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

Abstract

An analyte monitoring system, comprising: a continuous analyte sensor configured to measure an analyte concentration of a host; a sensor electronics module configured to: receive a current from the continuous analyte sensor indicative of the analyte concentration; generate analyte data based on the current; transmit the analyte data directly to a first display device using a wireless transmitter; and transmit the analyte data directly to a second display device using the wireless transmitter; wherein the first display device comprises a smart watch; and the second display device comprises a smart phone.

Description

[0001] This application is a divisional application of Chinese Patent Application No. 202210265634.4, filed on March 17, 2022, entitled "System and Method for Health Data Visualization and User Support Tool for Continuous Glucose Monitoring".

[0002] Incorporation of related applications Any and all priority claims listed in the application data sheet or any correction thereof are incorporated herein by reference in accordance with 37 CFR 1.57. This application claims the benefit of U.S. Provisional Application No. 62 / 374,539, filed August 12, 2016. The foregoing application is incorporated herein by reference in its entirety and is expressly formed part of this specification. Technical Field

[0003] This disclosure generally relates to the continuous monitoring of analyte values ​​received from an analyte sensor system. More specifically, this disclosure is directed to systems, methods, apparatus, and devices for generating dynamic data structures and graphical displays. Background Technology

[0004] Diabetes is a condition in which the pancreas cannot produce enough insulin (type 1 or insulin-dependent) and / or the insulin is not effective enough (type 2 or non-insulin-dependent). In diabetes, the patient suffers from hyperglycemia, which causes a host of physiological disturbances associated with the deterioration of small blood vessels (kidney failure, skin ulcers, or vitreous hemorrhage). Hypoglycemia can be induced by unintentional overdose of insulin, or by excessive exercise or insufficient food intake following a normal dose of insulin or a glucose-lowering agent.

[0005] Typically, people with diabetes carry a self-monitoring blood glucose (SMBG) monitor, which usually requires an uncomfortable finger-prick method. Due to this lack of comfort and convenience, people with diabetes will typically only measure their glucose levels two to four times a day. The downside is that these time intervals are so widely spaced that people with diabetes may be warned of high or low blood sugar too late, sometimes leading to dangerous side effects. In fact, due to the limitations of the conventional method, people with diabetes are not only unlikely to obtain SMBG values ​​in a timely manner, but they also won't know whether their blood glucose level is rising (higher) or falling (lower).

[0006] Therefore, various non-invasive, percutaneous (e.g., transdermal), and / or implantable electrochemical sensors are being developed for the continuous detection and / or quantification of blood glucose levels. Continuous glucose monitoring (CGM) devices are gaining popularity as a simple method for monitoring glucose levels. In the past, patients sampled their glucose levels several times throughout the day, for example, in the morning, around noon, and in the evening. These levels were measured by taking a small blood sample from the patient and measuring glucose levels with a test strip or glucometer. However, this technology has drawbacks because patients would prefer not to have a blood sample taken, and users do not know what their glucose levels were between sampling points throughout the day.

[0007] One potentially dangerous time range is at night, as a patient's glucose levels can drop to dangerous levels during sleep. Therefore, continuous glucose monitors have gained popularity by providing sensors that continuously measure a patient's glucose levels and wirelessly transmit the measured glucose levels to a display. This allows the patient or their caregiver to monitor the patient's glucose levels throughout the day and even set alarms when glucose levels reach predefined levels or undergo defined changes.

[0008] Initially, continuous glucose monitors wirelessly transmit glucose level-related data to a dedicated display. This dedicated display is a medical device designed to show users glucose levels, trend patterns, and other information. However, with the increasing prevalence of smartphones and the software applications (apps) running on them, some users prefer to avoid carrying a dedicated display. In fact, some users prefer to monitor their glucose levels using dedicated software applications running on their mobile computing devices, such as smartphones, tablets, or wearable devices like smartwatches or smart glasses. Besides dedicated displays, other users may prefer the flexibility of accessing their glucose and glucose-related data on other mobile or stationary computing devices. Summary of the Invention

[0009] One embodiment includes a system comprising: a continuous analyte sensor configured to acquire analyte measurements of a subject; a wireless transmitter configured to receive the analyte measurements from the continuous analyte sensor and at least partially process the analyte measurements to generate one or more datasets of analyte data, each dataset containing analyte concentration values ​​associated with time for one or more of the analyte measurements, wherein the wireless transmitter includes an energy storage unit, a data converter unit, a processing unit, and a transmitter unit; and an analyte data processing module operable on a mobile computing device wirelessly connected to the wireless transmitter, the analyte data processing module being configured to receive and process the one or more datasets from the wireless transmitter to generate a graphical display on the mobile computing device, wherein the graphical display contains an arrangement of the analyte concentration values ​​over multiple time intervals, the arrangement being graphically modified to indicate one or more patterns in the analyte data.

[0010] In one aspect of the system, the analyte data processing module is further configured to: aggregate groups of analyte data; flag the groups of analyte data based on additional information corresponding to one or more graphical displays; arrange the flagged groups of analyte concentration values; and generate a self-reference dataset from the arranged groups of analyte concentration values.

[0011] In one aspect, generating the self-reference dataset further includes one or more of the following: flagging the analyte data based on one or more high and low thresholds for the analytes in the subject; flagging the analyte data based on performing statistical analysis on the analyte data; and flagging the analyte data based on contextual data related to the time when the analyte data was obtained.

[0012] In one aspect, the contextual data includes: data indicating one or more physical locations where the analyte data is obtained, the relationship between the subject and the physical location, the frequency of access to the physical location, meals, the type and intensity of exercise, the type and amount of insulin administered, and the likelihood that the subject is asleep or awake when the analyte data is obtained.

[0013] In another aspect, the analysis data processing module is further configured to generate a graphical display on the mobile computing device by: receiving user input containing the user's desired graphical display; receiving display configuration data; regenerating the self-reference dataset when the self-reference dataset does not contain data useful for forming the desired graphical display; and reformatting the self-reference dataset based on the user's input and the display configuration data.

[0014] In some aspects, the analyte data processing module is further configured to modify the graphical display by: scanning the self-reference dataset to obtain a threshold flag and modifying the graphical display based on the threshold flag; scanning the self-reference dataset to obtain a statistical analysis flag and modifying the graphical display based on the statistical analysis flag; and scanning the self-reference dataset to obtain an analyte contextual data flag and modifying the graphical display based on the contextual data flag.

[0015] In one aspect, modifying the graphic display includes introducing or using one or more of the following: color, gradient of color or shadow, transparency, opacity, buffer, graphic icon, arrow, animation, text, number, and gradual fading.

[0016] In one aspect, the arrangement includes a spatial-temporal organization of the analyte concentration values, wherein the analyte concentration values ​​are positioned along a first direction according to a first time scale and along a second direction according to a second time scale, and the analyte level of the analyte concentration values ​​is constituted by one or more of shape, color, tinting, or size based on the magnitude of the analyte level.

[0017] In one aspect, the first direction and the second direction are linear directions.

[0018] In another aspect, the first direction is a bending direction and the second direction is a radial direction.

[0019] In some respects, the first time scale is hourly and the second time scale is daily.

[0020] In one aspect, the first time scale is hourly and the second time scale is daily, wherein the graphical modification includes an analyte level trace overlaid on the graphical display such that higher analyte levels are closer to the outer curvature of the graphical display and lower analyte levels are closer to the inner curvature of the graphical display, or vice versa.

[0021] In one aspect, the higher analyte level is represented by a first color, the lower analyte level by a second color, and the analyte level between the higher and lower analyte levels by a third color.

[0022] In one aspect, the analyte level trace includes the average analyte level of the daily analyte concentration values.

[0023] In one aspect, the analyte level trace includes the current analyte level on the hourly timescale.

[0024] In another aspect, the modifications to the graphical display include clustering of display colors, gradients of colors or shadows, alignment of areas, or lighter or darker shadows of overlapping areas, to modify the arrangement of the analyte concentration values ​​over the plurality of time intervals.

[0025] In one aspect, the one or more modes indicate the analyte concentration values ​​relative to high and low analyte level thresholds of the subject.

[0026] In one aspect, the plurality of time intervals comprise a 24-hour cycle within a 7-day period.

[0027] In one aspect, the graph displays an isometric curve plotted over a 24-hour cycle within a 7-day period.

[0028] In one aspect, the isometric graph can be displayed in a three-dimensional view.

[0029] In one aspect, the graphic display includes concentric rings.

[0030] In another aspect, the graphical display includes a sector curve.

[0031] In one aspect, the graphical display includes one or more graphs.

[0032] Another embodiment includes a computer-implemented method comprising: receiving analyte data obtained from a continuous analyte sensor device at a mobile computing device, wherein the analyte data includes analyte concentration values, each associated with a time-varying measurement; processing the analyte data at the mobile computing device to generate an arrangement of the analyte concentration values ​​over a plurality of time intervals; generating a graph of the arrangement of the analyte concentration values; modifying the graph to indicate one or more patterns in the analyte data; and displaying the modified graph at the mobile computing device.

[0033] In some aspects, the processing further includes: aggregating groups of analyte data; flagging the groups of analyte data based on additional information corresponding to one or more graphical displays; arranging the flagged groups of analyte concentration values; and generating a self-reference dataset from the arranged groups of analyte concentration values.

[0034] In one aspect, generating the self-reference dataset further includes one or more of the following: flagging the analyte data based on one or more high and low thresholds for the analyte in the subject; flagging the analyte data based on performing statistical analysis on the analyte data; and flagging the analyte data based on contextual data related to the time when the analyte data was obtained.

[0035] In some aspects, contextual data may include: data indicating one or more physical locations where the analyte data is obtained, the relationship between the subject and the physical location, the frequency of access to the physical location, meals, the type and intensity of exercise, the type and amount of insulin administered, and the likelihood that the subject is asleep or awake when the analyte data is obtained.

[0036] In another aspect, the graphical representation of the arrangement that generates the analyte concentration values ​​further includes: receiving user input containing the user's desired graphical display; receiving display configuration data; regenerating the self-reference dataset when the self-reference dataset does not contain data useful for forming the desired graphical display; and reformatting the self-reference dataset based on the user's input and the display configuration data.

[0037] In another aspect, modifying the graph to indicate one or more patterns in the analyte data may include: scanning the self-reference dataset to obtain a threshold flag and modifying the graph based on the threshold flag; scanning the self-reference dataset to obtain a statistical analysis flag and modifying the graph based on the statistical analysis flag; and scanning the self-reference dataset to obtain an analyte contextual data flag and modifying the graph based on the contextual data flag.

[0038] In one aspect, modifying the graphic includes introducing or using one or more of the following: color, gradient of color or shadow, transparency, opacity, buffer, graphic icon, arrow, animation, text, number, and gradual fading.

[0039] In one aspect, the arrangement includes a spatial-temporal organization of the analyte concentration values, wherein the analyte concentration values ​​are positioned along a first direction according to a first time scale and along a second direction according to a second time scale, and the analyte level of the analyte concentration values ​​is constituted by one or more of shape, color, tinting, or size based on the magnitude of the analyte level.

[0040] In one aspect, the first direction and the second direction are linear directions.

[0041] In another aspect, the first direction is a bending direction and the second direction is a radial direction.

[0042] In one aspect, the first time scale is hourly and the second time scale is daily.

[0043] In another aspect, the first time scale is hourly and the second time scale is daily, wherein the modified graph includes analyte level traces overlaid on the modified graph such that higher analyte levels are closer to the outer curvature of the graph and lower analyte levels are closer to the inner curvature of the graph, or vice versa.

[0044] In one aspect, the higher analyte level is represented by a first color, the lower analyte level by a second color, and the analyte level between the higher and lower analyte levels by a third color.

[0045] In one aspect, the analyte level trace includes the average analyte level of the daily analyte concentration values.

[0046] In another aspect, the analyte level trace includes the current analyte level on the hourly timescale.

[0047] In some aspects, modifying the graph may include: clustering of colors, gradients of colors or shadows, alignment of areas, or lighter or darker shadows of overlapping areas, thereby modifying the arrangement of the analyte concentration values ​​over the plurality of time intervals.

[0048] In some aspects, the one or more modes indicate the analyte concentration values ​​relative to high and low analyte level thresholds of the subject.

[0049] In one aspect, the plurality of time intervals comprise a 24-hour cycle within a 7-day period.

[0050] In one aspect, the graph comprises an isometric curve plotted over a 24-hour cycle over a 7-day period.

[0051] In another aspect, the isometric graph can be displayed in a three-dimensional view.

[0052] In one aspect, the graphic comprises concentric rings.

[0053] In one aspect, the graph comprises a sector curve.

[0054] In another aspect, the graph may include one or more curves.

[0055] Another embodiment includes a system comprising: a continuous analyte sensor configured to acquire glucose data of a subject; a wireless transmitter configured to receive the glucose data from the continuous analyte sensor and transmit the glucose data to a processing module; the processing module is further configured to receive insulin data of the subject, the glucose data of the subject, and event data of the subject and generate a graphical display on a mobile computing device, wherein the processing module further modifies the graphical display to display visual elements indicating the relationship between the insulin data, the glucose data, and the event data and one or more of the relationships between them or with time.

[0056] In one aspect, the event data includes one or more of insulin administration, carbohydrate intake, or exercise.

[0057] In one aspect, the insulin data includes an active insulin value, and the visual element includes a colored ring indicating the active insulin and an estimated time remaining for the active insulin.

[0058] In one aspect, the visual element includes a trend graph of the glucose data and an interactive pop-up window associated with a region or feature of the trend graph, the interactive pop-up window being presented when a user selects the region or feature of the trend graph on the graphical display, wherein the presented pop-up window contains at least some of the insulin data and / or the event data.

[0059] In another aspect, the presented pop-up window is configured to display a graphical arrangement of the insulin data, including one or more of the following: insulin bolus or basal dose, administration time of bolus insulin, administration time of basal insulin, or active insulin value.

[0060] In one aspect, the presented pop-up window is configured to display a graphical arrangement of the event data, including one or more of the following: the amount of carbohydrate intake, the amount of time spent exercising, the amount of calories burned, or heart rate levels at or associated with a threshold.

[0061] In one aspect, the visual element includes arrows corresponding to insulin data and glucose readings including glucose trends corresponding to glucose data, wherein the arrows are displayed close to the trend graph and modified to indicate the effect of insulin data on the glucose data.

[0062] In some aspects, the visual element includes trend graphs of past glucose data and future glucose data, wherein the future glucose data is determined based on the subject's insulin data and action data.

[0063] In another aspect, the visual elements include: a first graphical display depicting the current value of the glucose data and an indication of the future trend of the glucose data, and a second graphical display representing the amount of insulin, wherein the second graphical display is interactive with the first graphical display to depict the possible influence of the amount of insulin on the indication of the future trend of the glucose data.

[0064] In one aspect, the processing module is further configured to: generate one or more datasets, each based on an action of the subject, and a prediction of glucose data trends based on the action of the subject, wherein the visual element comprises a scrollable list containing one or more modified graphs, each based on one or more datasets.

[0065] In another aspect, the processing module is further configured to: compare the current glucose value with high and low glucose thresholds and generate a glucose score; compare the current active insulin with high and low insulin thresholds and generate an IOB score; generate an insulin status by multiplying the glucose score and the IOB score; and classify the insulin score in one of a plurality of categories.

[0066] In one aspect, the multiple categories include good, attentive, and bad.

[0067] In one aspect, the visual element includes a colored display, wherein each plurality of categories is associated with a different color, and the color depicts the insulin score associated with the grading.

[0068] In another aspect, generating the insulin state further involves multiplying by a trend value.

[0069] In one aspect, generating the insulin state further includes multiplying by one or more scores based on location, food intake, and exercise.

[0070] In one aspect, the visual element includes a digital display of the current glucose value and a graphic representation of a predicted future trend in the glucose value.

[0071] In some aspects, the system includes: a lead module configured to receive input data of the subject in relation to future event data, wherein the visual element includes a glucose trend curve and the visual element is modified accordingly when the input data is modified.

[0072] In some aspects, the visual element includes a trend curve of glucose, wherein the region between the trend curve and a high glucose threshold is a first color and the region between the trend curve and a low threshold is a second color.

[0073] 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, 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-reference dataset; and generating the graphical display in an arrangement that is graphically modified to indicate one or more features in the data.

[0074] One embodiment includes a computer-implemented method comprising: obtaining glucose data of a subject via a glucose monitoring device; transmitting the glucose data of the subject via a wireless transmitter; receiving insulin data, glucose data, and event data of the subject, and generating a graphical display on a mobile computing device, wherein the graphical display includes a display of one or more of the insulin data, glucose data, or event data; modifying the graphical display to display visual elements indicating the relationship between the insulin data, glucose data, or event data and one or more of each other or with time, wherein the visual elements are shaped and configured or scaled to avoid obscuring the display of the insulin data, glucose data, or event data, and the visual elements are fully displayed within the display of the insulin data, glucose data, or event data.

[0075] In some aspects, the event data includes one or more of insulin administration, carbohydrate intake, or exercise.

[0076] In one aspect, the insulin data includes an active insulin value, and the visual element includes a colored ring indicating the active insulin and an estimated time remaining for the active insulin.

[0077] In some aspects, the visual element includes a trend graph of the glucose data and an interactive pop-up window associated with a region or feature of the trend graph, the interactive pop-up window being presented when a user selects the region or feature of the trend graph on the graphical display, wherein the presented pop-up window contains at least some of the insulin data and / or the event data.

[0078] In another aspect, the presented display window contains a graphical arrangement of the insulin data, including one or more of the following: insulin bolus or basal dose, bolus insulin administration time, basal insulin administration time, or active insulin value.

[0079] In one aspect, the presented pop-up window contains a graphical arrangement of the event data, including one or more of the following: the amount of carbohydrate intake, the amount of time spent exercising, the amount of calories burned, or heart rate levels at or associated with a threshold.

[0080] In some aspects, the visual elements include arrows corresponding to insulin data and glucose readings containing glucose trends corresponding to glucose data, wherein the arrows are displayed close to the trend graph and modified to indicate the effect of insulin data on glucose data.

[0081] In one aspect, the visual element includes trend graphs of past glucose data and future glucose data, wherein the future glucose data is determined based on the subject's insulin data and action data.

[0082] In another aspect, the visual elements include: a first graphical display depicting the current value of the glucose data and an indication of the future trend of the glucose data, and a second graphical display representing the amount of insulin, wherein the second graphical display is interactive with the first graphical display to depict the possible influence of the amount of insulin on the indication of the future trend of the glucose data.

[0083] In some aspects, the method further includes: generating one or more datasets, each based on the actions of the subject, and a prediction of glucose data trends based on the actions of the subject, wherein the visual element comprises a scrollable list containing one or more modified graphs, each based on the one or more datasets.

[0084] In other aspects, the method further includes: comparing the current glucose value with high and low glucose thresholds to generate a glucose score; comparing the current active insulin with high and low insulin thresholds to generate an IOB score; generating an insulin status by multiplying the glucose score and the IOB score; and classifying the insulin score into one of a plurality of categories.

[0085] In one aspect, the multiple categories include good, attentive, and bad.

[0086] In another aspect, the visual elements include a colored display, wherein each of the plurality of categories is associated with a different color, and the color depicts the insulin score associated with the grade.

[0087] In one aspect, generating the insulin state further involves multiplying by a trend value.

[0088] In another aspect, generating the insulin state further involves multiplying by one or more scores based on location, food intake, and exercise.

[0089] In another aspect, the visual elements include a digital display of the current glucose value and a graphic representation of a predicted future trend in the glucose value.

[0090] In one aspect, the method further includes: receiving input data of the subject in relation to future event data, wherein the visual element comprises a glucose trend curve and the visual element is modified accordingly when the input data is modified.

[0091] In one aspect, the visual element includes a trend curve of glucose, wherein the region between the trend curve and a high glucose threshold is a first color and the region between the trend curve and a low threshold is a second color.

[0092] In some aspects of the method, generating the graphical display comprises: 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-reference dataset; and generating the graphical display in an arrangement that is graphically modified to indicate one or more features in the data.

[0093] In one aspect, the processing module is further configured to receive diabetes-related data from the subject and generate an interactive graphical display on the mobile computing device, wherein a viewer is able to interact with the interactive graphical display.

[0094] In one aspect, the interactive graphical display includes a trend curve containing the glucose data and a region between the trend curve and a glucose threshold, with different colors for regions exceeding a high threshold and regions exceeding a low threshold, wherein the high threshold and the low threshold can be adjusted by the viewer interacting with the interactive graphical display.

[0095] In another aspect, the viewer can interact with the interactive graphic display through a foldable design layout.

[0096] In some aspects, the interactive graphical display further includes one or more animations to convey information.

[0097] In another aspect, the viewer can interact with the interactive graphic display by selecting a personalized background image.

[0098] In some embodiments, the viewer can interact with the interactive graphical display by entering numerical values ​​via a graphics wheel.

[0099] In one aspect, the method further comprises: receiving diabetes-related data of the subject and generating an interactive graphical display on the mobile computing device, wherein a viewer is able to interact with the interactive graphical display.

[0100] In one aspect, the interactive graphical display includes a trend curve containing the glucose data and a region between the trend curve and a glucose threshold, with different colors for regions exceeding a high threshold and regions exceeding a low threshold, wherein the high threshold and the low threshold can be adjusted by the viewer interacting with the interactive graphical display.

[0101] In another aspect, the viewer can interact with the interactive graphic display through a foldable design layout.

[0102] In some aspects, the interactive graphical display further includes one or more animations to convey information.

[0103] In one aspect, the viewer can interact with the interactive graphical display by selecting a personalized background image.

[0104] In one aspect, the viewer can interact with the interactive graphical display by inputting numerical values ​​via a graphics wheel.

[0105] In one aspect of the system, the graphical display further includes an indication of the subject in which the analyte measurement value is obtained.

[0106] One embodiment includes a system comprising: a continuous analyte sensor configured to acquire analyte measurements of a subject; a wireless transmitter configured to receive the analyte measurements from the continuous analyte sensor; and an analyte data processing module operable on a mobile computing device wirelessly connected to the wireless transmitter, the analyte data processing module being configured to: receive at least a portion of the analyte measurements; generate a self-reference dataset in part based on the analyte measurements; generate one or more graphical displays based on the self-reference dataset; modify the self-reference dataset; and display one or more modified graphical displays based on the modified self-reference dataset.

