodiment 3002, analyte data within a target range may be flagged and indicated with a line style 3012. Analyte data within a caution range may be flagged and their corresponding flags may be associated with a line style 3014. Analyte values ​​outside of a target range may be flagged and their corresponding flags may be assigned a line style 3016. Other visual indicators such as color, gradient, other line styles, or animation may be used as described. Visual indicators associated with caution ranges or outside of a target range may be selected to quickly grab attention and capture the information being conveyed. For example, a darker contrast line 3016 may be used to indicate analyte values ​​outside of a target range.

[0278] Graphical display 3004 is similar to graphical display 3002. Analyte data within the target range may be further displayed via a rectangle 3018 surrounding the target analyte value. Analyte values ​​within the attention range may be highlighted with the area under the curve shaded in a style 3020. Analyte values ​​outside the target range may be highlighted with the area under the curve shaded in a style 3022 that is different from style 3020 to provide a visual difference and attract the user's attention.

[0279] Graphical display 3006 is similar to graphical display 3004. Analyte values ​​within the target ranges have been subtracted and are not shown to highlight analyte values ​​within the caution ranges and outside the target ranges that may pose health concerns and require attention and corrective action. Graphical display 3006 allows the user to see analyte values ​​within the caution ranges 3024 and analyte values ​​outside the target ranges 3026.

[0280] The graphical displays 3008 and 3010 use adaptive target region techniques whereby the graphical display is modified to account for variations in analyte data that are expected to occur with or without diabetes. For example, a non-diabetic person may experience a peak in blood glucose levels following consumption of a meal, just like a diabetic. For example, the graphical display 3008 may be modified to adjust the attention region 3028 based on event data obtained from the user and / or the sensor. Such adjustments may be desirable to avoid unnecessarily alarming the user. For example, when a meal event is detected, an increase in the user's blood glucose level may be expected and normal. The attention range 3028 within the associated time frame may be adjusted to account for the expected increase in blood glucose level, for example, by shading the area under the curve within the attention region 3028 with the same shading used within the target analyte value. Graphical display 3010 uses the same adaptive target region technique as described in connection with display 3008, however, analyte values ​​within the target range have been subtracted and are not shown to further highlight and draw attention to analyte values ​​within attention range 3030 and analyte values ​​outside target range 3032.

[0281] 31 illustrates modified graphical displays generated from the data structures and arrays of data according to one embodiment, where the graphical displays 3102, 3104, 3106, 3108, 3110, and 3112 include visual representations showing the status of the analyte monitoring system, the health status of the user, trends, alarms, or other data related to the health of the user. The illustrated graphical displays may use, for example, an inverted or dark background 3114 to enhance contrast and improve readability. An updated current analyte value reading 3116 may be displayed by displaying a number, such as 100 mg / dL. An analyte trend indicator 3118 may be displayed nested next to the updated current glucose 3116. The analyte trend indicator 3118 includes an arrow 3117 surrounded by a circle 3122 where the direction of the arrow 3117 indicates the future trend of the analyte data. The circle 3122 surrounding the arrow 3117 may be filled with an appropriate shading style to indicate a trend or direction of the future analyte value and / or to provide contrast with the background 3114 to improve readability. In some embodiments, the trend indicator 3118 includes a faded ring 3119 surrounding the circle 3122. A text description 3120 of the state and / or trend of the analyte data value may be displayed near or above the current value of the analyte data 3116 (e.g., "In Range and Steady"). The display 3102 may include an analyte graph 3124, where the magnitude of the analyte concentration value is illustrated on the vertical axis versus time on the horizontal axis. A dot 3126 may indicate the current analyte value on the analyte graph 3124. The dot 3126 is surrounded by a faded ring, which in some embodiments may pulsate at the same rate and may be rendered in the same style as the faded ring 3119 of the analyte indicator 3118. The analyte graph 3124 also illustrates an upper threshold line 3128 that corresponds to an upper range of desired analyte concentration values. The graphic 3124 also illustrates a lower threshold line 3130 that corresponds to a lower range of desired analyte concentration values.