[0107] In one aspect, the analyte data processing module is further configured to: generate a high or low threshold for the concentration of the analyte in the subject, in part based on one or more of the following: health data obtained from the subject, statistical analysis of the analyte measurement, contextual data related to the analyte measurement, health data derived from the subject's profile, or health data obtained from one or more health data databases; determine the time when the analyte measurement of the subject reaches the high or low threshold; modify one or more of the high or low threshold when the time is equal to or less than a predetermined safety time; and regenerate the self-reference dataset to display an animation indicating the change of the threshold.

[0108] In one aspect, the modified graphical display includes a graph of analyte measurements against time, and the animation includes moving a flashing threshold line from a first value to the current analyte value of the subject.

[0109] In one aspect, the desired graphical display includes one or more graphs of analyte measurements against time, and wherein the analyte data processing module is further configured to: determine one or more expected ranges for analyte values; and modify the self-reference dataset based on the expected ranges for analyte values ​​to display the analyte measurements.

[0110] In some respects, the expected range of the analyte value is based on one or more of the following: input from the subject, contextual data relating to the analyte measurement, or health data from a healthcare organization or healthcare authority.

[0111] In some aspects, the self-reference dataset is modified to display the analyte measurements relative to the expected range using differences in color, line style, animation, shading, gradient, or other visual elements.

[0112] In one aspect, the expected range of the analyzed value includes the target range, the range of attention, and the range beyond the target range.

[0113] In another aspect, the self-reference dataset is modified to subtract the analyte values ​​within the target range and only display the analyte values ​​within the attention range and those outside the target range.

[0114] In some respects, the expected range of the analyzed value is modified based on event data obtained from the subject.

[0115] In some aspects, the modified graphical display includes one or more digital displays containing the current value of the analyte measurement, an indication of a predicted future trend of the analyte measurement, a textual phrase indicating the current state and the predicted future trend of the analyte measurement, a graph of the analyte measurement against time, one or more lines indicating high and low thresholds of analyte concentration in the body, and a graphical representation on the analyte graph indicating the current value of the analyte measurement.

[0116] In one aspect, the self-reference dataset is dynamically modified based on analyte measurements, and the self-reference dataset is further modified to indicate whether the current analyte measurement reaches or exceeds a threshold of the analyte concentration value in the body, and wherein the indication of the predicted future trend of the analyte measurement, the threshold line associated with reaching or exceeding the threshold, and the graphical representation of the current analyte value on the analyte graph consistently change styles and pulsate.

[0117] In another aspect, the analyte data processing module is further configured to generate one or more audible alarms when an analyte threshold is reached or exceeded.

[0118] In one aspect, the self-referenced dataset is modified to display one or more system status messages.

[0119] In another aspect, the self-referenced dataset is modified to display a dark background. Attached Figure Description

[0120] Further aspects of this disclosure will become more readily apparent upon review of the detailed description of the various disclosed embodiments described below in conjunction with the accompanying drawings.

[0121] Figure 1A This describes aspects of an example system that can be used in conjunction with embodiments of this disclosure.

[0122] Figure 1B This describes aspects of an example system that can be used in conjunction with embodiments of this disclosure.

[0123] Figure 2A This is a perspective view of an example housing that can be used in conjunction with an embodiment of an analytical material sensor system.

[0124] Figure 2B This is a side view of an example housing that can be used in conjunction with an embodiment of an analytical material sensor system.

[0125] Figure 3A This describes aspects of an example system that can be used in conjunction with embodiments of this disclosure.

[0126] Figure 3B This describes aspects of an example system that can be used in conjunction with embodiments of this disclosure.

[0127] Figure 4A It is a modified graphical display where analyte concentration values ​​are arranged and presented over multiple time intervals.

[0128] Figure 4B It is by Figure 4A The modified graphic representation is composed of a bird's-eye view of the curve graph.

[0129] Figure 5 This is an illustration of an exemplary graphical display, in which analyte concentration values ​​are arranged and presented in a pie chart at multiple time intervals.

[0130] Figure 6 This section describes a modified graphical display of the data structure and layout corresponding to the analyte concentration values ​​over a time interval.

[0131] Figure 7 It is a modified graphical representation of the data structure and arrangement of analyte data over multiple time intervals.

[0132] Figure 8 It is a modified graphical representation of the data structure and arrangement of analyte data over multiple time intervals.

[0133] Figure 9 It is a modified graphical representation of the data structure and arrangement of analyte data over multiple time intervals.

[0134] Figure 10 yes Figure 9 The modified graphic display shows the explanation.

[0135] Figure 11 It provides daily breakdown of analytical values. Figure 10 The modified graphic display.

[0136] Figure 12 This is an illustration of an exemplary graphical display, in which analyte concentration values ​​are shown on a clock scale graph.

[0137] Figure 13AA flowchart illustrating an exemplary method by which the disclosed system can generate and display modified graphical displays.

[0138] Figure 13B Explanation for implementation in Figure 13A A flowchart illustrating an exemplary method for the identification process during the process.

[0139] Figure 13C Explanation for implementation in Figure 13A A flowchart illustrating an exemplary method for the identification process during the process.

[0140] Figure 13D Explanation for implementation in Figure 13A A flowchart illustrating an exemplary method for the identification process during the process.

[0141] Figure 14 This is a modified graphical representation of the data structure and layout of insulin data.

[0142] Figure 15 and 16 The modified graphic display shows visual elements indicating the relationship between insulin data, analyte data, and event data and one or more of them and / or with respect to a time period.

[0143] Figure 17 illustrate Figure 15 and 16 The insulin bond diagram.

[0144] Figure 18 This describes a modified graphical representation of the trend curve of the analyzed data.

[0145] Figure 19A and 19B The illustration shows a modified graphical representation of the property values ​​based on historical, current, and forecast analyses.

[0146] Figure 20 The illustration shows a modified graphical representation of the effect of insulin dosage on analyte data.

[0147] Figure 21 This describes a modified graphical display of a scrollable list depicting user action data and future value trends.

[0148] Figure 22 A modified graphical display illustrating the relationship between multiple variables related to trends in data and user actions.

[0149] Figure 23 This indicates that the glucose trend curve visually distinguishes deviations outside of high and low thresholds.

[0150] Figure 24AThis illustrates a modified graphic display that utilizes a foldable design layout.

[0151] Figure 24B and 24C This describes a display screen that presents modifiable graphics based on user interaction with the screen.

[0152] Figure 25 This describes a modified graphic display that can use animation to convey health-related information.

[0153] Figure 26 This describes the modified graphic display of the background image that users can customize.

[0154] Figure 27 The description includes a modified graphical display that allows users to input numerical data using the scroll wheel.

[0155] Figure 28 This illustrates an example of a modified display in which the user's identifier is incorporated.

[0156] Figure 29 This explains how the change in the analysis threshold is conveyed through animation.

[0157] Figure 30 Explain the analyte curve plotting the measured values ​​of the analyte in relation to the expected range of the analyte values.

[0158] Figure 31 This describes an exemplary modified graphical display that conveys information about the concentration, threshold, relevant analyte graphs, and / or the status and reporting of the analyte monitoring system in the subject.

[0159] The accompanying drawings are described in more detail in the following description and examples. The drawings are provided for illustrative purposes only and depict only typical or exemplary embodiments of this disclosure. The drawings are not intended to be exhaustive or to limit this disclosure to the precise forms disclosed. It should also be understood that this disclosure can be practiced with modifications or alterations, and that this disclosure may be limited only by the claims and their equivalents. Detailed Implementation

[0160] Embodiments of this disclosure pertain to systems, methods, and apparatus for generating dynamic data structures and graphical displays. In the various deployments described herein, analyte data is glucose data generated by an analyte sensor system configured to connect to a display device and the like. As described in detail herein, aspects of this disclosure can modify the graphical display of analyte data in a way that conveniently and efficiently indicates patterns in the analyte data. Furthermore, aspects of this disclosure can also conveniently indicate one or more relationships between glucose data, insulin data, and user actions. Specifically, such aspects of this disclosure relate, for example, generating a reference data structure and modifying the graphical display based on said data structure to convey information related to diabetes management.

[0161] Details of some exemplary embodiments of the systems, methods, and apparatuses disclosed herein are set forth in this specification and, in some cases, in other parts of this disclosure. Other features, objects, and advantages of this disclosure will become apparent to those skilled in the art upon review of this disclosure, the specification, the drawings, examples, and claims. It is intended that all such additional systems, methods, apparatuses, features, and advantages be incorporated herein by reference (whether explicitly or implicitly), are included within the scope of this disclosure, and are protected by one or more of the appended claims.

[0162] Overview In some embodiments, a system is provided for the continuous measurement of an analyte in a body. The system may include: a continuous analyte sensor configured to continuously measure the concentration of the analyte in the body, and a sensor electronics module physically connected to the continuous analyte sensor during sensor use. In some 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, transformed sensor data, and / or any other sensor data. The sensor electronics module may be further configured to generate sensor information tailored to a corresponding display device, such that different display devices can receive different sensor information.

[0163] As used herein, the term "analyte" is a broad term and its general and conventional meaning (and not limited to a specific or customized meaning) is to be determined by those skilled in the art. It further refers to (but is not limited to) substances or chemical components in analyzable biological fluids (e.g., blood, interstitial fluid, cerebrospinal fluid, lymph, urine, sweat, saliva, etc.). Analytes may include naturally occurring substances, artificial substances, metabolites, and / or reaction products. In some embodiments, the analyte used for measurement by the method or apparatus is glucose. However, other analytes are also anticipated, including but not limited to: prothrombin; acetoacetic acid; acetone; acetyl-CoA; carnitine; adenine phosphoribosyltransferase; adenosine deaminase; albumin; alpha-fetoprotein; amino acid profile (arginine (Krebs cycle), histidine / uric acid, homocysteine, phenylalanine / tyrosine, tryptophan); androstenedione; antipyrine; arabinitol enantiomers; arginase; biotinylate; biopterin; C-reactive protein; L-carnitine; carnosinase; CD4; ceruloplasmin; chenodeoxycholic acid; chloroquine; cholesterol; cholinesterase; conjugated protein. 1-β-hydroxycholic acid; cortisol; creatine kinase; creatine kinase MM isoenzyme; cyclosporine A; d-penicillamine; desethylchloroquine; dehydroepiandrosterone sulfate; DNA (acetylation polymorphism); alcohol dehydrogenase; α1-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; β-thalassemia; hepatitis B virus; HCMV; HIV-1; HTLV-1; Reiber's hereditary optic neuropathy MCAD, RNA, PKU, Plasmodium vivax, sexual differentiation, 21-deoxycortisol); debutylhalogenated pan-group; dihydropteridine reductase; diphtheria / tetanus antitoxin; erythrocyte arginase; erythrocyte protoporphyrin; esterase D; fatty acid / acylglycine; triglycerides; free β-human chorionic gonadotropin; free erythrocyte porphyrin; free thyroxine (FT4); free triiodothyronine (FT3); fumarate diacetyl; galactose / galon-1-phosphate; galactose-1-phosphate uridine ditransferase; gentamicin; glucose-6-phosphate dehydrogenase; glutathione ; Glutathione peroxidase; Glycine; Glycated hemoglobin; Halopanatin; Hemoglobin variants; Hexosamine A; Human erythrocyte carbonic anhydrase I; 17-α-dihydroxyprogesterone; Hypoxanthine phosphoribosyltransferase; Immunoreactive trypsin; Ketone bodies; Lactate; Lead; Lipoproteins ((a), B / A-1, β); Lysozyme; Mefloquine; Netilmicin; Phenobarbital; Phenytoin sodium; Phytane / proline; Progesterone; Prolactin; Proline peptidase; Purine nucleoside phosphorylase; Quinine; Reverse triiodothyronine (rT3); Selenium; Serum pancreatic lipase; Cesarean mycoside; Somatostatin C;Specific antibodies (adenovirus, antinuclear antibody, antizeta antibody, arbovirus, pseudorabies virus, dengue virus, dracunculia spp., echinococcosis, entamoeba histolytica, enterovirus, giardia duodenalis, Helicobacter pylori, hepatitis B virus, herpesvirus, HIV-1, IgE (atopic), influenza virus, isoprene (2-methyl-1,3-butadiene), Leishmania donovani, leptospira, measles / mumps / rubella, Mycobacterium leprae, Mycoplasma pneumoniae, myoglobin, Onchocerca salina). Parainfluenza virus, Plasmodium falciparum, poliovirus, Pseudomonas aeruginosa, respiratory syncytial virus, Rickettsia (scrub typhus), Schistosoma mansoni, Toxoplasma gondii, Xanthium sibiricum, Trypanosoma cruzi / Langelly, vesicular stomatitis virus, Wuchnis bancroftian nematode, flaviviruses (e.g., deer tick, dengue fever, brucellosis virus, West Nile virus, yellow fever, or Zika virus); specific antigens (hepatitis B virus, HIV-1); succinyl; sulfonamides; theophylline; thyroid-stimulating hormone (TSH); thyroxine (T4); thyroxine-binding globulin; Trace elements; transfer proteins; UDP-galactose-4-epimerase; urea; uroporphyrinogen I synthase; vitamin A; leukocytes; and zinc protoporphyrin. In some embodiments, salts, sugars, proteins, fats, vitamins, and hormones naturally present in blood or interstitial fluid may also constitute the analyte. The analyte may be naturally present in biological fluids, for example, metabolites, hormones, antigens, antibodies, and analogues. Alternatively, the analyte may be introduced into the body or be non-native, for example, contrast agents used for imaging, radioactive isotopes, chemical... Reagents, fluorocarbon-based synthetic blood or pharmaceutical or medical compositions, including (but not limited to): glucagon, ethanol, inhalants (nitrous oxide, amyl nitrite, butyl nitrite, chlorinated hydrocarbons, hydrocarbons), inhibitors (barbiturates, methylquinone, such as diazepam, nitrazepam, nitrazepam, methylbutyrate, potassium chlordiazepoxide), anesthetics (codeine, pethidine, oxycodone, compound oxycodone, hydrocodone antitussives, fentanyl, propoxyphene hydrochloride preparations, analgesics, antidiarrheal drugs), designer drugs. Drugs (analytes of fentanyl, pethidine, amphetamine, and phencyclohexylpiperidine, e.g., psychedelic drugs), anabolic steroids, and nicotine. Metabolites of drugs and pharmaceutical compositions are also included as analytes. Analytes produced in the human body, such as neurochemicals and other chemicals, such as ascorbic acid, uric acid, dopamine, norepinephrine, 3-methoxytyramine (3MT), 3,4-dihydroxyphenylacetic acid (DOPAC), homovanillic acid (HVA), serotonin (5HT), 5-hydroxyindoleacetic acid (FHIAA), and mediators in the citric acid cycle, may also be analyzed.

[0164] Warning In some embodiments, one or more alerts are associated with a sensor electronics module. For example, each alert may include one or more alert conditions indicating when the corresponding alert has been triggered. For example, a hypoglycemia alert may include alert conditions indicating a minimum glucose level. Alert conditions may also be based on transformed sensor data, such as trend data, and / or sensor data from multiple different sensors (e.g., an alert may be based on sensor data from both a glucose sensor and a temperature sensor). For example, a hypoglycemia alert may include alert conditions indicating a minimum required trend in the subject's glucose level, which must exist before the alert is triggered. As used herein, the term "trend" generally refers to data indicating some attribute of data acquired over time, such as calibrated or filtered data from a continuous glucose sensor. A trend may indicate the amplitude, rate of change, acceleration, direction, etc., of data such as sensor data, which includes transformed or raw sensor data.

[0165] In some embodiments, each of the alerts is associated with one or more actions to be performed in response to the triggering of the alert. Alert actions may include, for example, activating an alarm, such as displaying information on a display of the sensor electronics module or activating an audible or vibration alarm coupled to the sensor electronics module, and / or transmitting data to one or more display devices external to the sensor electronics module. For any transmission action associated with a triggered alert, one or more transmission options define the content and / or format of the data to be transmitted, the device to which the data will be transmitted, when the data will be transmitted, and / or the communication protocol used for data transmission.

[0166] In some embodiments, multiple transmission actions (each with a corresponding transmission option) can be associated with a single alert, causing displayable sensor information with different content and formatting to be transmitted to the corresponding display device, for example, in response to the triggering of a single alert. For instance, a mobile phone can receive a data packet containing minimal displayable sensor information (specifically formatted for display on the mobile phone), while a desktop computer can receive a data packet containing most (or all) of the displayable sensor information generated by the sensor electronics module in response to the triggering of a common alert. Advantageously, the sensor electronics module is not tied to a single display device but is configured to communicate directly, systematically, simultaneously (e.g., via broadcast), regularly, periodically, randomly, on demand, in response to queries, based on alerts or alarms, and / or similarly with multiple different display devices.

[0167] In some embodiments, clinical risk alerts are provided that include alert conditions combining intelligent and dynamic estimation algorithms that estimate current or predicted hazards with greater accuracy, more timely information about impending hazards, avoidance of false alarms, and less annoyance to the patient. Generally, clinical risk alerts incorporate dynamic and intelligent estimation algorithms based on analyte concentrations, rates of change, accelerations, clinical risks, statistical probabilities, known physiological constraints, and / or individual physiological patterns, thereby providing more appropriate, clinically safe, and patient-friendly alerts. U.S. Patent Publication No. 2007 / 0208246, incorporated herein by reference in its entirety, describes some systems and methods associated with the clinical risk alerts (or alarms) described herein. In some embodiments, a clinical risk alert may be triggered for a predetermined period of time to allow a user to care for his / her condition. Additionally, a clinical risk alert may be deactivated when the patient leaves a clinically risky area so as not to disturb the patient with repetitive clinical alarms (e.g., visual, audible, or vibratory) as the patient's condition improves. In some embodiments, dynamic and intelligent estimation determines the likelihood of the patient avoiding clinical risks based on analyte concentrations, rates of change, and other aspects of the dynamic and intelligent estimation algorithm. If the probability of avoiding a clinical risk is minimal or nonexistent, a clinical risk warning is triggered. However, if the probability of avoiding a clinical risk exists, the system is configured to wait a predetermined amount of time and re-analyze the probability of avoiding the clinical risk. In some embodiments, when the probability of avoiding a clinical risk exists, the system is further configured to provide goals, treatment recommendations, or other information that can assist the patient in prospectively avoiding the clinical risk.

[0168] In some embodiments, the sensor electronics module is configured to search for one or more display devices within its communication range and wirelessly transmit sensor information (e.g., data packets containing displayable sensor information, one or more alarm conditions, and / or other alarm information) to them. Therefore, the display devices are configured to display at least some of the sensor information and / or issue an alarm to the subject (and / or caregiver), wherein the alarm mechanism is located on the display device.

[0169] In some embodiments, the sensor electronics module is configured to provide one or more different alarms via the transmission of data packets indicating that an alarm should be initiated by one or more display devices (e.g., sequentially and / or simultaneously). In some embodiments, the sensor electronics module provides only a data field indicating the presence of an alarm condition, and the display device can decide to trigger an alarm immediately after reading the data field indicating the presence of the 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 have been triggered. For example, when an alert trigger indicates severe hypoglycemia, the sensor electronics module may perform multiple actions, such as activating an alarm on the sensor electronics module, transmitting a data packet to a monitoring device to indicate the activation of the alarm on a display, and transmitting the data packet as a text message to a care provider. As an example, the text message may appear on a custom monitoring device, mobile phone, pager device, and / or the like, containing displayable sensor information indicating the condition of the subject (e.g., "severe hypoglycemia").

[0170] In some embodiments, the sensor electronics module is configured to wait for a period of time for a subject to respond to a triggered alert (e.g., by pressing or selecting a drowsy and / or disconnect function and / or button on the sensor electronics module and / or display device), after which additional alerts (e.g., in an incremental manner) are triggered until one or more alerts are responded to. In some embodiments, the sensor electronics module is configured to send a control signal (e.g., a stop signal) to a medical device associated with an alarm condition (e.g., hypoglycemia), such as an insulin pump, wherein the stop alert triggers the cessation of insulin delivery via the pump.

[0171] In some embodiments, the sensor electronics module is configured to transmit alarm information directly, systematically, simultaneously (e.g., via broadcast), regularly, periodically, randomly, on demand, in response to queries (from a display device), based on alerts or alarms, and / or similar methods. In some embodiments, the system further includes a repeater such that the wireless communication range of the sensor electronics module can be increased, for example, to 10, 20, 30, 50, 75, 100, 150, or 200 meters or more, wherein the repeater is configured to forward wireless communication from the sensor electronics module to a display device located away from the sensor electronics module. The repeater can be used in homes with children who have diabetes. For example, to allow parents to carry the display device or place it in a fixed location, such as in a large house where parents and children sleep at a distance.

[0172] Display device In some embodiments, the sensor electronics module is configured to search for and / or attempt to wirelessly communicate with display devices in a list of display devices. In some embodiments, the sensor electronics module is configured to search for and / or attempt to wirelessly communicate with the list of display devices in a predetermined and / or programmable order (e.g., hierarchical and / or incremental), such that a failed attempt and / or alarm regarding communication with a first display device triggers an attempt and / or alarm regarding communication with a second display device, and so on. In one example embodiment, the sensor electronics module is configured to sequentially search and attempt to alarm a subject or care provider using a list of display devices, such as: (1) a default display device or a custom analyte monitoring device; (2) a mobile phone via auditory and / or visual methods, e.g., text messages to the subject and / or care provider, voice messages to the subject and / or care provider, and / or 911); (3) a tablet computer; (4) a smartwatch or wristband; and / or (5) smart glasses or other wearable display devices.

[0173] Depending on the embodiment, one or more display devices that receive data packets from the sensor electronics module are “dummy displays” where they display displayable sensor information received from the sensor electronics module without additional processing (e.g., the forward-looking algorithmic processing 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 the display of the displayable sensor information. Some display devices may include software including display instructions (including software programming configured to display the displayable sensor information and optionally query the sensor electronics module to obtain the displayable sensor information), the display instructions being configured to implement the displayable sensor information on the display device. In some embodiments, the display device is programmed with display instructions at the manufacturer and may include security and / or authentication to prevent plagiarism of the display device. In some embodiments, the display device is configured to display the displayable sensor information via a downloadable program (e.g., a Java script downloadable via the Internet), such that any display device that supports program download (e.g., any display device that supports Java applets) can therefore be configured to display the displayable sensor information (e.g., mobile phones, tablets, PDAs, PCs, and the like).