[0282] The display 3104 is similar to the display 3102. The user's current blood glucose value 3116 has reached 200 mg / dL, which is the upper range of the desired analyte concentration value. The trend indicator 3118 has been updated to indicate the current trend and characteristic trends of the analyte concentration values. The arrow 3117 has been updated to point appropriately upward. The circle 3122 has been updated and filled with a shading style 3132 that is different from the shading style of the circle 3122 to draw attention to the current high analyte concentration value. The text description 3120 has also been updated with appropriate text to indicate that the analyte concentration value is high and rising. The high threshold line 3128 has been updated and rendered with a different style 3134 than the line style 3128 to draw attention to the current high value of the analyte concentration. In some embodiments, the different style of the line 3134 may include rendering the line in a larger and higher contrast style to draw the user's attention. The dot 3126 is updated and rendered in a style 3136 different from the style used to generate the dot 3126 to draw additional attention to the high analyte concentration values. The dot 3136 and the circle 3132 may be rendered in the same style and the faded ring surrounding them may pulsate at the same rate to draw attention to the high analyte concentration values. In some embodiments, the high threshold line 3134 may pulsate at the same rate as the dot 3136, the circle 3132, or the faded ring surrounding them.

[0283] The display 3106 is similar to the display 3102. The user's current blood glucose value 3116 has fallen to 54 mg / dL, which is the lower limit of the desired analyte concentration value. The trend indicator 3118 has been updated to indicate the current and future trends in the analyte concentration value. The arrow 3117 has been updated to change shape and point dramatically downward. The circle 3122 has been updated and filled with a shading style 3138 that is different from the shading style of the circle 3122 to draw attention to the current analyte concentration value. The text description 3120 has also been updated with appropriate text indicating that the analyte concentration value is low and continues to fall quickly. The low threshold line 3130 has been updated and rendered with a style 3140 that is different from the line style 3130 to draw attention to the low current value of the analyte concentration. In some embodiments, the different style of the line 3140 may include rendering the line larger and in a high contrast style to draw attention. The dot 3126 is updated and rendered in a different style 3142 than the style used to generate the dot 3126 to draw more attention to the low analyte concentration values. The dot 3142 and circle 3138 may be rendered in the same style and the faded ring surrounding them may pulsate at the same rate to draw attention to the low analyte concentration values. In some embodiments, the low threshold line 3140 may pulsate at the same rate as the dot 3142, circle 3138, or faded ring surrounding them.

[0284] The user data, numerical values, thresholds, graphs, and future projections described above in connection with the display of FIG. 31 are exemplary, and other user data may trigger different displays, text, graphs, and / or thresholds without departing from the spirit of the described technology.

[0285] As described above, an analyte graph 3124 of the analyte data value may be displayed where the magnitude of the analyte value is plotted over a period of time. The current value of the analyte data may be indicated by a pulsating graphic 3126, for example a graphic including one or two concentric circles fading radially in a stepwise fashion. The analyte graph 3124 and the data structures generating the analyte graph 3124 may be dynamically updated based on the current analyte sensor data. The displays 3102, 3104, 3106, or data structures generating similar displays, may be modified to display one or more pulsating animations that may pulsate in sync to further draw a user's attention to information related to health care. Examples of display elements that may be modified or rendered with pulsating animations include the trend indicator 3118, the current analyte value dot 3126, and the threshold lines 3128 and 3130.

[0286] Other status information associated with the operation of the analyte monitoring system may be communicated via the modified graphical displays 3108, 3110, and 3112. For example, the modified graphical display 3108 may indicate via text 3144 and 3146 that the analyte sensor is warming up and how much time may remain before the sensor is ready. A status bar 3148 may also provide a visual representation of the status of the sensor. The graphical displays 3110 and 3112 are modified graphical displays that report the status of the system 302. For example, the graphical display 3110 illustrates a situation in which a loss of signal from the glucose sensor is encountered. The loss of signal may be indicated via text and graphical display elements 3150. The analyte graph 3124 no longer displays the current analyte value dot 3126. Other information, such as the current analyte concentration 3116 and the analyte trend indicator 3118, are also not displayed. Text, graphical displays, icons, and symbols 3150 are utilized to indicate the signal loss and alert the user. In the graphical display 3112, no sensor is detected and text, graphical symbols, and / or icons 3152 are used to indicate the absence of an analyte sensor and to prompt the user to connect an analyte sensor.

[0287] For ease of explanation and illustration, in some instances, the detailed description describes the exemplary systems and methods in terms of a continuous glucose monitoring environment, but it should be understood that the scope of the invention is not limited to that particular environment, and those skilled in the art will appreciate that the systems and methods described herein may be embodied in a variety of forms. Accordingly, any structural and / or functional details disclosed herein should not be construed as limiting the systems and methods, but rather are provided as attributes of representative embodiments and / or arrangements to teach those skilled in the art one or more ways to implement the systems and methods that may be advantageous in other contexts.

[0288] For example, but not limited to, the described monitoring systems and methods may include sensors that measure concentrations of one or more analytes (e.g., glucose, lactate, potassium, pH, cholesterol, isoprene, and / or hemoglobin) and / or receptors and / or other blood or bodily fluids of or associated with another party.

[0289] By way of example, and not limitation, embodiments of the monitoring systems and methods described herein may include finger stick blood sampling, blood specimen test strips, non-invasive sensors, wearable monitors (e.g., smart bracelets, smart watches, smart rings, smart necklaces or pendants, movement monitors, fitness monitors, health and / or medical monitors, clip-on monitors, etc.), adhesive monitors, smart textiles and / or clothing integrated sensors, shoe inserts and / or insoles containing sensors, transdermal (i.e., transcutaneous) sensors, and / or swallowed, inhaled, or implantable sensors.

[0290] In some embodiments, the monitoring systems and methods may include other sensors instead of or in addition to the sensors described herein, such as, without limitation, inertial measurement units including accelerometers, gyroscopes, magnetometers, and / or barometers; motion, altitude, position, and / or location sensors; biometric sensors; optical sensors including, for example, optical heart rate monitors, photoplethysmogram (PPG) / pulse oximeters, fluorescence monitors, and cameras; wearable electrodes; electrocardiogram (EKG or ECG), electroencephalography (EEG), and / or electromyography (EMG) sensors; chemical sensors; flexible sensors for measuring, for example, stretch, displacement, pressure, weight, or impact; galvanometric sensors, capacitive sensors, electrolytic sensors, temperature / heat sensors, microphones, vibration sensors, ultrasonic sensors, piezoelectric / piezoresistive sensors, and / or transducers for measuring information of or related to receptors and / or other parties.

[0291] As used herein, the terms "computer program medium" and "computer usable medium" and "computer readable medium", as well as variations thereof, generally refer to a transitory or non-transitory medium, such as, for example, a main memory, a storage unit interface, a removable storage medium, and / or a channel. These and other various forms of computer program medium or computer usable / readable medium may be involved in carrying one or more sequences of one or more instructions to a processing device for execution. Such instructions embodied on the medium may generally be referred to as "computer program code" or "computer program product" or "instructions" (which may be grouped in the form of a computer program or other groupings). When executed, such instructions may enable a computing module or its processor or a processor connected thereto to perform the features or functions of the present disclosure as discussed herein.

[0292] Various embodiments have been described with reference to certain exemplary features thereof. It will be apparent, however, that various modifications and changes may be made thereto without departing from the broader spirit and scope of the various embodiments as set forth in the appended claims. The specification and figures are, therefore, to be regarded in an illustrative rather than a restrictive sense.

[0293] Although described above in terms of various exemplary embodiments and implementations, it should be understood that the various features, aspects, and functions described in one or more of the individual embodiments are not limited in their applicability to the particular embodiment for which they are described, but instead may be applied, alone or in various combinations, to one or more of the other embodiments of the present application, regardless of whether such an embodiment is described and whether such features are presented as being part of the described embodiment. Thus, the breadth and scope of the present application should not be limited by any of the exemplary embodiments described above.

[0294] Terms and phrases used in this application, and variations thereof, unless otherwise specified, should be interpreted liberally and not limiting. As examples of the foregoing, the term "including" should be read to mean "including but not limited to" and the like; the term "example" is used to provide illustrative examples of the items under discussion, not an exhaustive or limiting list thereof; the term "one" or "one" should be read to mean "at least one," "one or more," and the like; and adjectives such as "conventional," "conventional," "usual," "standard," "known," and the like, and terms of similar meaning, should not be interpreted to limit the items described to those available in a given period or for a given time, but instead should be read to encompass conventional, conventional, ordinary, or standard technology that may be available or known at any time now or in the future. Similarly, when the specification refers to technology that is apparent or known to one of ordinary skill in the art, such technology encompasses technology that is apparent or known to one of ordinary skill in the art at any time now or in the future.