[0174] In some embodiments, certain display devices may directly communicate wirelessly with the sensor electronics module, but intermediate network hardware, firmware, and / or software may be included within the direct wireless communication. In some embodiments, a repeater (e.g., a Bluetooth repeater) may be used to retransmit transmitted displayable sensor information to a location farther from the immediate vicinity of the telemetry module of the sensor electronics module, wherein the repeater enables 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 transmitted displayable sensor information, possibly in a different format, such as in a text message, to a TV screen, wherein the receiver enables direct wireless communication when no substantial processing of the sensor information occurs. In some embodiments, the sensor electronics module directly and wirelessly transmits displayable sensor information 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.

[0175] In some embodiments, one or more display devices include a built-in authentication mechanism where authentication is required for communication between the sensor electronics module and the display device. In some embodiments, to authenticate data communication between the sensor electronics module and the display device, a challenge-response protocol, such as password authentication, is provided, where a challenge is a request for a password and a valid response is the correct password, allowing pairing of the sensor electronics module and the display device to be accomplished by the user and / or the manufacturer via a password. In some cases, this may be referred to as two-way authentication.

[0176] In some embodiments, one or more display devices are configured to query a sensor electronics module for displayable sensor information, wherein the display devices act as master devices that request sensor information from the sensor electronics module (e.g., a slave device) on demand, for example, in response to a query. In some embodiments, the sensor electronics module is configured to periodically, systematically, regularly, and / or periodically transmit sensor information to one or more display devices (e.g., every 1, 2, 5, or 10 minutes or more). In some embodiments, the sensor electronics module is configured to transmit data packets associated with triggered alerts (e.g., triggered by one or more alert conditions). However, any combination of the above-described states of data transmission can be implemented using any combination of paired sensor electronics modules and display devices. For example, one or more display devices may be configured to query a sensor electronics module database and to receive alert information triggered by the fulfillment of one or more alert conditions. Additionally, the sensor electronics module may be configured for periodic transmission of sensor information to one or more display devices (the same or different display devices described in the previous examples), thereby allowing the system to include display devices that function differently regarding how sensor information is obtained.

[0177] In some embodiments, the display device is configured to query the data storage memory in the sensor electronics module for certain types of data content, including direct queries to a database in the sensor electronics module's memory and / or requests for configurable or configurable packages of data content therefrom; that is, the data stored in the sensor electronics module is configurable, searchable, predetermined, and / or pre-packaged based on the display device to which the sensor electronics module is communicating. In some additional or alternative embodiments, the sensor electronics module generates displayable sensor information based on its knowledge of which display device will receive a particular transmission. Additionally, some display devices are capable of acquiring calibration information and wirelessly transmitting the calibration information to the sensor electronics module, for example, through manual input of calibration information, automatic transmission of calibration information, and / or incorporation into an integrated reference analyzer monitor within the display device. U.S. Patent Publications 2006 / 0222566, 2007 / 0203966, 2007 / 0208245, and 2005 / 0154271 describe systems and methods for providing an integrated reference analyte monitor incorporated into a display device and / or other calibration methods that may be implemented using the embodiments disclosed herein, all of which are incorporated herein by reference in their entirety.

[0178] Generally, multiple display devices (e.g., custom analyte monitoring devices (also referred to as analyte display devices), mobile phones, tablet computers, smartwatches, reference analyte monitors, drug delivery devices, medical devices, and personal computers) can be configured to communicate wirelessly with the sensor electronics module. These multiple display devices can be configured to display at least some of the displayable sensor information wirelessly transmitted from the sensor electronics module. The displayable sensor information may include sensor data, such as raw data and / or transformed sensor data, such as analyte concentration values, rate of change information, trend information, warning information, sensor diagnostic information, and / or calibration information.

[0179] Analyte Sensor refer to Figure 1A In some embodiments, the analyte sensor 10 includes a continuous analyte sensor, such as a subcutaneous, percutaneous (e.g., transcutaneous), or intravascular device. In some embodiments, this sensor or device can analyze multiple intermittent blood samples. While this disclosure includes embodiments of a glucose sensor, these embodiments can also be used for other analytes. The glucose sensor can use any glucose measurement method, including enzymatic, chemical, physical, electrochemical, spectrophotometric, polarimetric, calorimetric, iontophoresis, radiation measurement, immunochemical, and similar methods.

[0180] Glucose sensors can use any known method, including invasive, minimally invasive, and non-invasive sensing techniques (e.g., fluorescence monitoring), to provide a data stream indicating the glucose concentration in a subject. The data stream is typically a raw data signal that is converted into a calibrated and / or filtered data stream to provide useful glucose values ​​to a user, such as a patient or caregiver (e.g., a parent, relative, guardian, teacher, doctor, nurse, or any other individual concerned about the subject's health).

[0181] A glucose sensor can be any device capable of measuring glucose concentration. According to one example embodiment described below, an implantable glucose sensor can be used. However, it should be understood that the apparatus and methods described herein can be applied to any device capable of detecting glucose concentration and providing an output signal representing the glucose concentration (e.g., in the form of analyte data).

[0182] In some embodiments, the analyte sensor 10 is an implantable glucose sensor, for example, referring to U.S. Patent 6,001,067 and U.S. Patent Publication US-2005-0027463-A1. In embodiments, the analyte sensor 10 is a percutaneous glucose sensor, for example, referring to U.S. Patent Publication US-2006-0020187-A1. In embodiments, the analyte sensor 10 is configured to be implanted in a host blood vessel or implanted externally, as described, for example, in U.S. Patent Publication US-2007-0027385-A1, co-pending U.S. Patent Publication US-2008-0119703-A1 filed October 4, 2006, U.S. Patent Publication US-2008-0108942-A1 filed March 26, 2007, and U.S. Patent Application US-2007-0197890-A1 filed February 14, 2007. In embodiments, the continuous glucose sensor comprises, for example, a percutaneous sensor as described in U.S. Patent 6,565,509 to Say et al. In embodiments, the analyte sensor 10 is a continuous glucose sensor comprising, for example, a subcutaneous sensor as described in U.S. Patent 6,579,690 to Bonnecaze et al. or U.S. Patent 6,484,046 to Say et al. In embodiments, the continuous glucose sensor comprises, for example, a refillable subcutaneous sensor as described with reference to U.S. Patent 6,512,939 to Colvin et al. The continuous glucose sensor may comprise, for example, an intravascular sensor as described with reference to U.S. Patent 6,477,395 to Schulman et al. The continuous glucose sensor may comprise, for example, an intravascular sensor as described with reference to U.S. Patent 6,424,847 to Mastrototaro et al.

[0183] Figure 2A and 2BThese are perspective and side views of a housing 200 used in conjunction with embodiments of the analyte sensor system 8 according to certain aspects of this disclosure. In some embodiments, the housing 200 includes a mounting unit 214 and a sensor electronics module 12 attached thereto. The housing 200 is shown in a functional position, including the mounting unit 214 and the sensor electronics module 12 matingly engaged therein. In some embodiments, the mounting unit 214, also referred to as a housing or sensor compartment, includes a base 234 adapted to fasten to the skin of a body or user. The base 234 may be formed of a variety of hard or soft materials and may include a low profile for minimal protrusion of the device from the body during use. In some embodiments, the base 234 is at least partially formed of a flexible material, which can provide many advantages over other transdermal sensors, however, it may suffer from motion-related artifacts associated with movement of the body when the body uses the device. The mounting unit 214 and / or the sensor electronics module 12 may be located above the sensor insertion site to protect the site and / or provide minimal footprint (utilization of the surface area of ​​the body's skin).

[0184] In some embodiments, a detachable connection is provided between the mounting unit 214 and the sensor electronics module 12. This achieves improved manufacturability, meaning that the potentially relatively inexpensive mounting unit 214 can be discarded when the analyte sensor system 8 is serviced or maintained, while the relatively more expensive sensor electronics module 12 can be reused in multiple sensor systems. In some embodiments, the sensor electronics module 12 is configured with signal processing (programming), for example, configured to filter, calibrate, and / or execute other algorithms that can be used to calibrate and / or display sensor information. However, an integrated (non-detachable) sensor electronics module can be configured.

[0185] In some embodiments, the contact 238 is mounted on or within a sub-assembly hereinafter referred to as contact sub-assembly 236, which is configured to engage within the base 234 and hinge 248 of the mounting unit 214, allowing the contact sub-assembly 236 to pivot relative to the mounting unit 214 between a first position (for insertion) and a second position (for use). The term “hinge” as used herein is a broad term and is used in its general sense to include, but is not limited to, any of a variety of pivoting, articulated, and / or articulated mechanisms, such as adhesive hinges, sliding joints, and the like; the term hinge does not necessarily imply a fulcrum or fixed point around which an articulated connection is surrounded. In some embodiments, the contact 238 is formed of a conductive elastic material, such as a carbon black elastomer, through which the sensor 10 extends.

[0186] See further Figure 2A and 2BIn some embodiments, the mounting unit 214 includes an adhesive pad 208 disposed on the back surface of the mounting unit and comprising a releasable backing layer. Thus, removing the backing layer and pressing at least a portion of the base 234 of the mounting unit 214 onto the skin of the subject will adhere the mounting unit 214 to the skin of the subject. Alternatively or additionally, after sensor insertion is complete, the adhesive pad may be placed over some or all of the analyte sensor system 8 and / or sensor 10 to ensure adhesion and optionally to ensure an airtight or watertight seal around the wound exit site (or sensor insertion site) (not shown). Appropriate adhesive pads may be selected and designed to stretch, elongate, conform to, and / or ventilate the area (e.g., the skin of the subject). Reference is made to U.S. Patent No. 7,310,544, which is incorporated herein by reference in its entirety, for more detailed description. Figure 2A and 2B The described embodiments. The configuration and arrangement can provide water-resistant, waterproof, and / or hermetically sealed properties associated with the mounting unit / sensor electronics module embodiments described herein.

[0187] Various methods and apparatuses 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 herein by reference in its entirety for all purposes.

[0188] Instance Configuration See again Figure 1A This document describes a system 100 that can be used in conjunction with aspects of implementing an analyte sensor system. In some cases, system 100 can be used to implement various systems described herein. According to certain aspects of this disclosure, system 100 includes, in embodiments, an analyte sensor system 8 and display devices 110, 120, 130, and 140. The analyte sensor system 8 in the illustrated embodiments includes a sensor electronics module 12 and a continuous analyte sensor 10 associated with the sensor electronics module 12. The sensor electronics module 12 can wirelessly communicate (e.g., directly or indirectly) with one or more of the display devices 110, 120, 130, and 140. In embodiments, system 100 also includes a medical device 136 and a server system 134. The sensor electronics module 12 can also wirelessly communicate (e.g., directly or indirectly) with the medical device 136 and the server system 134. In some instances, display devices 110-140 can also wirelessly communicate with the server system 134 and / or the medical device 136.

[0189] In some embodiments, the sensor electronics module 12 includes electronic circuitry associated with measuring and processing continuous analyte sensor data, and includes forward-looking 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 integrally attached to the continuous analyte sensor 10 (in a non-releasable manner) or releasably attached to the continuous analyte sensor. The sensor electronics module 12 may include hardware, firmware, and / or software enabling the measurement of analyte levels via a glucose sensor. For example, the sensor electronics module 12 may include a potentiometer, a power source for supplying power to the sensor, other components for signal processing and data storage, and a telemetry module for transmitting data from the sensor electronics module to one or more display devices. The electronics may be attached to a printed circuit board (PCB) and the like, and may take various forms. For example, the electronics may be in the form of integrated circuits (ICs), such as application-specific integrated circuits (ASICs), microcontrollers, and / or processors.

[0190] Sensor electronics module 12 may include sensor electronics configured to process sensor information, such as sensor data, and generate transformed sensor data and display sensor information. Examples of systems and methods for processing sensor analyte data are described in more detail herein and in U.S. Patents 7,310,544 and 6,931,327 and U.S. Patent Publications 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 herein by reference in their entirety for all purposes.

[0191] See again Figure 1ADisplay devices 110, 120, 130, and / or 140 are configured to display (and / or alarm) displayable sensor information that can be transmitted by sensor electronics module 12 (e.g., in a customized data packet transmitted to the display device based on the respective preferences of the display device). Each of display devices 110, 120, 130, or 140 may include a display such as a touchscreen display 112, 122, 132, / or 142 for displaying sensor information and / or analyte data to a user and / or receiving input from the user. For example, a graphical user interface may be presented to the user for these purposes. In some embodiments, instead of or supplementing a touchscreen display, the display device may include other types of user interfaces, such as a voice user interface, for transmitting sensor information to the user of the display device and / or receiving user input. In some embodiments, one, some, or all of the display devices are configured to display or additionally transmit sensor information as if it were transmitted from the sensor electronics module (e.g., in a data packet transmitted to the respective display device), without requiring any additional forward-looking processing required for the calibration and real-time display of the sensor data.

[0192] In exemplary embodiments of this disclosure, the medical device 136 may be a passive device. For example, the medical device 136 may be an insulin pump for administering insulin to a user, such as... Figure 1B As shown. This insulin pump may need to receive and track glucose values ​​emitted from the analyte sensor system 8 for a variety of reasons. One reason is to provide the insulin pump with the ability to pause or activate insulin administration when the glucose value falls below a threshold. One solution that allows a passive device (e.g., medical device 136) to receive analyte data (e.g., glucose values) without being integrated with the analyte sensor system 8 is to include the analyte data in an advertising message emitted from the analyte sensor system 8. The data included in the advertising message can be encoded so that only a device with identification information associated with the analyte sensor system 8 can decode the analyte data. In some embodiments, the medical device 136 includes, for example, a sensor device 136b that can be attached or worn by a user, which is wired or wirelessly connected to a dedicated monitor or display device 136a to process sensor data and / or display data from the sensor device 136a and / or receive input for operation of the sensor device and / or data processing.

[0193] See further Figure 1AThe plurality of display devices may include custom display devices specifically designed to display certain types of displayable sensor information (e.g., numerical values ​​and arrows in some embodiments) associated with analyte data received from sensor electronics module 12. Analyte display device 110 is an example of such a custom device. In some embodiments, one of the plurality of display devices is a smartphone, such as a mobile phone 120 based on Android, iOS, or other operating systems, and is configured to display a graphical representation of continuous sensor data (e.g., including current and historical data). Other display devices may include other handheld devices, such as tablet computer 130, smartwatch 140, medical device 136 (e.g., insulin delivery device or blood glucose meter), and / or desktop or laptop computers.

[0194] Because different display devices provide different user interfaces, the content of data packets (e.g., the amount, format, and / or type of data to be displayed, alarms, and the like) can be customized (e.g., programmed differently by the manufacturer and / or the end user) for each specific display device. Therefore, in Figure 1A In some embodiments, during a sensor session, multiple different display devices can communicate directly with the sensor electronics module (e.g., the on-skin sensor electronics module 12, which is physically connected to the continuous analyte sensor 10) to enable multiple different types and / or levels of display and / or functionality associated with displayable sensor information, which is described in more detail elsewhere herein.

[0195] like Figure 1A Further explanation indicates that system 100 may also include a wireless access point (WAP) 138, which can be used to couple one or more of the analyte sensor system 8, the plurality of display devices, server system 134, and medical device 136 to each other. For example, WAP 138 may provide Wi-Fi and / or cellular connectivity within system 100. Near field communication (NFC) may also be used between devices in system 100. Server system 134 may be used to collect analyte data from analyte sensor system 8 and / or the plurality of display devices to, for example, perform analysis thereon, generate general or individualized models of glucose levels and distributions, etc.

[0196] Now for reference Figure 3A The diagram depicts system 300. System 300 can be used in conjunction with embodiments of the disclosed systems, methods, and apparatus. For example, Figure 3A The various components described below can be used to provide, for example, in an analyte sensor system and, for example... Figure 1A The diagram shows wireless communication of glucose data between multiple display devices, medical devices, servers, etc.

[0197] like Figure 3AAs shown, system 300 may include an analyte sensor system 308 and one or more display devices 310. Additionally, in the illustrated embodiment, system 300 includes a server system 334, which in turn includes a server 334a coupled to a processor 334c and a storage device 334b. The analyte sensor system 308 may be coupled to the display device 310 and / or the server system 334 via a communication medium 305.

[0198] As will be described in detail herein, the analyte sensor system 308 and the display device 310 can exchange messages via a communication medium 305, which can also be used to transmit 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 smartphones, tablet computers, laptop computers, wearable devices, etc. The display device 310 may also include an analyte display device 110 and a medical device 136. It should be noted here that the GUI of the display device 310 can perform several functions, such as accepting user input and displaying menus and information derived from the analyte data. The GUI can be provided by various operating systems known in the art, such as iOS, Android, Windows Mobile, Windows, Mac OS, Chrome OS, Linux, Unix, gaming platform OS (e.g., Xbox, PlayStation, Wii), etc. In various embodiments, 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 protocol, infrared (IR), radio frequency (RF), 2G, 3G, 4G and / or wired protocols and media.

[0199] In various embodiments, the elements of system 300 may be used to perform the various processes described herein and / or to perform the various operations described herein with respect to one or more of the disclosed systems and methods. Upon review of this disclosure, those skilled in the art will appreciate that system 300 may include multiple analyte sensor systems, communication media 305, and / or server systems 334.

[0200] As mentioned, communication medium 305 can be used to connect or communicatively couple the analyte sensor system 308, display device 310, and / or server system 334 to each other or to a network, and communication medium 305 can be implemented in various forms. For example, communication medium 305 may include Internet connections, such as local area networks (LANs), wide area networks (WANs), fiber optic networks, Internet over power lines, hard-wired connections (e.g., buses), and the like, or any other type of network connection. Communication medium 305 can be implemented using any combination of routers, cables, modems, switches, fiber optics, wires, radio (e.g., microwave / RF links), and the like. Furthermore, communication medium 305 can be implemented using various wireless standards, such as Bluetooth®, BLE, Wi-Fi, 3GPP standards (e.g., 2G GSM / GPR / EDGE, 3G UMTS / CDMA2000, or 4G LTE / LTE-U), etc. Upon reading this disclosure, those skilled in the art will recognize other ways in which communication medium 305 can be implemented for communication purposes.

[0201] Server 334a may receive, collect, or monitor information containing analyte data and related information from analyte sensor system 308 and / or display device 310, such as input in response to analyte data or input received in conjunction with an analyte monitoring application running on analyte sensor system or display device 310. In these cases, server 334a may be configured to receive this information via communication medium 305. This information may be stored in storage device 334b ​​and may be processed by processor 334c. For example, processor 334c may include an analysis engine capable of performing analysis on information that server 334a has collected, received, etc., via communication medium 305. In embodiments, server 334a, storage device 334b, and / or processor 334c may be implemented as a distributed computing network, such as a Hadoop® network, or as a relational database or the like.

[0202] Server 334a may include, for example, an Internet server, router, desktop or laptop computer, smartphone, tablet computer, processor, module, or the like, and may be implemented in various forms, including, for example, integrated circuits or sets thereof, printed circuit boards or sets thereof, or in discrete housings / packages / racks or more thereof. In embodiments, server 334a at least partially directs communications conducted on communication medium 305. These communications include the delivery and / or sending and receiving of messages (e.g., advertisements, commands, or other messages) and analyte data. For example, server 334a may process and exchange messages related to frequency bands, transmission timing security, alarms, etc., between analyte sensor system 308 and display device 310. Server 334a may update information stored on analyte sensor system 308 and / or display device 310, for example, by delivering an application. Server 334a may send / receive information to / from analyte sensor system 308 and / or display device 310 in real time or sporadically. In addition, server 334a can implement cloud computing capabilities for the analyzer sensor system 308 and / or display device 310.

[0203] Figure 3B System 302 is depicted, which includes examples of additional aspects of this disclosure that can be used in conjunction with an implementation of an analyte sensor system. As illustrated, system 302 may include an analyte sensor system 308. As shown, analyte sensor system 308 may include an analyte sensor 375 coupled to sensor measurement circuitry 370 for processing and managing sensor data (e.g., in...). Figure 1A (This can also be specified by reference numeral 10). The sensor measurement circuit 370 can be coupled to the processor / microprocessor 380 (e.g., it can be...). Figure 1A (Part of item 12 in the document). In some embodiments, processor 380 may perform part or all of the functions of sensor measurement circuitry 370 for acquiring and processing sensor measurement values ​​from sensor 375. Processor 380 may be further coupled to radio unit or transceiver 320 (e.g., which may be...). Figure 1A The section of item 12 is used to transmit sensor data and receive requests and commands from external devices such as display device 310, which can be used to display or additionally provide sensor data (or analyte data) to the user. As used herein, the terms "radio unit" and "transceiver" 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 (e.g., which may be a storage unit). Figure 1A (Part 12 of the project) and Real-Time Clock (RTC) 380 (e.g., could be Figure 1A (Part of Item 12) is used for storing and tracking sensor data.

[0204] As mentioned above, wireless communication protocols can be used to transmit and receive data between the analyte sensor system 308 and the display device 310 via communication medium 305. These wireless protocols can be designed for wireless networks optimized for periodic, small data transmissions (which may be transmitted at low rates if necessary) to and from multiple devices within proximity (e.g., a personal area network (PAN)). For example, one such protocol can be optimized for periodic data transmissions, where the transceiver can be configured to transmit data in short intervals and then enter a low-power mode in longer intervals. The protocol may have low overhead requirements for normal data transmission and for initially setting up the communication channel (e.g., by reducing overhead) to reduce power consumption. In some embodiments, burst broadcast schemes (e.g., one-way communication) can be used. This eliminates the overhead required for acknowledgment signals and allows for periodic transmissions consuming very little power.

[0205] The protocol can be further configured to establish communication channels with multiple devices while implementing interference avoidance schemes. In some embodiments, the protocol can utilize an adaptive isochronous network topology, which defines various time slots and frequency bands for communication with several devices. The protocol can therefore modify its transmission window and frequency in response to interference and support communication with multiple devices. Thus, the wireless protocol can use a time-frequency division multiplexing (TDMA) based scheme. The wireless protocol can also employ direct sequence spread spectrum (DSSS) and frequency hopping spread spectrum schemes. Various network topologies can be used to support short-range and / or low-power wireless communication, such as peer-to-peer, star, tree, or mesh network topologies, such as Wi-Fi, Bluetooth, and Bluetooth Low Energy (BLE). The wireless protocol can operate in various frequency bands, such as the open ISM band, for example, 2.4 GHz. Furthermore, to reduce power consumption, the wireless protocol can adaptively configure the data rate according to power consumption.