[0295] The presence of broad words and phrases such as "one or more," "at least," "without limitation," or other similar phrases in some instances shall not be read to imply that a narrower case is intended and required in instances where such broad phrases may not be present. Use of the term "module" does not imply that components or functionality described or claimed as part of a module are all configured in a common package. Indeed, any or all of the various components of a module, whether control logic or other components, may be combined in a single package or maintained separately, and may even be distributed across multiple groups or packages, or at multiple locations.

[0296] Moreover, the various embodiments described herein are described in terms of exemplary block diagrams, flow charts, and other illustrations. As will become apparent to one of ordinary skill in the art after reading this specification, the illustrated embodiments and various alternatives thereof may be implemented without being limited to the illustrated examples. For example, the block diagrams and their accompanying description should not be construed as requiring a particular architecture or configuration. [Explanation of symbols]

[0297] 8 Analyte Sensor System 10 Analyte Sensor 12 Sensor Electronics Module 100 Systems 110 Sample display device 120 Mobile Phones 130 tablets 140 Smart Clock 112, 122, 132, 142 Touch Screen Displays 134 Server System 136 Medical Devices 138 Wireless Access Points 200 units 208 Adhesive Pad 214 Mounting unit 234 Base 236 Contact Sub-Assembly 238 Contact 248 Hinge 300 Systems 302 System 305 Communication media 308 Analyte Sensor System 310 Display Device 315, 355 connection interface 320, 360 Transmitter / Receiver 325, 365 storage device 330 Analyte Sensor Applications 334 Server System 334a Server 334b Storage device 334c processor 335, 380 Processors / Microprocessors 340 Graphic User Interface 345 Display 350, 385 Real Time Clock 370 Sensor measurement circuit 375 Sensors

Claims

1. 1. A system comprising: a continuous analyte sensor configured to obtain glucose data of a receptor; and 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 configured to receive insulin data of the receptor, the glucose data of the receptor, and event data of the receptor, and generate a graphical display on a mobile computing device, the insulin data including a residual insulin value; the processing module is further configured to modify the graphical display to display a visual representation showing one or more relationships of the insulin data, the glucose data, and the event data with respect to one another or with respect to time, the display of the insulin data, glucose data, or event data being zoomed in or out in response to a user interaction; The system wherein the visual representation includes a trend graph of the glucose data and an interactive callout window associated with an area or feature of the trend graph that is presented when a user selects a point on the trend graph on the graphical display, the presented callout window including the remaining insulin value.

2. The system of claim 1 , wherein the event data includes one or more of insulin administration, carbohydrate intake, or exercise.

3. The system of claim 1 , wherein the visual representation includes a colored ring indicating the remaining insulin and an estimated time remaining for the remaining insulin.

4. 2. The system of claim 1, wherein the presented callout 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 to administer bolus insulin, a time to administer basal insulin, or a value of remaining insulin.

5. 2. The system of claim 1, wherein the presented callout window is configured to display a graphical arrangement of the event data including one or more of carbohydrate intake, amount of time spent exercising, amount of calories burned, or heart rate reaching a threshold or time associated therewith.

6. 2. The system of claim 1, wherein the visual representation includes an arrow corresponding to insulin data and a glucose reading including a glucose trend corresponding to glucose data, the arrow being displayed adjacent to a trend graph and modified to show the effect of insulin data on the glucose data.

7. 2. The system of claim 1, wherein the trend graph includes past glucose data and future glucose data, the future glucose data being determined based on insulin data and performance data of the receptor.

8. The visual representation comprises: a first graphical display configured to illustrate a current value of the glucose data and an indication of a future trend of the glucose data; 2. The system of claim 1, further comprising: a second graphical display configured to represent an amount of insulin, the second graphical display further configured to interact with the first graphical display to illustrate a possible effect of the amount of insulin on the indication of the future trend of the glucose data.

9. 2. The system of claim 1, wherein the area between the trend graph and a high glucose threshold is a first color and the area between the trend graph and a low threshold is a second color.

10. 1. A system comprising: a continuous analyte sensor configured to obtain glucose data of a receptor; 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 configured to receive the insulin data of the receptor, the glucose data of the receptor, and the event data of the receptor, and generate a graphical display on a mobile computing device; the processing module is further configured to modify the graphical display to display a visual representation showing one or more relationships of the insulin data, the glucose data, and the event data with respect to one another or with respect to time, the display of the insulin data, glucose data, or event data being zoomed in or out in response to a user interaction; The processing module comprises: and further configured to generate one or more data sets each based on the receptor's behavior and a prediction of a glucose data trend based on the receptor's behavior; The system, wherein the visual representation comprises a scrollable list including one or more modified graphs each based on the one or more datasets.