[0206] See further Figure 3B 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 connectivity interface 315 (which in turn includes a transceiver 320), a storage device 325 (which stores the analyte sensor application 330 and / or additional applications), a processor / microprocessor 335, a graphical user interface (GUI) 340 that can be rendered using the display 345 of the display device 310, and a real-time clock (RTC) 350. A bus (not shown here) may be used to interconnect various components of the display device 310 and to transfer data between these components.

[0207] Display device 310 can be used to alert and provide sensor information or analyte data to the user, and may include a processor / microprocessor 335 for processing and managing sensor data. 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. Display device 310 may further include a radio unit or transceiver 320 coupled to other components of display device 310 via a connectivity interface 315 and / or a bus. Transceiver 320 can be used to receive sensor data and to send requests, instructions, and / or data to analyte sensor system 308. Transceiver 320 may further employ a communication protocol. Storage device 325 may also be used to store the operating system for display device 310 and / or custom (e.g., proprietary) applications designed for wireless data communication between the transceiver and display device 310. Storage device 325 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. Instructions can be executed by processor 335 to control and manage transceiver 320.

[0208] In some embodiments, when using standardized communication protocols, commercially available transceiver circuitry can be utilized, incorporating processing circuitry to handle low-level data communication functions, such as data encoding management, transmission frequency, handshake protocols, and the like. In these embodiments, processors 335 and 380 do not need to manage these activities; instead, they provide the required data values ​​for transmission and manage advanced functions such as power-on or power-off, setting the rate of transmitted messages, etc. Instructions and data values ​​for performing these advanced functions can be provided to the transceiver circuitry via a data bus and transmission protocol established by the manufacturer of transceivers 320 and 360.

[0209] Components of the analyte sensor system 308 may require periodic replacement. For example, the analyte sensor system 308 may include an implantable sensor 375, which can be attached to a sensor electronics module containing sensor measurement circuitry 370, a processor 380, a storage device 365, a transceiver 360, and a battery (not shown). The sensor 375 may require periodic replacement (e.g., every 7 to 30 days). The sensor electronics module may be configured to be powered and operational for a much longer period than the sensor 375 (e.g., up to three to six months or more) until the battery needs replacement. Replacing these components can be difficult and requires the assistance of trained personnel. Reducing the need to replace these components, specifically the battery, significantly improves the convenience and cost of using the analyte sensor system 308, including for the user. In some embodiments, when the sensor electronics module is first used (or, in some cases, reactivated once the battery has been replaced), it can be connected to the sensor 375 and a sensor session can be established. As will be further described below, there may be a process for initially establishing communication between the display device 310 and the sensor electronics module when the module is first used or reactivated (e.g., when the battery is replaced). Once communication has been established between the display device 310 and the sensor electronics module, they can remain in communication periodically and / or continuously for the lifetime of several sensors 375, until, for example, a battery replacement is required. Each time a sensor 375 is replaced, a new sensor session can be established. The new sensor session can be initiated by a process performed using the display device 310, and this process can be triggered by a notification of a new sensor via communication between the sensor electronics module and the display device 310, which can be persistent across the sensor session.

[0210] The analyte sensor system 308 typically collects analyte data from sensor 375 and transmits it to display device 310. Data points regarding analyte values ​​can be collected and transmitted over the lifetime of sensor 375 (e.g., within the range of 1 to 30 days or more). New measurements can be transmitted frequently enough to adequately monitor glucose levels. Instead of continuous communication between the transmitting and receiving circuits of each of the analyte sensor system 308 and display device 310, a communication channel can be established between them regularly and / or periodically. Therefore, in some cases, the analyte sensor system 308 can communicate wirelessly with display device 310 (e.g., a handheld computing device, medical device, or proprietary device) at predetermined time intervals. The duration of the predetermined time interval can be selected to be long enough that the analyte sensor system 308 does not consume excessive power by transmitting data more frequently than necessary, but is frequent enough to provide substantially real-time sensor information (e.g., measured glucose values ​​or analyte data) to the display device 310 for output (e.g., via display 345) to the user. Although in some embodiments the predetermined time interval is every five minutes, it should be understood that this time interval can be changed to any desired length of time.

[0211] Continue to refer to Figure 3B As shown in the figure, the connectivity interface 315 interfaces the display device 310 to the communication medium 305, enabling the display device 310 to be communicatively coupled to the analyte sensor system 308 via the communication medium 305. The transceiver 320 of the connectivity interface 315 may include multiple transceiver modules operable according to different wireless standards. The transceiver 320 can be used to receive analyte data and associated commands and messages from the analyte sensor system 308. Additionally, the connectivity interface 315 may, in some cases, include additional components for controlling radio and / or wired connections, such as baseband and / or Ethernet modems, audio / video codecs, etc.

[0212] Storage device 325 may include volatile memory (e.g., RAM) and / or non-volatile memory (e.g., flash memory), and may include any of EPROM, EEPROM, cache memory, or a combination / variation thereof. In various embodiments, storage device 325 may store user input data and / or other data collected by display device 310 (e.g., input from other users collected via analyzer sensor application 330). Storage device 325 may also be used to store large amounts of analyzer data received from analyzer sensor system 308 for later retrieval and use, such as for trend determination and alert triggering. Additionally, storage device 325 may store analyzer sensor application 330, which, when executed using, for example, processor 335, receives input (e.g., via conventional hard / soft keys or touchscreen, voice detection, or other input mechanisms) and allows users to interact with analyzer data and related content via GUI 340, as will be described in further detail herein.

[0213] In various embodiments, a user can interact with the analyte sensor application 330 via a GUI 340, which may be provided by a display 345 of the display device 310. For example, the display 345 may be a touchscreen display that accepts various gestures as input. The application 330 can process and / or present analyte-related data received by the display device 310 according to various operations described herein, and present this data via the display 345. Additionally, the application 330 can be used to acquire, access, display, control, and / or interface with analyte data and related message transmission and processing associated with the analyte sensor system 308, as described in further detail herein.

[0214] Application 330 can be downloaded, installed, and initially configured / set up on display device 310. For example, display device 310 may obtain application 330 from server system 334 or from another source accessible via a communication medium (e.g., communication medium 305), such as an app store or the like. After installation and setup, application 330 can be used to access and / or interface with analyte data (e.g., whether stored on server system 334, locally from storage device 325, or from analyte sensor system 308). With the aid of illustration, application 330 may present a menu containing various controls or commands that can be executed in conjunction with the operation of analyte sensor system 308 and one or more display devices 310. Application 330 can also be used to interface with or control other display devices 310, for example, to transmit or make analyte data available to it, including, for example, by directly receiving / sending analyte data to another display device 310 and / or sending instructions for connecting the analyte sensor system 308 and another display device 310, as will be described herein. In some embodiments, application 330 can interact with other applications on the display device to retrieve or provide relevant data, such as other health data.

[0215] The analyte sensor application 330 may include various code / functional modules, such as display modules, menu modules, list modules, etc., as will become clear from the various functional descriptions herein (e.g., in conjunction with the disclosed methods). These modules may be implemented individually or in combination. Each module may include a computer-readable medium and have computer-executable code stored thereon, such that the code is operatively coupled to and / or executed by a processor 335 (which may include, for example, circuitry for such execution) to perform a specific function (e.g., as described herein with respect to various operations and flowcharts, etc.) in relation to and associated with analyte data. As will be further described below, the display module may present various screens to the user (e.g., via display 345) containing a graphical representation of information provided by the application 330. In other embodiments, the application 330 may be used to display to the user an environment for viewing and interacting with various display devices that can be connected to and connected to the analyte sensor system 308, as well as for interacting with the analyte sensor system 308 itself. Sensor application 330 may contain native applications that are modified with a software design kit (e.g., depending on the operating system) to implement the functionality / features described herein.

[0216] See again Figure 3BThe display device 310 also includes a processor 335. The processor 335 may include processor submodules containing, for example, an application processor that interfaces with and / or controls other components of the display device 310 (e.g., connectivity interface 315, application program 330, GUI 340, display 345, RTC 350, etc.). The processor 335 may include controllers and / or microcontrollers that provide various controls related to device management (e.g., interfaces with buttons and switches), such as a list of available or previously paired devices, information related to measurements, information related to network conditions (e.g., link quality and the like), information related to 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 related to the collection of user input, such as the user's fingerprint (e.g., used to authorize user access to data or for authorization / encryption of data, including analyte data) and the analyte data itself.

[0217] Processor 335 may include circuitry such as logic circuitry, memory, battery and power circuitry, as well as other circuit drivers for peripheral components and audio components. Processor 335 and any of its subprocessors may include logic circuitry for receiving, processing, and / or storing data received and / or input to display device 310 and data to be transmitted or transmitted by display device 310. Processor 335 may be coupled via a bus to display 345, connectivity interface 315, and storage device 325 (including application program 330). Therefore, processor 335 can receive and process electrical signals generated by these corresponding elements and thus perform various functions. For example, processor 335 may access stored content from storage device 325 at the instruction of application program 330 and process the stored content for display and / or output to display 345. Additionally, processor 335 may process stored content for transmission to other display devices 310, analyte sensor system 308, or server system 334 via connectivity interface 315 and communication medium 305. Display device 310 may include... Figure 3B Other peripheral components not shown in detail.

[0218] In other embodiments, processor 335 may further acquire, detect, calculate, and / or store data input by the user via display 345 or GUI 340 or data received from analyte sensor system 308 (e.g., analyte sensor data or related message transmissions) within a time period. Processor 335 may use this input to measure the user's physiological and / or psychological response to data and / or other factors (e.g., time of day, location, etc.). In various embodiments, user responses or other factors may indicate preferences for the use of certain display devices 310 under certain conditions, and / or the use of certain connectivity / transmission schemes under various conditions, as will be described in further detail herein.

[0219] It should be noted that at this time, similarly named elements between the display device 310 and the analyte sensor system 308 may contain similar features, structures, and / or capabilities. Therefore, the description of the display device 310 above can be applied to the analyte sensor system 308 in some cases with respect to these elements.

[0220] In some aspects of the systems, apparatuses, and methods according to this disclosure, health-related and non-health-related data are aggregated, structured, and / or transformed to intelligently generate outputs that include the construction, display, and control of new analytical data for the devices of the system and other systems. Such health-related data may include glucose and related data (e.g., insulin, meals, activity, etc.), and non-health-related data may include location data, user demographic data, etc. Embodiments of such aspects of the invention are perceived to improve the operation of the system, for example, by reducing the complexity of data processing and data transmission between devices, reducing the amount of data to be stored and manipulated, and thereby accelerating the performance of the system as described herein. Furthermore, embodiments of such aspects of the invention are envisioned to improve a user's ability to manage their diabetes or other conditions through continuous analyte monitoring. Examples of techniques and tools for generating such outputs on glucose status, trends, history, context, and insights to help users make informed decisions in managing their diabetes are disclosed below. The disclosed techniques, systems, apparatuses, and tools can also be applied to other health conditions.

[0221] In managing diabetes, a growing number of patients using CGM systems want to see more glucose data over time in their living environment, such as how their glucose levels fluctuate during their dietary habits (generally and for specific meals), their lifestyle (e.g., during the workday and at home or at play), physical activity, etc. However, displays are limited in size, resolution, and other technical parameters. Furthermore, even with larger displays, cramming more data onto the screen doesn't always improve the effectiveness of the data display or help users understand the data presented. To address these limitations in CGM systems, data display should be designed and constructed intelligently to avoid information overload and clutter, which leads to misunderstandings, confusion, missed information, or worse, poor decision-making. For example, poor data display can ultimately lead to poor user decisions, which can therefore be detrimental to their glucose management and health.

[0222] Furthermore, while more context-dependent and meaningful data is needed, manufacturers of CGM systems must be mindful of regulations and standards imposed by regulatory bodies such as the Federal Drug Administration (FDA). In some cases, data displayed within an "actionable timeframe," such as a real-time three-hour period, may be subject to certain limitations or requirements, which can affect the classification of CGM devices and related software applications. These regulations and limitations also impact the cost of their target products, software, or services.

[0223] Users of CGM devices and related software require more meaningful displays and graphics that efficiently and intelligently present their health-related data to enable safe and informed decision-making for managing their glucose and health. Data visualization techniques and modified graphics, as described herein, can intelligently present information about a user's glucose status, trends, history, and corresponding contexts, thereby overcoming technical and situational challenges (e.g., legal or regulatory) and providing direct (e.g., decision support) and indirect (e.g., saving users time in managing their diabetes in their daily lives) benefits.

[0224] Glucose pattern visualization As discussed above, the analyte data collected by the analyte sensor system 308 may include raw sensor data. Raw sensor data may not be of much value to a user's unmodified graphical representation, as the user may potentially miss important information hidden within the clutter of large amounts or unmodified raw sensor data. Therefore, the embodiments described herein include systems and methods for constructing data structures or arrangements for analyte data, characterized by features that facilitate the display of analyte data in modified graphical representations to conveniently indicate patterns and / or information valuable to the user's health.

[0225] In some embodiments, the analyte sensor system 308 may generate one or more datasets of analyte data corresponding to analyte measurements at one or more time intervals. For example, in some embodiments, the analyte sensor system 308 may generate datasets corresponding to analyte measurements every 5 minutes. Other time intervals are possible. The analyte sensor system 308 may generate an analyte concentration value for each analyte dataset. The display device 310 may receive the raw analyte concentration values ​​and generate a data structure or arrangement of the analyte data, which in turn may produce a modifiable graphical display. The modifiable graphical display can be efficiently adjusted to change one or more features that can conveniently indicate patterns or other valuable health information to the viewer.

[0226] In some implementation examples, the analyte sensor system 308 or display device 310 processes a dataset to produce a graphical display that can be displayed on the display device 310. This graphical display includes an arrangement of analyte concentration values ​​over multiple time intervals, the arrangement being graphically modified to, for example, indicate one or more patterns in the analyte data. In some instances, the arrangement of analyte concentration values ​​for the graphical display includes a spatial-temporal organization of the analyte concentration values, wherein the analyte concentration values ​​are positioned along a first direction according to a first time scale and along a second direction according to a second time scale. The analyte levels of the analyte concentration values ​​are modifiable and represented in the graphical display by one or more of the following: modifications in the graphical display through the introduction or use of shape, color, shading, gradients of color or shadow, various intensities or contrasts of different shadows, transparency, opacity, buffers, graphical icons, arrows, animations, text, numbers, or gradual fading based on various health parameters, the magnitude of the analyte level, and / or statistical measures associated with the analyte level or a group of analyte levels. In some implementations, an analyte application 330, which can operate on display device 310, processes the dataset to produce a graphical display on display 345, which can be modified or adjusted according to the magnitude and / or measurement of the analyte level.

[0227] Figure 4AThis is a modified graphical display where analyte concentration values ​​are arranged and presented at multiple time intervals to allow a viewer to easily detect patterns in the analyte data across said multiple time intervals. The data structure or arrangement of the analyte data generated by the embodiments described herein may use color, shape, shading, size, or other visual elements to produce a modified graphical display, making pattern detection in the analyte data easier for the viewer. The analyte application 330 may receive intermittent analyte concentration values ​​corresponding to the original dataset and generate a data structure or arrangement of the analyte data capable of producing a modified graphical display, such as graph 400A. Graph 400A illustrates analyte concentration values ​​along 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. Figure 4A In the example shown, the first timescale is an hourly timescale within a day (24-hour cycle), indicating analyte concentration values ​​for a full day or more on the daily timescale. The second timescale is a daily timescale within a week (7 days), indicating analyte concentration values ​​for the entire week or more on the weekly timescale. In the exemplary graph 400A, the concentration of analyte values ​​is shown within a 24-hour cycle within a week, but other time intervals may be used. For example, the first direction 402 may be an hourly timescale within a daily cycle, and the second direction 404 may be a monthly cycle (e.g., days of a specific month), a weekday cycle (e.g., 5 days Monday through Friday), a weekend cycle, or other selected cycles, such as those selected by the user on the user interface of display device 310. Averaging or other numerical / statistical techniques may be used to extend or include additional data. For example, on the daily scale 404, the average of analyte concentration values ​​for a specific day within a specific time period, or other statistically driven data, may be represented as the analyte concentration value for said day (e.g., analyte concentration values ​​for Sundays over the past three months). In this way, the 400A graph or other 7-day / 24-hour periodic graphs are not limited to only the past 7 days' values, and the 400A graph and other graphical displays described herein can be implemented using data from any period selected by the user or system.

[0228] Exemplary graph 400A may be an isometric graph, wherein the magnitude of the analyte concentration value is represented by shapes along vertical axes perpendicular to the first direction 402 and the second direction 404. The size of each shape may correspond to the magnitude of the analyte concentration value. In some embodiments, color may be used to further indicate the magnitude of the analyte concentration value or to convey additional information about the analyte data. In other embodiments, various colors may be used to identify different magnitudes of the analyte concentration value. For example, shading 406, 408, 410, 412, 414, 4116, 418, or yellow if color is used, may be used in regions of graph 400A where the analyte concentration value exceeds a high threshold. Shading 420, 422, 424, and 426 may be used to indicate regions of graph 400A where the analyte concentration value drops below a low threshold. If color is used, red may be used to indicate regions where the analyte concentration value drops below a low threshold. In the arrangement of analyte concentration values ​​in the exemplary graph 400A, a viewer can immediately identify when the analyte concentration value is above a high threshold by observing peaks in the data, or, if color is used, a viewer can observe yellow areas to quickly determine when the analyte concentration value exceeds the high threshold. The arrangement of analyte data as shown in exemplary graph 400A allows the viewer to easily observe patterns in the analyte data. For example, in exemplary graph 400A, regions 406, 408, 410, 412, 414, 416, and 418, corresponding to analyte concentration values ​​around 6 PM, show peaks, or, if color is used, regions 406, 408, 410, 412, 414, 416, and 418 can be shown as darker shades (relative to other regions), indicating that the analyte concentration value tends to rise around 6 PM during the shown period. Similar patterns can be observed if color is used. Observing such patterns in analyte concentration values ​​allows patients or their caregivers to make better decisions in managing the patient's health.

[0229] Figure 4BA graphical representation of the bird's-eye view including graph 400A is shown as graph 400B. Using graph 400B, a user can easily observe patterns in the analyte data. In some embodiments, graph 400A can be displayed interactively on display 345, allowing the user to rotate, distort, deflect, and / or zoom in or out of the displayed graph 400A to manipulate the viewing of graph 400A. In this respect, display 345 can present graph 400A and allow the user to change the display to graph 400B. Similar to graph 400A, graph 400B is modified to identify features in the analyte data by representing the magnitude of analyte concentration values ​​in a shape on a planar graph (e.g., along one or both of the first direction 402 and the second direction 404), such as high analyte concentration levels indicated by the magnified width of the plot for each day at a specific time of day, and low analyte concentration levels indicated by the contracted width of the plot for each day at said specific time. Similar to graph 400A, graph 400B can also be modified to present coloring or other visual elements associated with the features, such as producing a function that allows viewers to determine at a glance when the analyte concentration value is above or below a high or low threshold by observing the modifications displayed graphically in the data.

[0230] Figure 5 This is an exemplary graphical illustration in which analyte concentration values ​​are arranged and presented in a ring graph 500 at multiple time intervals. In such embodiments, a viewer can easily and readily detect one or more patterns in the analyte data across the multiple time intervals based on the features generated by the graph 500. The graph 500 comprises concentric rings, each ring representing an analyte concentration value in a first direction 502 according to a first time scale. The concentric ring structure of the graph 500 allows for illustration of analyte concentration values ​​along a radial direction 504 according to a second time scale. Figure 5 In the example of graph 500 shown, the first timescale along the first direction 502 is an hourly timescale within a day (24-hour cycle), which may indicate, for example, the hourly analyte concentration value, and the second timescale along the second time direction 504 is a daily timescale within a week (7 days), which may indicate, for example, the daily analyte concentration value. In the exemplary graph 500, analyte concentration values ​​are shown over a 24-hour period within a week. Other time intervals may be used.

[0231] 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 a high threshold, a low threshold, and a target range. For example, for a ring 506 representing an exemplary display of analyte concentration values ​​over a 24-hour period on Sunday (or, in some embodiments, a combination of Sundays within a time period), a first shading 506-1 may be used to indicate the time during which the analyte concentration value has fallen below the low threshold, a second shading 506-2 may be used to indicate the time during which the analyte concentration value is within the target range, and a third shading 506-3 may be used to indicate the time during which the analyte concentration value has exceeded the high threshold. In some embodiments, colors may be used in addition to or instead of shading 506-1, 506-2, and 506-3. For example, red may indicate the time during which the analyte concentration value has fallen below the low threshold, white may indicate the time during which the analyte concentration value is within the target range, and yellow may indicate the time during which the analyte concentration value has 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 experimental data.

[0232] The arrangement of analyte data, as shown in exemplary graph 500, allows a viewer to observe patterns within the analyte data. For example, by browsing exemplary graph 500, a viewer can quickly observe that for several days of the week, the analyte concentration values ​​exceed a high threshold around noon.

[0233] In some embodiments, the data structure or arrangement of analyte concentration values ​​may be configured to produce a modified graphical display in the central area 508 of graph 500. For example, one or more additional visual elements may be included in the central area 508 to indicate whether the data corresponds to daytime or nighttime. As described above, the GUI 340 of display device 310 may be configured to receive user input from system 302 via, for example, a touch-sensitive display. When such input is present, the user may touch or indicate a point on any of the concentric rings in graph 500. Subsequently, a measurement of the analyte concentration value corresponding to the touched point may be displayed in the central area 508. In some embodiments, if no input data is received from the user, then an average value or other statistically driven representative data value corresponding to the entire time period shown in graph 500 may be displayed in the central area 508. For example, if the user does not indicate a point on graph 500, then a weekly average of the analyte concentration value may be displayed. In some instances, one or more additional graphical icons may be displayed in the central area 508 to indicate additional information about the analyte concentration values ​​represented in graph 500. The graphic icon may indicate whether the data relates to daytime, nighttime, weekends, weekdays, or other time indications of the graphic data.

[0234] In some embodiments, a user can obtain additional information about a given day by providing input to the analyte sensor application 330, such as by touching one of the rings in the graph 500. Alternative or supplementary graphs 500 may display additional graphs indicating more details corresponding to the day of the touched ring. Figure 6 A modified graphical display illustrating the data structure and arrangement corresponding to analyte concentration values ​​over a time interval is provided. The data structure and arrangement of the analyte concentration values ​​can produce graphs 600A or 600B, where the analyte concentration values ​​are shown in shapes relative to high and low thresholds and target areas. The time interval shown in graphs 600A or 600B can be a 24-hour cycle corresponding to the touched ring in graph 500. Other time intervals can be used. When a user points to a point on graph 500, graphs 600A or 600B can be displayed in parallel with, alternative to, or in conjunction with graph 500. Additionally, the user can point along different points on graph 600A using a pointing device or via a touchscreen, and graph 600A can be updated and modified to display analyte data corresponding to the point indicated by the user in the central area 614 of 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 graph 600A, the user has indicated that they wish to see the analyte data corresponding to 5:00 AM on June 24th by touching the touchscreen or by rotating point 616 on the display of graph 600A. Graph 600B is a modified version of graph 600A, in which the user has indicated that they wish to see the analyte data value corresponding to 9:00 AM on June 24th. The analyte concentration values ​​and corresponding times are therefore modified and updated in the central area 614.

[0235] In graphs 600A or 600B, analyte concentration values ​​exceeding a high threshold can be indicated by protrusions extending outward from the outer periphery of the ring in graph 600A or 600B. Some examples of high threshold protrusions may include outward protrusions 602, 604, and 606. Analyte concentration values ​​below a low threshold can be indicated by protrusions extending inward from the inner periphery of the ring in graph 600A or 600B. Some examples of low threshold protrusions may include inward protrusions 608, 610, and 612. As described above, in some embodiments, a user can touch a point 616 on or along the ring in graph 600A, and the measurement of the analyte concentration value corresponding to the touched point can be displayed in the central area 614 of graph 600A.

[0236] In some embodiments, graphs 600A or 600B may utilize shading, gradients, or colors corresponding to the magnitude of analyte concentration values. For example, graphs 600A or 600B may be generated or modified to indicate analyte concentration values ​​using various intensities and / or contrasts of shading. Shadings 602, 604, 606, and similar shadings may be used to indicate where analyte concentration values ​​exceed a high threshold. The intensity of the shading may correspond to the magnitude of the analyte concentration value. Shadings 608, 610, 612, and similar shadings may be used in regions of graphs 600A or 600B where analyte concentration values ​​are below a low threshold. A neutral shading, such as shading 618, may be used to indicate analyte concentration values ​​within a target range. Those skilled in the art will appreciate that the shadings described above are exemplary and other visual elements incorporating other shading, textures, gradients, and / or colors may be used.

[0237] Figure 7 This 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 ​​can produce a cross-sectional graph 700, in which the analyte concentration values ​​are shown in one or more segments in the curvature direction and the radial direction. In such embodiments, a viewer can easily and readily detect one or more patterns in the analyte data over the multiple time intervals based on the features generated by the graph 700. Graph 700 illustrates the analyte concentration values ​​in a first direction 702. The first direction 702 may be a curvature direction according to a first time scale. Graph 700 also illustrates the analyte concentration values ​​along a second direction 704 according to a second time scale. The second direction 704 may be a radial direction.

[0238] exist Figure 7 In an example of graph 700, the first time scale is a daily time scale along a first direction 702 over a week (7 days), which may, for example, indicate daily analyte concentration values ​​in 7 segments. The second time scale is an hourly time scale over a day (24-hour cycle), which may, for example, indicate hourly analyte concentration values. Other time intervals may be used. Each segment of graph 700 may represent hourly analyte concentration values ​​over a 24-hour cycle, with analyte concentration values ​​for other 24-hour cycles shown adjacent to it. In some embodiments, segments of graph 700 may optionally be separated by one or more buffers 706. The analyte data represented in graph 700 is not limited to analyte data over a 7-day cycle. The merging of analyte data for each day shown may also be used to produce graph 700.

[0239] The 700 curve graph can be shaded or color-coded, as shown above relative to... Figure 5 and 6As described in the embodiments, additional information about the analyte concentration values ​​is conveyed.

[0240] Users can click on any segment of the graph 700 to obtain a specialized view of the time interval corresponding to said segment. In some embodiments, after segment selection, the graph display 700 can be modified to show the remaining segments contracting into the selected segment, wherein only the selected segment is subsequently displayed to provide a graphical display focused on the selected segment. While the remaining segments are in contraction, the combined graph 700 can also display graphs corresponding to high and low analyte data relative to high and low thresholds.

[0241] Figure 8 This is an illustration of a modified graphical display generated from the data structure and arrangement of analyte data across multiple time intervals. The data structure and arrangement of analyte concentration values ​​can produce graph 800, where analyte concentration values ​​are displayed for multiple time intervals on a time scale 802. The magnitude of the analyte concentration values ​​can be represented on the vertical axis 804. The time scale 802 can represent a 24-hour period, but other time periods can be configured and displayed. Each graph 806, 808, 810, and the like represent analyte concentration values ​​over different 24-hour periods. For example, analyte concentration values ​​over a week can be represented by graphs 806, 808, 810, etc. The merging of analyte data for each day can also be used to produce graphs 806, 808, 810, etc. Each graph can visually distinguish analyte concentration values ​​for different time intervals using a shaded area below the curve with varying opacities. Users can point on graph 800 by pointing or via touchscreen, and a pop-up window 812 can be displayed containing measurements of analyte concentration values ​​corresponding to the selected point on graph 800.

[0242] In some embodiments, one or more side labels can be used to visually isolate analyte data and present a more focused view. For example, if graphs 806, 808, 810, and the like represent one week of analyte data, then a set of side labels or buttons 806-1, 808-1, ... 810-1 can be used, wherein activating side label or button 806-1 more clearly displays graph 806 and its corresponding under-curve area, as well as its opacity relative to other displayed analyte data. Unselected analyte data can be shown in a less noticeable shadow. Side label or button 814 can be activated and clearly display all analyte data.

[0243] In some embodiments, one or more buttons or icons may be used to isolate analyte data relative to high and low thresholds. For example, in graph 800, a user may point to the high threshold button 816 via a pointing device or by touching a touchscreen. Graph 800 may be modified to visually distinguish areas of analyte data having values ​​above one or more high thresholds. Visual distinctions may be created by using different shading, gradients, or, where 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 touchscreen. Graph 800 may be modified to visually distinguish areas of analyte data having values ​​below one or more low thresholds. Buttons or icons 816 and 818 may be displayed as pressed, thereby activating their corresponding display, or they may be displayed as not pressed, thereby deactivating their corresponding display. In some embodiments, cumulative information about the analyte data corresponding to the analyte data captured by graph 800 may be displayed. For example, one or more icons or visual elements may be displayed indicating the percentage of analyte data above the high threshold, below the low threshold, and within the high and low thresholds, respectively. The percentage icon can be displayed simultaneously when its corresponding high or low threshold button is pressed. In one embodiment, the percentage icon may be circular, wherein the thickness, color intensity, or opacity of the circle is determined based on the percentage shown at the center of the circle.

[0244] High or low thresholds can be entered by the user or exported from patient data or multiple patient data available to system 302. Multiple thresholds can be entered, defined, or exported for different time intervals, time periods, or dates. This can be done as described above relative to... Figure 5 and 6 The embodiments described use colors to reproduce curve 800.

[0245] Figure 9This 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 ​​can produce graph 900, in which analyte concentration values ​​are shown for multiple time intervals on a time scale 902. The magnitude of the analyte concentration values ​​can be represented on the vertical axis 904. The time scale 902 can represent a 24-hour period, but other time periods can be configured and displayed. Each of the example graphs 906, 908, 910, and the like represents analyte concentration values ​​in different 24-hour periods. For example, analyte concentration values ​​over a week can be represented by graphs 906, 908, 910, etc. The user can point to any part of graph 900 via a pointing device, such as by moving a mouse pointer on graph 900 or by touching the display of a touchscreen displaying graph 900. An icon or overlaid graphical display, such as a pop-up window 912, can be displayed on the graph 900 that the user has pointed to, which displays the measurement of analyte data corresponding to the point selected by the user. If a user clicks on 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, guiding the user to click for more information. If the user clicks on the graphical display 914, additional graphical displays, such as a text box 916, may appear within the area of ​​the graph 900, providing the user with additional information.

[0246] In some embodiments, graphs 906, 908, 910, and the like may be reproduced with different line shapes or styles depending on the reliability 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 expected future analyte data. A graph key 918 and a description of each graph style may be included along with the display of graph 900.

[0247] In some embodiments, one or more buttons or icons can be used to isolate analyte data relative to high and low thresholds. For example, in graph 900, a user can point to a high threshold button or other virtual menu or button option via a pointing device or by touching a touchscreen. Graph 900 can be modified to visually distinguish regions 920 of analyte data having values ​​higher than one or more high thresholds. Visual distinctions can be created by using different shading, gradients, or, where color is used, by using different intensities or gradients of color. Similarly, a user can point to a low threshold button or other virtual menu or button option via a pointing device or by touching a touchscreen. Graph 900 can be modified to visually distinguish regions 922 of analyte data having values ​​lower than one or more low thresholds. Buttons or icons can be displayed as pressed, thus activating their corresponding display, or they can be displayed as not pressed, thus deactivating their corresponding display.

[0248] Figure 10 yes Figure 9 The modified graphical display is illustrated below. Graph 1000 is similar to Graph 900, where the threshold viewing button or other virtual menu or button option is pressed or activated. Areas above one or more high thresholds 1002 and 1004 are visually distinguished by a first-style coloring to indicate the time during which analyte data values ​​have exceeded high thresholds 1002 and 1004. Areas below one or more low thresholds 1006 and 1008 are visually distinguished by a second-style coloring to indicate the time during which analyte data values ​​have fallen below low thresholds 1006 and 1008. (As described above relative to...) Figure 9 The discussion also covered other ways to visually distinguish between high and low offsets in the analyzed data. For example, if color is used, color gradients or different intensities of color can be employed.

[0249] Can be used as Figure 11 The example graph 1100 shown provides a daily breakdown of graphs 906, 908, 910, or the like from graph 900, and similarly, features 602, 604, 606, 608, and the like from graph 600A or 600B. Alternatively, other time intervals may be used. In the exemplary graph 1100, a bar chart is used to view the daily breakdown of analyte data. Axis 1102 indicates time. The magnitude of the analyte concentration values ​​can be represented on the vertical axis 1104. A user can trigger the display of graph 1100 by pointing at a specific graph 906, 908, or 910 via a pointing device or by touching a touchscreen. One or more lines may indicate the range and / or threshold level of the average analyte concentration values ​​used to generate graph 1100. Figure 11In the examples shown, high threshold levels 1002 and 1004 and low threshold levels 1006 and 1008 are displayed on graph 1100.

[0250] Figure 12 This 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 scale graph 1200 to allow a viewer to easily detect one or more patterns in the analyte data over the multiple time intervals. In one embodiment, graph 1200 may utilize different shadings, each shading corresponding to an analyte concentration value above a high threshold, below a low threshold, or a target value. Analyte concentration values ​​from several time intervals (e.g., several days) may be superimposed to form graph 1200. In this context, gradients can be created to indicate patterns over the multiple time intervals depicted in graph 1200. For example, if dark shading 1208 is used to indicate analyte concentration values ​​below a low threshold, and graph 1200 is constructed by superimposing analyte concentration values ​​for a seven-day period between 12:00 AM and 12:00 PM, the gradient of shading 1208 for the period between 3:00 AM and 6:00 AM may indicate a decrease in analyte values ​​during that time period in the seven-day period. Users can easily identify this pattern in the analyte data over the 7-day time period and take appropriate actions to better manage their health. In some embodiments, the graph 1200 may also include an analyte trend graph, with the graph 1202 indicating changes in analyte concentration values.

[0251] In some implementations, graph 1202 may be an analyte level trace overlaid on clock scale graph 1200, such that higher analyte levels are closer to the outer curves of graph 1200 and lower analyte levels are closer to the inner curves of graph 1200, or vice versa. As described, various gradients and / or contrast shading may be used in graph 1200 to represent various analyte level values. Higher analyte levels may be in a first shading 1206, lower analyte levels may be in a second shading 1204, and analyte levels between higher and lower analyte levels may be in a third shading 1208. Analyte level trace 1202 may include the average analyte level of daily analyte concentration values ​​or, alternatively, the current analyte level on an hourly timescale.

[0252] In some embodiments, the most recently detected analyte concentration value or the average of the analyte concentration values ​​may be displayed at the center 1204 of graph 1200. In some embodiments, additional icons may indicate whether the data depicted in graph 1200 corresponds to daytime or nighttime values.

[0253] In some embodiments, the implemented graphical display 1200 can be reproduced on the display 345. The display device 310 can receive input from the user (e.g., a touch on the touchscreen 345) and flip the graph 1200 to show a display graph depicting the percentage of time the user has experienced within the time period depicted in the graph 1200 that is above a high threshold, below a low threshold, or within both of the analyte concentration values.

[0254] Figure 13A The flowchart 1300, illustrating an exemplary method according to some embodiments, describes how system 302 can generate and display modified graphical displays 400A, 400B, 500, 600, 700, 800, 900, 1000, 1100, and 1200. Process 1300 begins at block 1302. At block 1304, analyte sensor application 330 can receive analyte data at display device 310 from continuous analyte sensor device 375 or from sensor measurement circuitry 370. The analyte data received at analyte sensor application 330 may include analyte concentration values ​​associated with analyte measurements over a time period. At block 1306, analyte sensor application 330 can cause processor 335 to process the analyte concentration values ​​at display device 310 to generate an arrangement of analyte concentration values ​​over multiple time intervals. At block 1308, analyte sensor application 330 can cause processor 335 to generate a graph of the arrangement of analyte concentration values. At box 1310, the analyte sensor application 330 may cause the processor 335 to modify the graph to indicate one or more features of the analyte concentration values. For example, modifying the graph to indicate one or more features of the analyte concentration values ​​may modify the graph to indicate one or more patterns of the analyte concentration values. At box 1312, the analyte sensor application 330 may cause the processor 335 to display the modified graph on the display 345 of the display device 310. The method ends at box 1314.

[0255] Figure 13B Instructions for implementation Figure 13AThe flowchart 1306 illustrates an exemplary method for arranging the process identified in block 1306 to process analyte data, such as analyte concentration values, to generate analyte concentration values ​​at multiple time intervals. While this exemplary method is described with the processor 335 of the display device 310 implementing the method, it should be understood that other devices of the system may be configured to implement the method. Process 1306 begins at block 1316. In some embodiments, at block 1318, the processor 335 aggregates groups of analyte concentration values ​​based on time values ​​of analyte concentration values ​​at different times of day. For example, analyte data may be aggregated based on daily, weekly, monthly, or other time periods, such as analyte concentration values ​​grouped at 12:00 PM, 12:10 PM, 12:20 PM, 12:30 PM, etc., every 5, 10, 15, or other time points throughout the day. In some examples, the analyte concentration values ​​may not all align with time values ​​of the same time of day, such as 12:00 PM, 12:01 PM, 11:59 PM. In such an example, processor 335 can correlate analyte concentration values ​​to a specific time point (e.g., 12:00 p.m.) for all values ​​falling within a certain range (e.g., ± 5 minutes).

[0256] At box 1320, processor 335 can be used for... Figure 13A Additional data is used to flag or embed the analyte data, generating a graph at box 1308 or a modified graph at box 1310. Among other graphs, the graphs may include the graphical displays described above for plots 400A, 400B, 500, 600, 700, 800, 900, 1000, 1100, and 1200. The additional data may include flagging or tabulating the analyte data based on: one or more time scales; the relationship between the flagged or tabulated analyte data and one or more sets of high and low thresholds for analyte data in a subject or subject group; contextual information related to the aggregated analyte data collected in box 1318; and any other information that can be later recalled or additionally used to generate or modify the graphical displays of the graphs described above. In some embodiments, the process of flagging or embedding additional data with analyte data is performed after the data analysis, as shown in box 1322.

[0257] At box 1322, processor 335 analyzes the analyte concentration values ​​of the group. In some embodiments, processor 335 may determine the maximum and / or minimum values ​​of the group. In some embodiments, processor 335 may determine the mean, median, standard deviation, or other statistical measures of the group values. Additionally, processor 335 may perform Fourier transforms, Laplace transforms, and / or sampling techniques on the analyte concentration values ​​of the group to help form a modified graphical display indicating patterns in the analyte data, such as in… Figure 13AAt box 1310. In some embodiments, the process at box 1320 is performed after box 1322 on the analyzed groups of analyte concentration values, wherein the analyzed groups of analyte concentration values ​​can be flagged or embedded with additional data for use in modifying the graph at box 1310. For example, the analyzed groups of analyte concentration values ​​may have averages, medians, standard deviations, etc., that exceed predetermined thresholds or predetermined ranges, and can be flagged or embedded with additional data.

[0258] At box 1324, processor 335 arranges the analyzed groups of analyte concentration values ​​based on spatial or temporal parameters associated with the type of the modified graph, as described above with respect to graphs 400A, 400B, 500, 600, 700, 800, 900, 1000, 1100, and 1200. For example, if the graph includes a second time scale, processor 335 may arrange the analyzed groups of analyte concentration values ​​according to their time values ​​for the daytime of the second time scale, such as days of the week, days of the month, selected days of a time period (e.g., weekdays, holidays, or other user-selected time ranges).

[0259] At frame 1326, processor 335 forms a dataset of analytical groups of arranged analyte data. The dataset is configured such that it can be processed by processor 335 to form a graphical display that can be shown on display 345, for example... Figure 13A At box 1308. As described above, the dataset generated in box 1326 is self-referenced and contains data used to... Figure 13A A graphic is generated at frame 1308 or... Figure 13A Information about the modified graphic is generated at box 1310.

[0260] Some advantages of the method and system include the following. The self-referenced dataset (SRDS) generated at box 1326 eliminates the need for processor 335 to search and retrieve necessary information from various parts of system 302 to generate the graphics of boxes 1308 and 1310. Otherwise, for example, without the self-referenced dataset generated at box 1326, processor 335 would have to search, query, and / or retrieve various parts of system 302 each time a user requests a different graphic or requests a modification to the displayed graphic. Therefore, the self-referenced dataset generated at box 1326 improves the operation of system 302 by reducing the complexity of data processing and data transmission between various parts of system 302. For example, using SRDS, the system does not need to store or process additional algorithms, such as pattern recognition algorithms, to produce, for example, displayed output to convey pattern information to the user. In addition, the self-referenced dataset generated at box 1326 reduces the need for... Figure 13AThe amount and frequency of data emitted by frames 1308 and 1310 for the purpose of generating graphical displays are thus reduced. This also reduces the associated processing or drawing algorithms for storage and operation, and increases the performance of system 302.

[0261] Process 1306 ends at box 1328, and further processing is handed over to... Figure 13A Box 1308.

[0262] Figure 13C Instructions for implementation Figure 13A The flowchart 1308 is an exemplary method for generating a graphical representation of analyte concentration values, as identified in block 1308. While this exemplary method is described with the processor 335 of the display device 310 implementing the method, it should be understood that other devices of the system may be configured to implement the method. Process 1308 begins at block 1330. At block 1332, the processor 335 receives user input data relating to the user's desired graphical display. This may include the type of desired graphical display (e.g., text, charts such as bar charts, pie charts, etc., or other charts, and / or graphical displays such as 400A, 400B, 500, 600, 700, 800, 900, 1000, 1100, and 1200, etc., or other graphical displays), and / or the range of graphical displays the user wishes to see relative to one or more timescales of the dataset in which process 1306 has been formed.

[0263] At box 1334, processor 335 may receive hardware or software data relating to display device 310 or display 345. Display data may include, for example, the size, dimensions, or resolution of the available viewing area, available orientation, and available input devices. At box 1336, processor 335 may determine whether the self-reference dataset formed in box 1326 contains all the information necessary to generate the desired graph for the user. As an example, the user may have requested the display of analyte data falling outside the range captured in the self-reference dataset. In these instances, process 1306 may be repeated and a more comprehensive self-reference dataset may be formed. However, in most cases, the self-reference dataset is formed in a manner containing all the necessary information and data for generating the desired graph for the user.

[0264] At box 1338, processor 335 reformats the self-reference dataset based on user input data and display device data, generating a formatted self-reference dataset. For example, if the user's desired display range is smaller than the range of data captured in the self-reference dataset, then at box 1338 processor 335 can filter the data by erasing unwanted or out-of-range data from the self-reference dataset. At box 1340, processor 335 generates a graph of the arrangement of analyte concentration values ​​based on the formatted self-reference dataset. The processing involved at box 1340 may depend on the type of graph selected by the user and the display device data. For example, if the user requires the display range as described above... Figure 4A Given the described graph 400A, the processor 335 can determine the correct scale for generating the graph 400A based on the available viewing area and the orientation of the display device 345.

[0265] Process 1308 ends at box 1342, and further processing is handed over to Figure 13A Box 1310.

[0266] Figure 13D Instructions for implementation Figure 13A The flowchart 1310 illustrates an exemplary method for modifying a graph to indicate one or more features in analyte concentration values, as identified in block 1310. While this exemplary method is described with respect to the implementation of the method by processor 335 of display device 310, it should be understood that other devices of the system may be configured to implement the method. Depending on the graphical display selected by the user, processor 335 may modify the graph generated by process 1308 to indicate one or more features and / or patterns in the analyte data. Furthermore, the modified graph may present the data in a manner that reduces information overload and potential user misinterpretation of the presented data. For example, if the user selects a three-dimensional graph, such as graph display 400A, then certain portions of the illustrated analyte data may obscure other portions of the illustrated data. Process 1310 may detect such instances and modify the illustrated data accordingly, for example, by making portions of the illustrated analyte data transparent in the overlapping area.

[0267] Process 1310 may use color to modify the graph produced by process 1308. For example, process 1310 may add various color shadings to the graphical analyte data relative to one or more sets of high and low thresholds. Process 1310 may utilize flagged or additional embedded information obtained in box 1320 of process 1306 to color-code the graphical data. For example, processor 335 may detect portions of the graphical data corresponding to analyte values ​​that are 20%-30% higher than the high threshold. Yellow or shading may be used to modify the graphical analyte data to indicate these values. If the graphical analyte data in another portion is 40%-50% higher than the high threshold, then a contrasting shading (e.g., a darker shading of a grayscale gradient or a darker shading of yellow in the case of color) may be used to indicate said portion of the analyte data. Processor 335 may query flags or additional embedded data from a reference dataset to detect and modify portions of the graphical data relative to high and low thresholds.