11. 1. A system comprising: a continuous analyte sensor configured to obtain glucose data of a receptor; 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 configured to receive the insulin data of the receptor, the glucose data of the receptor, and the event data of the receptor, and generate a graphical display on a mobile computing device; the processing module is further configured to modify the graphical display to display a visual representation showing one or more relationships of the insulin data, the glucose data, and the event data with respect to one another or with respect to time, the display of the insulin data, glucose data, or event data being zoomed in or out in response to a user interaction; The processing module comprises: comparing the current glucose value to a high glucose threshold and a low glucose threshold to generate a glucose score; comparing the current remaining insulin to a high insulin threshold and a low insulin threshold to generate a remaining insulin (IOB) score; generating an insulin status by multiplying said glucose score and said IOB score; The system is further configured to rank the IOB score into one of a plurality of categories.

12. The system of claim 11 , wherein the plurality of categories includes good, caution, and bad.

13. 13. The system of claim 12, wherein the visual representation comprises a color-coded display, each of the plurality of categories being associated with a different color, and the color associated with the ranked IOB scores is illustrated.

14. 1. A system comprising: a continuous analyte sensor configured to obtain glucose data of a receptor; 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 configured to receive the insulin data of the receptor, the glucose data of the receptor, and the event data of the receptor, and generate a graphical display on a mobile computing device; the processing module is further configured to modify the graphical display to display a visual representation showing one or more relationships of the insulin data, the glucose data, and the event data with respect to one another or with respect to time, the display of the insulin data, glucose data, or event data being zoomed in or out in response to a user interaction; The system further comprises a look-ahead module configured to receive input data for the receptor associated with future event data, the visual representation including a glucose trend graph, and when the input data is modified the visual representation is modified accordingly.

15. 1. A system comprising: a continuous analyte sensor configured to obtain glucose data of a receptor; 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 configured to receive the insulin data of the receptor, the glucose data of the receptor, and the event data of the receptor, and generate a graphical display on a mobile computing device; the processing module is further configured to modify the graphical display to display a visual representation showing one or more relationships of the insulin data, the glucose data, and the event data with respect to one another or with respect to time, the display of the insulin data, glucose data, or event data being zoomed in or out in response to a user interaction; The system, wherein the processing module is further configured to generate the graphical display by forming one or more datasets 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 datasets to generate a self-referencing dataset, and generating a graphical display within an array that is graphically modified to indicate one or more features in the data.

16. A non-transitory computer-readable medium storing executable program instructions, the instructions, when executed by one or more computing devices, causing the one or more computing devices to: obtaining receptor glucose data with a continuous analyte sensor; receiving and transmitting glucose data of said receptor by a wireless transmitter; receiving, at a processing module, insulin data for the receptor, the glucose data for the receptor, and event data for the receptor, the insulin data including a residual insulin value; the operations generating a graphical display on a mobile computing device; and modifying the graphical display to display a visual representation showing one or more relationships of the insulin data, the glucose data, and the event data with respect to each other or with respect to time, wherein the display of the insulin data, glucose data, or event data is enlarged or reduced in response to user manipulation; A non-transitory computer-readable medium, the operations further including receiving the diabetes-related data of the recipient and generating an interactive graphical display on the mobile computing device, a viewer being able to interact with the interactive graphical display, the interactive graphical display including the remaining insulin value.

17. 17. The non-transitory computer-readable medium of claim 16, wherein the interactive graphical display includes a trend graph of the glucose data with areas between the trend graph and a glucose threshold value having different colors for areas above a high threshold and areas above a low threshold, the high threshold and the low threshold being adjustable by the viewer's interaction with the interactive graphical display.

18. The non-transitory computer-readable medium of claim 16 , wherein the viewer can interact with the interactive graphical representation via a collapsible design layout.

19. 20. The non-transitory computer-readable medium of claim 16, wherein the interactive graphical display further comprises one or more animations to convey information.

20. The non-transitory computer-readable medium of claim 16 , wherein the viewer can interact with the interactive graphical display by selecting a personalized background image.

21. 20. The non-transitory computer-readable medium of claim 16, wherein the viewer can interact with the interactive graphical display by inputting numerical values ​​via a graphical scroll wheel.

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