[0268] In some instances, process 1310 may use the statistical analysis obtained in block 1322 of process 1306 to modify the graph produced by process 1308. For example, a self-referenced dataset (SRDS) may contain flags or embedded data indicating which analyte values ​​fall outside the acceptable multiplier of the standard deviation of the analyte data or which analyte values ​​are statistically unreliable. Processor 335 may modify the graph data based on flags derived statistically from the SRDS.

[0269] In some implementations, the SRDS may include flags or embedded information about contexts based on analyte data. Contexts for the analyte data can be obtained or derived from various sources. For example, if an analyte value obtained on a specific day of the week matches a detection of a mobile display device 310 in a restaurant, the SRDS may include flags or embedded information indicating this association. The frequency of correlation between detected analyte data and the context of the data may also be included in the SRDS. The processor 335 may modify the graphical data to include features based on context-based flags found in the SRDS to visually indicate user behavior patterns relative to analyte data over a period of time. Users may make health or diabetes-related decisions in part based on the modified graphical analyte data and the features described therein.

[0270] In some implementations, processor 335 may modify the graphic data based on patterns detected by flags or embedded information in the SRDS. For example, the SRDS may contain flags indicating peaks and troughs in the analyte data. Processor 335 may detect in a two-dimensional graph that, for many concentrated peaks, different segments of the graphic analyte data visually merge together, making these peaks difficult for the viewer to identify. In such cases, processor 335 may add or introduce buffers between the various segments of the graphic analyte data to remedy this situation. Processor 335 may query flags or additional embedded data in the SRDS to detect peaks and troughs in the data and determine if there are patterns where the peaks are graphicly too close together, such that modifying the graphic data to include new or added buffers can facilitate convenient visual interpretation of the graphic data.

[0271] Process 1310 begins at box 1344. Process 1310 then proceeds to a series of decisions, followed by modifications to the graphical data to indicate characteristics in the analyte data. For example, modifying the graph to indicate one or more characteristics in the analyte concentration values ​​may modify the graphical data to indicate one or more patterns of the analyte concentration values. Those skilled in the art will readily recognize that the invention is not limited to the series of decisions and modifications disclosed herein, and that additional series of decisions and modifications can be designed and implemented without departing from the spirit of the invention. Not all disclosed decision and modification steps are required in every embodiment. Depending on the user's desired graphical display, one or more decision and modification steps may be eliminated or additional steps may be added.

[0272] In decision box 1346, processor 335 scans the SRDS to detect the presence of flags or embedded additional data relating to the relationship between the analyte data and one or more high and low thresholds. Various such flags or additional embedded information may be included in the SRDS. For example, analyte data in the SRDS may be flagged or threshold-related, where different time scales within the analyte values ​​of the SRDS may have their own associated thresholds. Analyte data in the SRDS may be flagged based on a percentage or range by which the analyte data exceeds or falls below a high or low threshold. At box 1348, depending on the combination of threshold flags and the type of graph requested by the user, processor 335 modifies the graphical data to indicate features and / or patterns in the analyte data.

[0273] In some implementations, the modification may include using color, color gradient, shadow, various degrees of transparency or opacity, and changing color, gradient, or transparency based on overlap and underlying areas to allow visual detection of features and / or patterns in the analyte data, as described above with respect to modified graphical displays 400A, 400B, 500, 600, 700, 800, 900, 1000, 1100, and 1200.

[0274] In block 1350, processor 335 scans the SRDS to detect the presence of flags or embedded additional data within the SRDS that are relevant to the statistical analysis performed in process 1306. Processor 335 can modify the graphical data based on the flags or embedded additional data in the SRDS, wherein the flags or embedded additional data are based on the statistical analysis. For example, analyte data in the SRDS can be flagged based on the relationship between the analyte data and the standard deviation, mean, variance, or other statistical parameters related to the underlying analyte data. In some embodiments, analyte data in the SRDS can be flagged if it falls outside an acceptable multiplier of the standard deviation of the analyte data. Corresponding graphical modifications to the graphical analyte data can be based on these flags. Alternatively, analyte data within two multipliers of the standard deviation of the analyte data can be flagged for later color-coding of the graphical data.

[0275] If the SRDS contains statistically based flags or embedded information and corresponding graphical modifications, then at box 1352, the processor 335 may modify the graphical data accordingly. In some embodiments, the modifications may include using color, color gradients, shading, various degrees of transparency or opacity to allow visual detection of features and / or patterns in the analyte data, as described above relative to modified graphical displays 400A, 400B, 500, 600, 700, 800, 900, 1000, 1100, and 1200.

[0276] At box 1354, processor 335 can scan the SRDS to detect the presence of flags or embedded additional data related to the context of the analyte data. Some instances of the context of the analyte data may include contextual information related to the user's location when the analyte data is collected (e.g., whether the user is in a restaurant, at a gym, at home, or at work or school, and the frequency of the user's presence at this location), and the relationship between the analyte data and various user activities (e.g., whether the analyte data is collected when the user has just eaten or exercised, or when the user is awake or asleep, whether insulin is taken, and how much insulin is taken). Contextual analyte data can be obtained automatically without user intervention or can be entered by the user.

[0277] Contextual analysis data is not limited to the examples listed herein, and those skilled in the art can easily identify other contextual analysis data that can be flagged, embedded, or otherwise referenced in the SRDS. At box 1356, processor 335 can modify the graphic data based on contextual flags or embedded data in the SRDS. Various graphic modifications corresponding to different contexts can be programmed in process 1310. Contextual modifications may include the use of color, color gradients, shading, and various degrees of transparency or opacity to allow visual detection of features and / or patterns in the analysis data, as described above relative to modified graphic displays 400A, 400B, 500, 600, 700, 800, 900, 1000, 1100, and 1200.

[0278] The graphical modifications in process 1310 are not limited to the examples listed above. Various graphs can be used to modify data to indicate characteristics, patterns, or trends in the analyte data, and to conveniently alert or convey health or diabetes-related data to the user. Processor 335 can use graphics or graphic techniques, such as graphic icons, animations, text or text boxes, fonts and stylized text or numbers, arrows, fade-out effects, or other techniques, to modify graphical data in process 1310.

[0279] At box 1358, processor 335 may scan the flags in the SRDS and the graphics generated by process 1308 to determine whether further modifications to the graphic data could further improve readability, reduce clutter, and better indicate features and / or patterns in the analyte data. For example, as described above, if processor 335 detects numerous concentrated peaks in the graphic data and associated flags in the SRDS, then, depending on the type of graphic data, at box 1360, processor 335 may modify the graphic data by introducing or adding one or more buffers to improve readability and better indicate features and / or patterns in the analyte data. Processor 335 may also analyze the graphic data generated by process 1308 and the flagged data in the SRDS to detect whether overlapping areas are reproduced in a manner that reduces the transmission of information in the graphic data. At box 1360, processor 335 may modify the color, shading, gradient, spacing, or transparency in the overlapping areas to visually distinguish the overlapping areas and improve the ability of the graphic data to convey features, patterns, or trends in the analyte data. Those skilled in the art can easily identify additional analysis of the flag and graphic data, and their associated modifications, to improve the communication of health or diabetes-related data. Process 1310 ends at box 1362, and further processing is handed over to... Figure 13A Box 1312.

[0280] Although in some embodiments the process of generating SRDS, graphic data, and modified graphic data is described relative to past or collected analyte data, the systems and methods of the present invention can be used with future or predicted analyte data or a combination of past, collected, and future analyte data.

[0281] Insulin visualization The embodiments described herein are not limited to generating data structures based on analyte data. Raw data on other compounds relevant to a patient's health can also be received, and the system can generate modified graphical data structures and arrangements based on such data. For example, the system can receive data corresponding to a patient's active insulin (IOB) level and generate modified graphical data structures or arrangements to conveniently indicate useful information about the patient's health. This can be implemented with... Figures 13A-13D The associated methods are used to generate modified graphical displays that are correlated with insulin data.

[0282] Figure 14 This is an explanation of a modified graphical display 1400 derived from the data structure and arrangement of insulin data. Display 1400 may include a ring 1402, where a complete circular ring may represent the duration of insulin action (DIA). An overlying ring 1404 may represent the remaining time for the placement of active insulin. The size of the overlying ring 1404 may be determined as a fraction of the complete circular DIA. For example, if one hour remains in a four-hour DIA, then the remaining time will be 1 / 4 of the total DIA. In this case, the overlying ring 1404 may overly cover only 1 / 4 of the ring 1402. When a user takes a dose of insulin, the overlying ring 1404 overlies the entire ring 1402. As time passes and insulin is metabolized, the overlying ring 1404 gradually decreases. In some embodiments, the ring 1402 and the overlying ring 1404 may be reproduced in different shades to better distinguish them visually. In some embodiments, color is used to visually distinguish them. A graphical representation 1406 corresponding to the remaining time may be shown at the center of the ring 1402. In some embodiments, graphic representation 1406 includes numbers representing the amount of active insulin.

[0283] If the overlying ring 1404 gradually decreases over a long period, this gradual decrease may be difficult for some viewers to discern. In some embodiments, when generating graphic display 1400, the overlying ring 1404 is initially shown to completely overlap with ring 1402, and graphic representation 1406 is shown to correspond to DIA. In short time increments, the size of the overlying ring 1404 decreases rapidly to correspond to the remaining time for the current amount of active insulin. In the same time increment, graphic representation 1406 may be shown decreasing and stabilizing at the current amount of active insulin. For example, if numbers are used for graphic display 1406, these numbers may decrease similarly to a rapid counter countdown and stabilize at the current amount of active insulin. This graphic representation of the overlying ring 1404 and graphic representation 1406 in short time increments helps viewers discern what information graphic display 1400 is conveying.

[0284] The SRDS generated based on insulin data can be flagged according to some embodiments of process 1306 to include appropriate triggers for animation, overlay graphs, and text information, as described above. In some embodiments, when the graphic display 1400 is initiated, processes 1308 and 1310 analyze the SRDS for flags related to the generation of graphic 1400 and modify the graphic generated by process 1308 to produce the modified graphic 1400.

[0285] In some embodiments, the analyte sensor application 330 may be configured to receive event data, which may contain information about a user's actions and activities related to health management or diabetes. For example, the event data may include: meal intake, type of exercise, duration and intensity, and the amount and type of insulin taken. The analyte sensor application 330 may be configured to generate a data structure and arrangement of the analyte data, which in turn can produce a modified graphical display capable of visually representing the relationships between the analyte data, insulin data, and event data and one or more of each other and / or about a time period. For example, based on the visual construct generated from the SRDS, the user of system 302 can conveniently make health-related decisions or detect features and / or patterns without excessive mental activity.

[0286] Figure 15 and 16The modified graphical displays 1500 and 1600, generated from data structures and data arrangements according to embodiments, are described below. Graphical displays 1500 and 1600 include visual elements indicating the relationship between insulin data, analyte data, and event data and one or more of each other and / or with respect to a time period. In various embodiments of the modified graphical displays 1500 and 1600, the display may include one or more of insulin data, analyte data, or event data, wherein these displays may be modified to further display visual elements indicating the relationship between insulin data, analyte data, or event data and one or more of each other or with respect to a time period. These visual elements may be shaped and configured or scaled such that they do not obscure the display of insulin data, analyte data, or event data. Furthermore, the visual elements may be displayed entirely within the display of insulin data, glucose data, or event data.

[0287] The graphical display 1500 may include an analyte trend graph 1502. Time is represented on the horizontal axis 1504. The magnitude of the analyte data is represented on the vertical axis 1506. The analyte trend graph 1502 may be displayed relative to a high threshold 1508 and a low threshold 1510. Although not all embodiments are shown, the analyte trend graph 1502 may be reproduced with various colors, line styles, or shading relative to the high threshold 1508 and low threshold 1510 to visually indicate the relationship between the analyte data and the high threshold 1508 and low threshold 1510. The graphical display 1500 may additionally include an event data display area 1512. Figure 15 In this instance, the event data is not shown in event data display area 1512, but it may exist within it. Instances of event data will be discussed later. Figure 16 As shown, various icons and graphics are displayed in the event data display area 1612. (Return to view) Figure 15 The graphical display 1500 may additionally include a graph of insulin data 1514. The horizontal axis 1516 may represent time. The vertical axis 1518 may represent the magnitude of insulin data. The user can expand or collapse the time periods displayed in the analyte trend graph 1502 and the insulin graph 1514 via different time period labels 1520. The graphical display or icon 1522 may indicate to the user, by changing the orientation of the mobile computing device from portrait to landscape or vice versa, that the user can obtain different visual elements relating analyte data, insulin data, event data, and time. The event display area 1512 may include: a graphical arrangement of event data, including one or more of the following: the amount of carbohydrate intake, the amount of time spent exercising, the amount of calories burned, or heart rate levels reached or associated with a threshold.

[0288] See Figure 16The graphical display 1600 is similar to the graphical display 1500. The event data display area 1612 allows the user to easily access indicators of when the user has taken actions that can be considered relevant to the user's diabetes management. For example, a label or graphical icon 1616 can indicate a meal, or a label or graphical icon 1618 can indicate a period of exercise. The event display area 1612 can be generated and shown to the patient's caregiver for quick access to the patient's diabetes management-related actions. In some embodiments, an array of graphical icons of potential diabetes management-related actions can be presented to the user, and the user can drag and drop them onto the analyte trend graph 1602 or the event display area 1612 to indicate when the user has taken those actions. For example, the user can drag the meal event icon 1616 and drop it onto the analyte trend graph 1602 around 12:00 PM. The event display area 1612 can then be updated to show the graphical icon 1616 corresponding to when the user has eaten around 12:00 PM. Similarly, the user can add an exercise icon around 6:30 PM. In some embodiments, users may also input event information via voice recognition or keyboard input, and the event display area 1612 may be automatically updated based on the user's input, displaying relevant icons such as a meal icon 1616 and an exercise icon 1618.

[0289] Users can also use a pointing device or touchscreen to point to or touch a point on the trend graph 1602 and activate the pop-up window 1620. The pop-up window 1620 may contain more details related to the event data displayed in the event data display area 1612. For example, the pop-up window 1620 may contain the timestamp, type, or amount of meals the user has eaten; the type, intensity, and duration of any exercise the user has performed; some indication of the user's general feelings; and the type and amount of insulin the user has taken. The pop-up window 1620 may contain a graphical arrangement of insulin data, such as insulin data including one or more of the following: bolus or basal insulin doses, bolus insulin administration time, basal insulin administration time, or active insulin values.

[0290] Some implementations of the graphical display 1500 or 1600 may include a chart key. Figure 17 An example of an insulin chart key 1700 is described, which may optionally be generated and displayed together with a graphic display 1500 or 1600. Chart key 1700 may include different types of graphic displays 1702, 1704, 1706, 1708, and 1710 corresponding to the insulin that the user can take; these may include, for example, basal temperature, bolus, extended bolus, continuous bolus, and basal.

[0291] Figure 18The modified graphical display 1800, generated from the data structure and data arrangement according to an embodiment, includes visual elements indicating 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 the horizontal axis 1804. The magnitude of the analyte data is represented on the vertical axis 1806. One or more amounts of active insulin (IOB) data can be represented above or on the analyte trend graph 1802 using one or more arrows 1808 and 1810, wherein the size of arrows 1808 and 1810 corresponds to the amount of active insulin (IOB) indicated by each arrow. Optionally, one or more numerical representations, such as text, of the amount of active insulin (IOB) can be displayed on or above arrows 1808 and 1810.

[0292] In illustrative examples of the use of the modified graphical display 1800, datasets can be constructed to allow for intuitive visualization of the meaning or role of the IOB data they contain and display. For example, instead of just numbers, active insulin is visualized as a downward arrow above a glucose trend chart. This can be intuitive because physiologically it should be understood that insulin causes glucose to drop. The more active insulin there is, the larger the arrow (the greater the downward force). The number of units can also optionally be displayed along with the arrow. In an example use case where a user eats and takes insulin, a potentially useful reminder is that the user may not necessarily need to take more insulin because the insulin has not yet taken effect, which in turn prevents insulin buildup. In the opposite use case, such as if a user forgets to take insulin, the absence of an arrow (or a small arrow) can serve as a reminder that they have forgotten.

[0293] Algorithm visualization and decision support Diabetes can be a complex disease in which patients find themselves constantly making frequent treatment decisions. Therefore, the psychological needs and stress of managing diabetes can be a burden on patients. System 302 can utilize available data to present graphical displays depicting one or more relationships between analyte data and the user's past, present, and future actions to aid in patient analysis and health management.

[0294] Figure 19A and 19BThe modified graphical displays 1900A and 1900B, generated from the data structure and data arrangement according to an embodiment, are illustrated. Graphical displays 1900A and 1900B include visual elements indicating one or more relationships between insulin data and analyte data based on historical, current, and predicted analyte values. Modified graphical display 1900A may include an analyte trend graph 1902. Time is represented on the horizontal axis, and the magnitude of the analyte data is represented on the vertical axis. Graphical display 1900A may include the current value of analyte data 1912. Graphical display 1900A may be an action-based predicted trend graph and may include one or more predicted curve lines 1904, 1906, and 1908 based on user actions. These actions may include, for example, eating, exercising, or not taking any action. Predicted curve lines 1904, 1906, and 1908 may be based on actions the user has already taken or actions the user is considering. Alternatively, the prediction may be depicted as a range 1910 as illustrated in graphical display 1900B. Depending on one or more reliability parameters and the underlying prediction algorithm, graphical displays 1900A and 1900B can be shown as general range predictions similar to hurricane path estimation visualizations, or they can be shown as single or multiple lines. Graphical displays 1900A and 1900B can be modified according to procedure 1310, as described above based on flags in SRDS corresponding to parameters related to the determinism or reliability of the prediction. Such modifications may include fading the prediction range that degrades one or more deterministic parameters. The graphical display of the predictions can visually convey the relationship between a user's actions and their potential impact on the analyte data, thereby alleviating patient stress when making treatment decisions.

[0295] In another implementation, a predictive bolus calculator can be used to visually inform the user about the impact of bolus administration on the future trend of analyte values ​​in the subject. Figure 20 The system may include modified graphical displays 2002, 2004, and 2006, where the recommended (or predetermined) injection amount is represented by graphical display 2008. Graphical display 2010 can depict the current values ​​of the analyte data and an indication of future trends in the analyte data. Graphical displays 2008 and 2010 can interact through user interaction with graphical display 2008 or through actions initiated by system 302. Graphical display 2010 can be modified based on the impact of the recommended (or predetermined) injection amount on the future trend of the analyte values ​​in the body. After such modification, graphical display 2012 can depict the predicted trend of the analyte values ​​resulting from the application of the recommended (or predetermined) injection. In graphical display 2006, graphical displays 2014 and 2016 can revert to their previous shapes 2008 and 2010, respectively.

[0296] Figure 21The modified graphical display 2100 according to an embodiment illustrates a scrollable list depicting user action data and future analyte value trends. In some embodiments, the user may have a graphical interface module including a button 2102 to enable the addition of events (e.g., actions the user has taken, including eating, injections, exercise, stress, etc.). System 302 may generate a modified graphical display that displays a scrollable list view of input events (e.g., meal event 2104 or meal + exercise event 2106) for the current time or for a recent time range, along with one or more snapshots of analyte trend values ​​2108 and 2110 over time periods following the event times. Users can visualize the causal relationship between their actions (input events) and their analyte levels. The user's clinical team can identify patterns and react accordingly to better manage the user's health. Optionally, in some embodiments, algorithms may be used to infer or automatically indicate and / or link multiple events based on patterns in the analyte data to determine one or more trends in the future analyte data.

[0297] Figure 22 This illustration shows a modified graphical display depicting the relationships between multiple complex variables in a simplified display 2200. People with diabetes often have to consider numerous complex variables and their relationships when making decisions about their diabetes management. The modified graphical display 2200 simplifies the mental process associated with analyzing multiple complex variables that influence a person's decision-making. In some embodiments, the current analyte value can be compared to high and low analyte thresholds to generate an analyte score. The amount of active insulin can be compared to high and low active insulin thresholds to generate an IOB score. An insulin status score can be generated by multiplying the analyte score and the IOB score. In some embodiments, other diabetes parameters can be analyzed and a score can be determined for each parameter. The score can be added as an additional multiplier to the insulin status score. These diabetes parameter scores may include, for example, analyte trend scores, GPS location-based scores (e.g., bars or restaurants, or physical locations where past data indicates the influence of the location on the analyte value), food-related scores, physical exercise scores, etc.

[0298] Insulin status scores can be graded and categorized based on the graded scores. In some implementations, the three categories of insulin status scores can be simply: Good (indicating the patient is in a good state regarding diabetes parameters), Attentive (indicating the patient should pay attention and continue monitoring diabetes parameters and make appropriate decisions), and Poor (indicating that corrective actions may be needed to remedy the situation). Display visual element 2200 may include visual elements resembling traffic lights, comprising three circles 2202, 2204, and 2206. Each circle may be filled with a different color, shading, or gradient than the other circles. Depending on the graded insulin score, one of the shadows in traffic light 2200 may be depicted more clearly, similar to the operation of a traffic light. For example, the shading in circle 2206 of traffic light 2200 may indicate a good state, the shading in circle 2204 of traffic light 2200 may indicate attentiveness, and the shading in circle 2202 of traffic light 2200 may indicate a poor state.

[0299] In some implementations, the advance module allows users 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, disease, or other parameters affecting the health management of diabetes patients and glucose levels. For example, users can use swipes on a touchscreen, or otherwise indicate increases or decreases in current or future events, activities, or glucose-related parameters, and view the projected effect on a glucose trend graph in real time. Predictive effects can be generated using models based on a patient population and their glucose-related data, and / or based on time-varying machine learning tailored to a specific user. The advance module helps users make better diabetes-related decisions by observing the cumulative effect of factors on glucose levels. For example, a patient might observe a current glucose level of 100 mg / dL and consider snacking, going for a run, or taking a small dose of insulin. The advance module would allow users to freely choose the size / content of the snack, the type, duration, or intensity of exercise, and the type and size of the insulin dose to find a desirable combination for appropriate glucose control. The advance module can work in conjunction with other devices. For example, Time Travel on the Apple Watch can trigger predictions.

[0300] Figure 23 This illustrates an example of a modified graphical display 2300 that efficiently provides information about a user's diabetes-related data. Figure 23The glucose trend indicator 2302 represents an offset outside the high threshold 2304 and the low threshold 2306, visually distinguished by using one or more shaded areas 2310 and 2312 below the analyte trend curve 2308. Different coloring can be used, and if color is used, different colors can be employed to differentiate the offset above the high threshold 2304 from the offset below the low threshold 2306.

[0301] In some embodiments, the trend graph 2308, which replaces or supplements the analyte value, can depict a simpler graphical representation of the current and future analyte values ​​2314. For example, it can depict a numerical display of the current analyte value 2316 and a graph 2318 predicting the future trend of the analyte value. In some embodiments, the graph 2314 can be teardrop-shaped. The graph indicating the prediction can be a triangle 2318. The direction or orientation of the triangle 2318 can correspond to the prediction of the future analyte value. For example, a triangle 2318 pointing sharply upwards can indicate a prediction of a sharp increase in analyte concentration. A triangle 2318 pointing moderately upwards can indicate a prediction of a moderate increase in analyte concentration. A triangle 2318 pointing horizontally can indicate a prediction of no significant change in analyte concentration. A triangle 2318 pointing moderately downwards can indicate a prediction of a moderate decrease in analyte concentration. A triangle 2318 pointing sharply downwards can indicate a prediction of a significant or marked decrease in analyte concentration. Those skilled in the art may also envision the same or similar correlation between the orientation of triangle 2318 and the prediction of analyte concentration.

[0302] The analyte trend display 2304 can convey analyte concentration values ​​over a 24-hour period or other time interval selected by the user or automatically selected by the system 302. An analyte trend graph 2320 can be generated using a curve of analyte concentration values ​​against time. The trend graph 2320 can be depicted in relation to a high threshold 2321 and a low threshold 2322. The offset above the high threshold 2321 can be depicted by coloring the area below the curve between the trend graph 2320 and the high threshold line 2321. Examples of areas colored above the high threshold in the display 2304 include areas 2324 and 2326. The offset below the low threshold line 2322 can be depicted by coloring the area below the curve between the trend graph 2320 and the low threshold line 2322. Examples of areas colored below the low threshold in the display 2304 include areas 2328 and 2330.

[0303] Interactive UI display Some graphical displays depicting glucose, insulin, or diabetes-related data can be too cluttered for scientific viewing. This invention proposes a user-friendly, neat, and easily understandable modified graphical display.

[0304] Figure 24A This section describes a modified graphical display with a collapsible design layout, allowing users to see more details. Users can view one or more modified graphical displays at a time or all at once when desired. For example, modified graphical display 2402 depicts a three-hour analyte trend graph 2410 in an expanded view and IOB data 2412 in a collapsed view. Users can click or touch the collapsed IOB view 2412 and obtain an expanded IOB view 2414 in modified display 2404. Users can click or touch the expanded analyte trend graph 2410 and obtain a collapsed view 2416 in modified display 2406 or a collapsed view 2420 in modified display 2408. Some data depictions can be cycled through various display formats to depict the same data in multiple easy-to-understand formats. For example, users can click to expand IOB view 2414 to obtain different graphical representations 2418 of the IOB data, as shown in modified graphical display 2408. Subsequent user clicks or touches can collapse IOB view 2418 back to IOB view 2412, as shown in the modified display 2402.

[0305] Figure 24B and 24C The illustration describes a display screen that presents graphics that can be generated and modified according to embodiments of the disclosed methods and systems. Figure 24B In the examples shown, displays 2422, 2424, 2426, and 2428 contain example graphical displays presenting current glucose 2430, a glucose trend graph 2434, or active insulin 2432 information, as well as other health-related information. Features of display 2422 allow user interaction to receive user input (e.g., by touching specific graphical features of the display) and generate additional information based on the selected feature. For example, if the user selects IOB feature 2432, then display 2422 can be modified to produce display 2428, where display 2428 presents an enhanced view of the IOB data (e.g., differently formatted in some embodiments, and / or magnified in some embodiments) and descriptive information about what active insulin is and what it means, for example, in the context of the user's current glucose information. Figure 24C In the example shown, the display screen including the graphic display can be operated via a software application icon (e.g., icon 2436) and / or an event or notification display screen 2438 of the operating system of the mobile computing device.

[0306] The modified graphic display of this invention can utilize animation to better convey information. In some embodiments, various animations including pulsation and blinking can be used in combination with the graphic display as described above. Figure 25 This describes a modified graphical display that can use animation to convey health-related information. Various rates and speeds of pulsation or blinking can be used to convey different information. For example, a heartbeat-like pulsation can indicate that the modified graphical display is depicting real-time data. Such animation can present the graphical display in a more dynamic, vivid, and human-like way, thereby eliminating or reducing the possibility of user errors due to misinterpretation of the graphical display. In some embodiments, arrows in the modified graphical display, including the magnetic glass 2502 (a numerical value of the current glucose concentration at the center of the circle and smaller arrows around the perimeter pointing to future glucose value trends) can pulsate at different rates to indicate information. For example, a high-rate pulsation can indicate urgency. In some embodiments, various points on glucose trend graphs 2504, 2506, and 2508 can pulsate at different rates to indicate additional information. For example, the most recent point 2510 on trend graph 2504 can pulsate to indicate the current value. The pulsation can vary at different times of the day, such as at night when the user is sleeping, with a slower pulsation rate. Animating the graphical display can reassure the user that the system is active and currently being monitored. Alternatively, the lack of animation can indicate to the user that the system is offline or that the data in the diagram may be outdated.

[0307] If the modified graphic display includes personalized customizations from the user, the user is more likely to interact with the modified graphic display with interest and attention. Figure 26 The descriptions refer to modified graphical displays 2602, 2604, 2606, and 2608, where users can customize the background image of one or more of these displays to illustrate their health data within a user-selected theme. The background in display 2602 has been customized to Star Wars. ® Background Themes. The background in Display 2604 has been customized with a nature, religious, or inspirational theme. The background in Display 2606 has been modified to reflect or support learning in the SAT exam. The background in Display 2608 has been customized to reflect a retro look and feel. SRDS can be generated using custom background images or other user customizations. When one or more of the graphic displays described above are modified, the custom background image or the user's selected theme can be incorporated into the modified graphic display and presented to the user.

[0308] To improve the system's ability to input user data, various graphical user input interfaces can be used. In some implementations, a graphical keypad 2702 can be used. Figure 27The description allows users to input numeric data into a modified graphical display in system 302 using scroll wheel 2704 and gestures that interact with scroll wheel 2704. Scroll wheel 2704 can be programmed to cycle only through an acceptable range of values. Moving a finger clockwise 2706 on scroll wheel 2704 increases the input value, while moving a finger counterclockwise 2708 on scroll wheel 2704 decreases the input value.

[0309] In a home containing multiple analyte sensor systems 308 or displays 310, the user needs to be able to identify the corresponding device. Some current diabetes monitoring and management systems do not provide visual assistance, requiring these homes to use different colored casings to distinguish different units. The present invention allows for a modified graphical display in which an indication of the source of collected analyte, glucose, or insulin data can be generated and flagged in the appropriate SRDS, and subsequently incorporated and presented to the correct user as part of one or more of the modified graphical displays described above. Figure 28 This is an example of a modified display in which the user's initials are incorporated into the display to identify the source of the analyte data.

[0310] In some implementations, as part of the setup process for a new receiver or a receiver used by a new user, the user will be prompted to select a uniquely identifiable identifier, such as an initial, screen background, color theme, screen saver, animation, or a combination thereof. The user's selection may be displayed as a portion of a modified graphical display as described above. If the initial is selected, for example... Figure 28 If the modified display 2802 contains the first letter 2804, then the first letter 2804 can be displayed in the corner of screen 2802 or in the status bar 2806 of the modified display 2808. A screen saver can be applied when the modified graphic display is not displayed. When a modified graphic display as described above is generated, the selected theme can be flagged in SRDS and applied to physical fonts, backgrounds, etc. When a modified graphic display as described above is generated, the selected animation can also be flagged and referenced in SRDS.

[0311] Other instance graphics generated from SRDS Figure 29The modified graphical display 2900 according to the embodiment is described, wherein the graphical display 2900 can be automatically modified when the user's health status is predicted to be approaching an undesirable state. In the context of, for example, diabetes management, the user's CGM reading can indicate that the user is approaching a hyperglycemic or hypoglycemic condition that can generate an alert. Undesirable health conditions such as hyperglycemia or hypoglycemia can be detected when the analyte concentration value exceeds a hyperglycemic level threshold or drops below a hypoglycemic level threshold. An alarm condition can be triggered when the analyte concentration value exceeds a high threshold or falls below a low threshold. The high and low thresholds for generating alarm conditions can be user-defined, defined by members of the patient's support team, or can be automatically defined by system 302 based on the user's data, profile, habits, past glucose trend values, or other parameters related to diabetes management. The graphical display 2900 can be initially generated to convey diabetes health management data, such as a magnetic glass 2902 and a glucose trend graph 2904 relative to previously defined or default high threshold lines 2908 and low threshold lines 2906. In some cases, the previously defined alarm thresholds may allow too much time to pass before notifying the user. For example, previously defined alarm thresholds may be outdated or based on user health data that is no longer applicable. In these cases, the user may be potentially approaching a critical situation and experience negative health consequences before being notified. To encourage users to take swift corrective action, it is desirable to automatically modify the relevant thresholds linked to alarm conditions to generate one or more alarms in a timely manner. In some embodiments, system 302 may determine the rate at which the concentration of an analyte is approaching a high or low threshold and determine the time it would take for the analyte concentration to reach the threshold. If the determined time is equal to or less than a predetermined safe time, then system 302 may automatically modify the threshold linked to the alarm condition from its previous setting to the current analyte value to immediately trigger the alarm condition, notify the user, and stimulate corrective action.

[0312] For example, a hypoglycemic alarm condition may be preset to trigger an alarm when the user's blood glucose level drops below a low threshold 2906 corresponding to a decrease in blood glucose level of 70 mg / dL or more. A graphical display 2900 is generated, depicting an analyte trend curve 2904 and a low threshold line 2906, along with other relevant diabetes management data, such as a magnetic glass display 2902. Blood glucose readings and other data obtained regarding the user's condition can enable system 302 to predict whether modifications to the previously set alarm condition are desirable. For example, the user's analyte measurement and event data may indicate that the user's blood glucose level is currently 110 mg / dL and is decreasing at a rate of 2 mg / dL per minute. At this rate, the user's blood glucose level could reach the alarm level of 70 mg / dL within approximately 20 minutes. In some cases, delaying the correction action by 20 minutes may be undesirable or unsafe. For example, 20 minutes or more of safe time may be needed to effectively take corrective action and achieve results before the analyte concentration value reaches an unhealthy range. When system 302 determines that the user will reach the threshold in less time than the safe time, the system can overwrite the existing threshold linked to the alarm condition, trigger the alarm condition, and immediately notify the user. System 302 can modify the graphical display 2900 as described above to raise the low threshold level 2906 to a new low threshold level 2910 corresponding to the current blood glucose level of 110 mg / dL. An alarm is immediately generated and the user is notified. The user can take corrective measures to avoid a critical situation.

[0313] Modifications to the graphical display 2900 and threshold 2906 can be accompanied by audible alarms and visual cues to attract attention and inform the user of the changes. For example, the low threshold line 2906 can move upwards to its new position 2910, with the movement of the threshold line accompanied by an audible alarm and a flashing or sweeping motion of line 2906 to its new position 2910. An arrow 2912 can point in the direction of movement and flash, pulsate, or otherwise draw attention to the change.

[0314] Figure 30The modified graphical displays 3002, 3004, 3006, 3008, and 3010, generated from the data structure and data arrangement according to the embodiment, illustrate this. These graphical displays 3002, 3004, 3006, 3008, and 3010 contain visual elements indicating the range of analyte data. System 302 can automatically define various ranges of analyte data concentrations by default or via user input. For example, a target range for analyte concentration can be defined as when the analyte concentration value is between a desired high threshold and a desired low threshold. A range can be defined as when the analyte concentration value is between the desired high threshold and a desired low threshold but close to one of those thresholds, such that it may exceed the desired high threshold or fall below the desired low threshold within a short period of time. Exceeding the target range can be defined as when the analyte concentration value has exceeded the high threshold or fallen below the low threshold. The high and low thresholds used to determine the range of analyte data can be compiled based on anonymized data and / or analyte data from other users located in similar positions to the user. The target range, the range of concern, and the area outside the target range can be user-defined or automatically defined by System 302 based on guidelines from a healthcare organization or authority. For example, the target range can be defined from American Diabetes Association (ADA) guidelines as a fasting blood glucose level less than 100 mg / dL and a 2-hour postprandial glucose level less than 140 mg / dL. In some implementations, analyte concentrations exceeding 20% ​​of ADA guidelines can be considered within the range of concern. For example, an analyte concentration below 80 mg / dL when fasting is considered within the target range; an analyte concentration between 80 mg / dL and 100 mg / dL when fasting is considered within the range of concern; and an analyte concentration exceeding 100 mg / dL is considered outside the target range.

[0315] Graphical displays 3002, 3004, 3006, 3008, and 3010 illustrate the magnitude of analyte data on the vertical axis and time on the horizontal axis. When generating graphical displays 3002, 3004, 3006, 3008, and 3010, various visual techniques can be used to modify the analyte data to indicate its range. Graphical display 3002 illustrates a modified graphical display of the magnitude of the analyte concentration value against time, wherein the graph is modified with varying contrast or line style to illustrate the range of the analyte data. In other embodiments, color coding can be used to distinguish between target, attention, and out-of-target ranges. The self-reference dataset used to generate display 3002 can be modified, where analyte data are flagged by indicators of their range (e.g., target, attention, and out-of-target). When generating graphical display 3002, each flag can be assigned a visual indicator of line style, contrast, thickness, or other distinguishing features, and subsequent pixels on display 3002 can be generated based on these indicators. In Example 3002, analyte data within the target range can be flagged and displayed as line style 3012. Analyte data within the attention range can be flagged, and its corresponding flag is associated with line style 3014. Analyte values ​​outside the target range can be flagged, and their corresponding flags can be assigned line style 3016. As described, other visual indicators, such as color, gradient, other line styles, or animations, can be used. Visual indicators associated with attention or outside the target range can be selected to quickly attract and draw attention to the information being conveyed. For example, a darker contrast line 3016 can be used to indicate values ​​outside the target analyte range.

[0316] Graphical display 3004 is similar to graphical display 3002. Analyte data within the target range can be further indicated by a rectangle 3018 surrounding the target analyte value. Analyte values ​​within the attention range can be highlighted using a shaded area below the curve in style 3020. Analyte values ​​exceeding the target analyte value can be highlighted using a shaded area below the curve in style 3022 (different from style 3020) to provide visual distinction and attract the user's attention.

[0317] Graphical display 3006 is similar to graphical display 3004. Analyte values ​​within the target range have been subtracted and are not graphically highlighted to indicate the presence of analyte values ​​in the attention and outside the target range, which may indicate health problems and may require attention and corrective action. Graphical display 3006 allows the user to view analyte values ​​3024 within the attention range and analyte values ​​3026 outside the target range. Graphical displays 3008 and 3010 use an adaptive target area technique to modify the graphical display to account for analyte data changes expected regardless of the presence or absence of diabetes. For example, a non-diabetic patient experiences a similar blood glucose level spike after a meal as a diabetic patient. For example, graphical display 3008 can be modified to adjust the attention area 3028 based on event data obtained from the user and / or sensors. Such adjustments may be necessary to avoid unnecessarily alerting the user. For example, if a meal event is detected, a rise in the user's blood glucose level is expected and normal. The attention area 3028 within the relevant time range can be adjusted to account for the expected rise in blood glucose levels, for example, by coloring the area under the curve in attention area 3028 with the same shading used for target analyte values. Graphical display 3010 uses the same adaptive target area technique as described with respect to display 3008; however, analyte values ​​within the target range have been subtracted and are not illustrated to further highlight and draw attention to analyte values ​​within attention area 3030 and those outside the target range 3032.

[0318] Figure 31The illustration describes a modified graphical display generated from the data structure and data arrangement according to an embodiment, wherein graphical displays 3102, 3104, 3106, 3108, 3110, and 3112 include visual elements indicating the status of the analyte monitoring system, the user's health status, trends, alarms, or other data related to the user's health. The illustrated graphical display may, for example, use an inverted or dark background 3114 to increase contrast and improve readability. An updated current analyte value reading 3116 may be displayed via a display number, such as 100 mg / dL. An analyte trend indicator 3118 may be nested adjacent to the updated current glucose 3116. The analyte trend indicator 3118 includes an arrow 3117 surrounded by a circle 3122, the direction of which indicates a future trend in the analyte data. The circle 3122 surrounding the arrow 3117 may be filled with a coloring style suitable for indicating a trend or direction of future analyte values ​​and / or for providing contrast to the background 3114 to improve readability. In some embodiments, the trend indicator 3118 includes a fading ring 3119 surrounding the circle 3122. A textual 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., "within range and stable"). The display 3102 may include an analyte graph 3124, in which the magnitude of the analyte concentration value is plotted on a vertical axis and time is plotted on a horizontal axis. A point 3126 may indicate the current analyte value on the analyte graph 3124. The point 3126 is surrounded by a fading ring, which in some embodiments may pulsate at the same rate as and be reproduced in the same pattern as the fading ring 3119 of the analyte indicator 3118. The analyte graph 3124 also depicts a high threshold line 3128 corresponding to the upper range of desired analyte concentration values. The graph 3124 also depicts a low threshold line 3130 corresponding to the lower range of desired analyte concentration values.

[0319] Display 3104 is similar to display 3102. The user's current glucose level 3116 has reached 200 mg / dL, the upper range of the desired analyte concentration value. The trend indicator 3118 has been updated to indicate the current and characteristic trend of the analyte concentration value. The arrow 3117 has been updated to point moderately upwards. The circle 3122 has been updated and filled with a coloring style 3132 different from the coloring style of 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 reproduced in a style 3134 different from the line style 3128 to draw attention to the high current value of the analyte concentration. In some embodiments, the different styles of line 3134 may include reproducing the line in a bolder, higher contrast style to draw the user's attention. The point 3126 has been updated and reproduced in a style 3136 different from the style used to generate point 3126 to further draw attention to the high value of the analyte concentration. Dots 3136 and circles 3132 can be reproduced in the same pattern, and the dilution rings surrounding them can pulsate at the same rate to draw attention to high analyte concentration values. In some embodiments, the high threshold line 3134 can pulsate at the same rate as dots 3136, circles 3132, or the dilution rings surrounding them.

[0320] Display 3106 is similar to display 3102. The user's current glucose level 3116 has dropped to 54 mg / dL, the lower limit of the desired analyte concentration value. The trend indicator 3118 has been updated to indicate the current and future trends of the analyte concentration value. The arrow 3117 has been updated to change shape and point significantly downward. The circle 3122 has been updated and filled with a coloring style 3138 different from the coloring style of circle 3122 to draw attention to the current low analyte concentration value. The text description 3120 has also been updated with appropriate text to indicate that the analyte concentration value is low and continues to decrease rapidly. The low threshold line 3130 has been updated and reproduced in a style 3140 different from the line style 3130 to draw attention to the low current value of the analyte concentration. In some embodiments, the different styles of line 3140 may include reproducing the line in a bolder, higher contrast style to draw attention. Point 3126 is updated and reproduced in pattern 3142, different from the pattern used to generate point 3126, to further draw attention to low analyte concentration values. Point 3142 and circle 3138 can be reproduced in the same pattern, and the dilution rings surrounding them can pulsate at the same rate to draw attention to low analyte concentration values. In some embodiments, the low threshold line 3140 can pulsate at the same rate as point 3142, circle 3138, or the dilution rings surrounding them.

[0321] The above text is relative to Figure 31The user data, numbers, thresholds, graphs, and future predictions described are exemplary, and other user data may trigger different displays, texts, graphs, and / or thresholds without departing from the spirit of the described technology.

[0322] As described, an analyte graph 3124 can display analyte data values, plotting the magnitude of the analyte value over a time period. The current value of the analyte data can be indicated by a pulsation graph 3126, for example, a graph comprising one or two concentric circles that gradually fade in the radial direction. The analyte graph 3124 and the data structure that generates the analyte graph 3124 can be dynamically updated based on the current analyte sensor data. The data structure that generates displays 3102, 3104, 3106, or similar displays can be modified to display one or more pulsation animations, which can be synchronized to further draw the user's attention to information related to health management. Examples of display elements that can be modified or reproduced by pulsation animations include a trend indicator 3118, the current analyte value point 3126, and threshold lines 3128 and 3130.

[0323] Other status information related to the operation of the analyte monitoring system can be conveyed via modified graphical displays 3108, 3110, and 3112. For example, modified graphical display 3108 can indicate via text 3144 and 3146 that the analyte sensor is warming up and how much time remains before the sensor is ready. Status bar 3148 can also provide a visual element of the sensor's status. Graphical displays 3110 and 3112 are modified graphical displays of the status of reporting system 302. For example, graphical display 3110 illustrates a situation where a signal loss has occurred from the glucose sensor. Signal loss can be indicated via text and graphical display element 3150. Analyte curve 3124 no longer displays the current analyte value point 3126. Other information, such as the current analyte concentration 3116 and analyte trend indicator 3118, is also not displayed. Signal loss is indicated and the user is alerted using text, graphical displays, icons, and symbols 3150. In the graphical display 3112, no sensor is detected, and text, graphic symbols and / or icons 3152 are used to indicate that no analyte sensor exists and to invite the user to connect the analyte sensor.

[0324] For ease of explanation and illustration, in some cases, exemplary systems and methods are described in light of a continuous glucose monitoring environment; however, it should be understood that the scope of the invention is not limited to a particular environment, and that those skilled in the art will appreciate that the systems and methods described herein can be implemented in various forms. Therefore, any structural and / or functional details disclosed herein should not be construed as limiting the systems and methods, but rather as providing attributes of one or more representative embodiments and / or arrangements for teaching those skilled in the art to implement the systems and methods, which may be advantageous in other contexts.

[0325] For example, and without limitation, the described monitoring systems and methods may include measuring the concentration of one or more analytes (e.g., glucose, lactate, potassium, pH, cholesterol, isoprene and / or hemoglobin) and / or other blood or body fluid components or their associated concentrations in a subject and / or another party.

[0326] As examples and without limitation, the monitoring systems and methods described herein may include finger prick blood sampling, blood analyte test strips, non-invasive sensors, wearable monitors (e.g., smart wristbands, smartwatches, smart rings, smart necklaces or pendants, exercise monitors, fitness monitors, health and / or medical monitors, clamp monitors, etc.), adhesive sensors, smart textiles and / or clothing incorporating sensors, shoe inserts and / or insoles including sensors, transdermal (i.e., transcutaneous) sensors and / or swallowing, inhalation, or implantable sensors.

[0327] In some embodiments, and without limitation, the monitoring system and method may include information for measuring a subject and / or another party, or information related to a subject and / or another party, in lieu of or other sensors besides those described herein, such as inertial measurement units including accelerometers, gyroscopes, magnetometers, and / or barometers; motion, altitude, position, and / or positioning sensors; biometric sensors; optical sensors including, for example, optical heart rate monitors, plethysmography (PPG) / pulse oximeters, fluorescence monitors, and cameras; wearable electrodes; electrocardiogram (EKG or ECG), electroencephalography (EEG), and / or electromyography (EMG) sensors; chemical sensors; flexible sensors, such as those for measuring tension, displacement, pressure, weight, or impact force; current-measuring sensors, capacitive sensors, electric field sensors, temperature / thermal sensors, microphones, vibration sensors, ultrasonic sensors, piezoelectric / piezoresistive sensors, and / or transducers.

[0328] In this document, the terms “computer program medium,” “computer-usable medium,” and “computer-readable medium,” and variations thereof, are used to generally refer to transient or non-transitory media, such as main memory, memory cell interfaces, removable storage media, and / or channels. These and other various forms of computer program media or computer-usable / readable media may relate to loading one or more sequences of one or more instructions onto a processing device for execution. These instructions implemented on the medium may be generally referred to as “computer program code,” “computer program product,” or “instructions” (which may be grouped as computer programs or other groups). When executed, such instructions may cause a computing module or its processor, or a processor connected thereto, to perform the features or functions of this disclosure as discussed herein.

[0329] Various embodiments have been described with reference to specific example features of the embodiments. However, it will be apparent that various modifications and changes can be made to the specification without departing from the broader spirit and scope of the various embodiments set forth in the appended claims. Therefore, this specification and drawings should be viewed in an illustrative rather than restrictive sense.

[0330] Although the invention has been described above with respect to various exemplary embodiments and implementations, it should be understood that the applicability of the various features, aspects, and functionalities described in one or more of the individual embodiments is not limited to the specific embodiments described therewith, but can be applied individually or in various combinations to one or more other embodiments of this application, whether or not such embodiments are described and whether or not such features are presented as part of the described embodiments. Therefore, the breadth and scope of this application should not be limited by any of the foregoing exemplary embodiments.

[0331] Unless otherwise expressly stated, all terms and phrases used in this application, and their variations thereof, should be interpreted as open-ended, contrary to limitation. Examples of the foregoing: the term “comprising” should be understood to mean “including but not limited to”, etc.; the term “example” is used to provide illustrative examples of the items discussed, not an exhaustive or limiting list thereof; the term “a” should be understood to mean “at least one,” “one or more,” etc.; and adjectives such as “conventional,” “traditional,” “usual,” “standard,” “known,” and similar terms should not be interpreted as limiting the described items to items available within a given time period or at a given time, but should actually be understood to cover conventional, traditional, usual, or standard techniques now known or available at any time in the future. Similarly, while this document refers to techniques that would be obvious or known to a person skilled in the art, such techniques encompass those techniques that are obvious or known to a person skilled in the art now or at any time in the future.

[0332] In some cases, the presence of broadened words and phrases such as one or more, at least, but not limited to, or other similar phrases should not be construed as implying a narrower intent or need in instances where such broadened phrases may not exist. The use of the term "module" does not imply that the components or functions described or claimed as part of the module are configured within a common encapsulation. In fact, any or all of the various components of a module, whether control logic or other components, may be combined in a single encapsulation or maintained individually and may be further distributed across multiple groups or encapsulations or across multiple locations.

[0333] Furthermore, the various embodiments described herein are for the purpose of illustrating block diagrams, flowcharts, and other descriptions. As will be understood by those skilled in the art upon reading this document, the illustrated embodiments and various alternatives thereof can be implemented and are not limited to the illustrated examples. For instance, the block diagrams and their accompanying descriptions should not be construed as requiring a specific architecture or configuration.

Claims

1. An analyte monitoring system, comprising: A continuous analyte sensor, configured to measure the analyte concentration of a host computer; Sensor electronics module, the sensor electronics module being configured to: Receives a current from the continuous analyte sensor indicating the concentration of the analyte; Data is analyzed based on the current. The analyte data is transmitted directly to the first display device using a wireless transmitter; as well as The analyte data is transmitted directly to the second display device using the wireless transmitter. The first display device includes a smartwatch; and The second display device includes a smartphone.

2. The system of claim 1, wherein the first display device is configured to receive the analyte data and generate a first graphical user interface to display a first visual representation of the analyte data.

3. The system of claim 2, wherein the second display device is configured to receive the analyte data and generate a second graphical user interface to display a second visual representation of the analyte data.

4. The system according to claim 3, wherein: The first display device generates the first graphical user interface without requiring additional processing of the analyte data via the first display device; and The second display device generates the second graphical user interface when additional processing of the analyte data is performed via the second display device.

5. The system according to claim 3, wherein the first graphical user interface and the second graphical user interface are generated by performing additional processing on the analyte data through the first display device and the second display device, respectively.

6. The system of claim 3, wherein the first graphical user interface and the second graphical user interface are generated without additional processing of the analyte data via the first display device and the second display device, respectively.

7. The system according to claim 1, wherein: The analyte data is transmitted to the first display device in the form of a first data packet; The analytical data is transmitted to the second display device in the form of a second data packet; and The content of the first data packet is different from the content of the second data packet.

8. The system according to claim 7, wherein the format of the first data packet is different from the format of the second data packet.

9. The system according to claim 1, wherein: The analyte data is transmitted to the first display device in the form of a first data packet; The analytical data is transmitted to the second display device in the form of a second data packet; and The contents of the first data packet and the second data packet are the same.

10. The system of claim 9, wherein the format of the first data packet is different from the format of the second data packet.

11. The system of claim 1, wherein the sensor electronics module is configured to attempt to communicate with the first display device and the second display device in a predetermined order to transmit the analyte data to the first display device and the second display device.

12. The system of claim 11, wherein the sensor electronics module is configured to attempt to communicate with the first display device before attempting to communicate with the second display device.

13. The system of claim 12, wherein the failure of the sensor electronics module to communicate with the first display device automatically triggers the sensor electronics module to attempt to communicate with the second display device.

14. The system of claim 1, wherein the sensor electronics module is configured to simultaneously attempt to communicate with the first display device and the second display device to transmit the analyte data to the first display device and the second display device.

15. The system of claim 1, wherein the first display device and the second display device are each configured to generate and display alarms based on the analyte data in a predetermined order of the first display device and the second display device.

16. The system of claim 1, wherein the first display device and the second display device are simultaneously configured to generate and display an alarm based on the analyte data.

17. The system of claim 3, wherein the format of the first visual representation is different from the format of the second visual representation.

18. The system of claim 17, wherein the content of the first visual representation is the same as the content of the second visual representation.

19. The system of claim 17, wherein the content of the first visual representation is different from the content of the second visual representation.

20. A method comprising: The analyte concentration in the main unit is measured using a continuous analyte sensor; The sensor electronics module receives a current from the continuous analyte sensor indicating the concentration of the analyte; The sensor electronics module generates analyte data based on the current; The analyte data is transmitted directly to the first display device using a wireless transmitter that communicates with the sensor's electronic module. as well as Using the wireless transmitter, the analyte data is directly transmitted to the second display device, wherein: The first display device includes a smartwatch; and The second display device includes a smartphone.

21. The method of claim 20, wherein the first display device receives the analyte data and generates a first graphical user interface to display a first visual representation of the analyte data.

22. The method of claim 21, wherein the second display device receives the analyte data and generates a second graphical user interface to display a second visual representation of the analyte data.

23. The method according to claim 22, wherein: The first display device generates the first graphical user interface without requiring additional processing of the analyte data via the first display device; and The second display device generates the second graphical user interface when additional processing of the analyte data is performed via the second display device.

24. The method of claim 22, wherein the first graphical user interface and the second graphical user interface are generated by performing additional processing on the analyte data via the first display device and the second display device, respectively.

25. The method of claim 22, wherein the first graphical user interface and the second graphical user interface are generated without additional processing of the analyte data via the first display device and the second display device, respectively.

26. The method of claim 20, wherein: The analyte data is transmitted to the first display device in the form of a first data packet; The analytical data is transmitted to the second display device in the form of a second data packet; and The content of the first data packet is different from the content of the second data packet.

27. The method of claim 26, wherein the format of the first data packet is different from the format of the second data packet.

28. The method of claim 20, wherein: The analyte data is transmitted to the first display device in the form of a first data packet; The analytical data is transmitted to the second display device in the form of a second data packet; and The contents of the first data packet and the second data packet are the same.

29. The method of claim 28, wherein the format of the first data packet is different from the format of the second data packet.

30. The method of claim 20, wherein the sensor electronics module attempts to communicate with the first display device and the second display device in a predetermined order to transmit the analyte data to the first display device and the second display device.

31. The method of claim 30, wherein the sensor electronics module attempts to communicate with the first display device before attempting to communicate with the second display device.

32. The method of claim 31, wherein the failure of the sensor electronics module to communicate with the first display device automatically triggers the sensor electronics module to attempt to communicate with the second display device.

33. The method of claim 20, wherein the sensor electronics module simultaneously attempts to communicate with both the first display device and the second display device to transmit the analyte data to both the first display device and the second display device.

34. The method of claim 20, wherein the first display device and the second display device each generate and display an alarm based on the analyte data in a predetermined order.

35. The method of claim 20, wherein the first display device and the second display device simultaneously generate and display an alarm based on the analyte data.

36. The method of claim 22, wherein the format of the first visual representation is different from the format of the second visual representation.

37. The method of claim 36, wherein the content of the first visual representation is the same as the content of the second visual representation.

38. The method of claim 36, wherein the content of the first visual representation is different from the content of the second visual representation.

39. A system comprising: A continuous analyte sensor, the continuous analyte sensor being configured to obtain glucose data of the host; A wireless transmitter configured to receive glucose data from the continuous analyte sensor and transmit the glucose data to a processing module; The processing module is further configured to receive the subject's insulin data, the subject's glucose data, and the subject's event data, and to generate a graphical display on a mobile computing device. The processing module further modifies the graphical display to show visual elements indicating the relationship between the insulin data, the glucose data, the event data, and one or more of them or with time.

40. The system of claim 39, wherein the event data comprises one or more of insulin administration, carbohydrate intake, or exercise.

41. The system of claim 39, wherein the insulin data comprises an active insulin value, and the visual element comprises a colored ring indicating the active insulin and an estimated time remaining for the active insulin.

42. The system of claim 39, wherein the visual element includes a trend graph of the glucose data and an interactive pop-up window associated with a region or feature of the trend graph, the interactive pop-up window being presented when a user selects the region or feature of the trend graph on the graphical display, wherein the presented pop-up window includes at least some of the insulin data or the event data.

43. The system of claim 42, wherein the presented display window is configured to display a graphical arrangement of the insulin data, including one or more of the following: insulin bolus or basal dose, bolus insulin administration time, basal insulin administration time, or active insulin value.

44. The system of claim 42, wherein the presented pop-up window is configured to display a graphical arrangement of the event data, including one or more of the following: amount of carbohydrate intake, amount of time spent exercising, amount of calories burned, or heart rate level at or associated with a threshold.

45. The system of claim 39, wherein the visual element includes arrows corresponding to insulin data and glucose readings containing glucose trends corresponding to glucose data, wherein the arrows are displayed close to the trend graph and modified to indicate the effect of insulin data on the glucose data.

46. ​​The system of claim 39, wherein the visual element includes trend graphs of past glucose data and future glucose data, wherein the future glucose data is determined based on the subject's insulin data and action data.

47. The system of claim 39, wherein the visual element comprises: The first graph shows a depiction of the current value of the glucose data and an indication of the future trend of the glucose data. A second graph, representing the amount of insulin, is interactive with the first graph to depict the potential impact of the amount of insulin on the indication of future trends in the glucose data.

48. The system of claim 39, wherein the processing module is further configured to: Generate one or more datasets, each based on the actions of the subject, and predict glucose data trends based on the actions of the subject. The visual elements include scrollable lists, each containing a graph based on one or more modifications of the one or more datasets.

49. The system of claim 39, wherein the processing module is further configured to: The current glucose level is compared with high and low glucose thresholds and a glucose score is generated. The current active insulin is compared with high and low insulin thresholds and an IOB score is generated. Insulin status is generated by multiplying the glucose score and the IOB score; and The insulin score is graded in one of several categories.

50. The system of claim 49, wherein the plurality of categories includes good, attention, and bad.

51. The system of claim 50, wherein the visual element comprises a colored display, wherein each plurality of categories is associated with a different color, and the color depicts the insulin score associated with the grade.

52. The system of claim 49, wherein generating the insulin state further comprises multiplying by a trend value.

53. The system of claim 49, wherein generating the insulin state further comprises multiplying by one or more scores based on location, food intake, and exercise.

54. The system of claim 39, wherein the visual element comprises a digital display of the current glucose value and a graph representing a prediction of future trends in the glucose value.

55. The system of claim 39, further comprising: A preliminary module is configured to receive input data from the subject in relation to future event data, wherein the visual elements include a glucose trend graph and are modified accordingly when the input data is modified.

56. The system of claim 39, wherein the visual element comprises a trend graph of glucose, wherein the region between the trend graph and a high glucose threshold is a first color and the region between the trend graph and a low threshold is a second color.

57. The system according to any one of claims 39 to 56, wherein the processing module is 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-reference dataset; and generating the graphical display in an arrangement that is graphically modified to indicate one or more features in the data.

58. A computer-implemented method, comprising: The glucose data of the host are obtained through a glucose monitoring device; The glucose data of the subject is transmitted via a wireless transmitter; Receives insulin data, glucose data, and event data of the subject, and generates a graphical display on a mobile computing device, wherein the graphical display includes the display of one or more of the insulin data, glucose data, or event data; The graphical display is modified to show visual elements indicating the relationship between the insulin data, the glucose data, or the event data and one or more of them or with time, wherein the visual elements are scaled to avoid obscuring the display of the insulin, glucose, or event data.

59. The method of claim 58, wherein the event data comprises one or more of insulin administration, carbohydrate intake, or exercise.

60. The method of claim 58, wherein the insulin data comprises an active insulin value, and the visual element comprises a colored ring indicating the active insulin and an estimated time remaining for the active insulin.

61. The method of claim 58, wherein the visual element comprises a trend graph of the glucose data and an interactive pop-up window associated with a region or feature of the trend graph, the interactive pop-up window being presented when a user selects the region or feature of the trend graph on the graphical display, wherein the presented pop-up window comprises at least some of the insulin data or the event data.

62. The method of claim 61, wherein the presented display window comprises a graphical arrangement of the insulin data, including one or more of the following: insulin bolus or basal dose, bolus insulin administration time, basal insulin administration time, or active insulin value.

63. The method of claim 61, wherein the presented display window comprises a graphical arrangement of the event data, including one or more of the following: amount of carbohydrate intake, amount of time spent exercising, amount of calories burned, or heart rate level at or associated with a threshold.

64. The method of claim 58, wherein the visual element includes arrows corresponding to insulin data and glucose readings containing glucose trends corresponding to glucose data, wherein the arrows are displayed close to the trend graph and modified to indicate the effect of insulin data on the glucose data.

65. The method of claim 58, wherein the visual element comprises a trend graph of past glucose data and future glucose data, wherein the future glucose data is determined based on the subject's insulin data and action data.

66. The method of claim 58, wherein the visual element comprises: The first graph shows a depiction of the current value of the glucose data and an indication of the future trend of the glucose data. A second graph, representing the amount of insulin, is interactive with the first graph to depict the potential impact of the amount of insulin on the indication of future trends in the glucose data.

67. The method of claim 58, further comprising: Generate one or more datasets, each based on the actions of the subject, and a prediction of glucose data trends based on the actions of the subject. The visual elements include scrollable lists, each containing a graph based on one or more modifications of the one or more datasets.

68. The method of claim 58, further comprising: The current glucose level is compared with high and low glucose thresholds and a glucose score is generated. The current active insulin is compared with high and low insulin thresholds and an IOB score is generated. Insulin status is generated by multiplying the glucose score and the IOB score; as well as The insulin score is graded in one of several categories.

69. The method of claim 68, wherein the plurality of categories includes good, attention, and bad.

70. The method of claim 69, wherein the visual element comprises a colored display, wherein each plurality of categories is associated with a different color, and the color depicts the insulin score associated with the grading.

71. The method of claim 68, wherein generating the insulin state further comprises multiplying by a trend value.

72. The method of claim 68, wherein generating the insulin state further comprises multiplying by one or more scores based on location, food intake, and exercise.

73. The method of claim 58, wherein the visual element comprises a digital display of the current glucose value and a graph representing a prediction of future trends in the glucose value.

74. The method of claim 58, further comprising: The entity receives input data related to future event data, wherein the visual element includes a glucose trend curve and the visual element is modified accordingly when the input data is modified.

75. The method of claim 58, wherein the visual element comprises a trend graph of glucose, wherein the region between the trend graph and a high glucose threshold is a first color and the region between the trend graph and a low threshold is a second color.

76. The method of any one of claims 58 to 75, wherein generating and modifying the graphical display comprises: 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-reference dataset; and generating the graphical display in an arrangement that is graphically modified to indicate one or more features in the data.

77. The system according to claim 39, wherein: The processing module is further configured to receive diabetes-related data from the subject and generate an interactive graphical display on the mobile computing device. Viewers can interact with the interactive graphical display.

78. The system of claim 77, wherein the interactive graphical display includes a trend curve of the glucose data and a region between the trend curve and a glucose threshold, wherein regions exceeding a high threshold and regions exceeding a low threshold have different colors, wherein the high threshold and the low threshold can be adjusted by the viewer interacting with the interactive graphical display.

79. The system of claim 77, wherein the viewer is able to interact with the interactive graphical display via a foldable design layout.

80. The system of claim 77, wherein the interactive graphical display further includes one or more animations to convey information.

81. The system of claim 77, wherein the viewer is able to interact with the interactive graphical display by selecting a personalized background image.

82. The system of claim 77, wherein the viewer is able to interact with the interactive graphical display by inputting numerical values ​​via a graphics wheel.

83. The method of claim 58, further comprising: The device receives diabetes-related data from the subject and generates an interactive graphical display on the mobile computing device, wherein a viewer can interact with the interactive graphical display.

84. The method of claim 83, wherein the interactive graphical display includes a trend curve of the glucose data and a region between the trend curve and a glucose threshold, wherein regions exceeding a high threshold and regions exceeding a low threshold have different colors, wherein the high threshold and the low threshold can be adjusted by the viewer interacting with the interactive graphical display.

85. The method of claim 83, wherein the viewer is able to interact with the interactive graphical display via a foldable design layout.

86. The method of claim 83, wherein the interactive graphical display further includes one or more animations to convey information.

87. The method of claim 83, wherein the viewer is able to interact with the interactive graphical display by selecting a personalized background image.

88. The method of claim 83, wherein the viewer is able to interact with the interactive graphical display by inputting numerical values ​​via a graphics wheel.

89. A system comprising: A continuous analyte sensor, configured to obtain analyte measurements of the subject; A wireless transmitter configured to receive analyte measurements from the continuous analyte sensor; as well as An analyte data processing module, operable on a mobile computing device wirelessly connected to the wireless transmitter, is configured to: Receive at least a portion of the measured values ​​of the analyte; A self-reference dataset is generated in part based on measurements of the analytes; One or more graphical displays are generated based on the self-reference dataset; Modify the self-reference dataset; Based on the modified self-reference dataset, one or more modified graphical displays are shown.

90. The system of claim 89, wherein the analyte data processing module is further configured to: High or low thresholds for analyte concentration in the subject are generated in part based on one or more of the following: health data obtained from the subject, statistical analysis of the analyte measurements, contextual data related to the analyte measurements, health data derived from the subject's profile, or health data obtained from one or more health data databases. Determine the time when the analyte measurement of the subject reaches the high or low threshold; Modify one or more of the high or low thresholds when the time is equal to or less than the predetermined safety time; The self-reference dataset is regenerated to display an animation indicating the change in the threshold.

91. The system of claim 90, wherein the modified graphical display comprises a graph of the analyte measurement against time, and wherein the animation comprises moving a flashing threshold line from a first value to the current analyte value of the subject.

92. The system of claim 89, wherein one or more of the graphical displays include graphs of analyte measurements versus time, and wherein the analyte data processing module is further configured to: Determine one or more expected ranges for the values ​​of the analyte; The self-reference dataset is modified based on the expected range of the analyte values ​​to display the analyte measurements.

93. The system of claim 92, wherein the expected range of the analyte value is based on one or more of inputs from the subject, contextual data relating to the analyte measurement, or health data from a healthcare organization or healthcare authority.

94. The system according to any one of claims 92 and 93, wherein the self-reference dataset is modified to display the analyte measurements related to the expected range using color, line style, animation, shading, gradient, or other visual element differences.

95. The system according to any one of claims 92 to 94, wherein the expected range of the analyzed values ​​includes a target range, a range of attention, and beyond the target range.

96. The system of claim 95, wherein the self-reference dataset is modified to subtract analyte values ​​within the target range and only displays analyte values ​​within the attention range and those outside the target range.

97. The system according to any one of claims 92 to 96, wherein the expected range of the analyzed values ​​is modified based on event data obtained from the subject.

98. The system of claim 89, wherein one or more of the modified graphical displays include a digital display of the current value of the analyte measurement, an indication of a predicted future trend of the analyte measurement, a textual phrase indicating the current state and the predicted future trend of the analyte measurement, a graph of the analyte measurement against time, one or more lines indicating high and low thresholds of analyte concentration in the body, and a graphical representation on the analyte graph indicating the current value of the analyte measurement.

99. The system of claim 98, wherein the self-reference dataset is dynamically modified based on analyte measurements, and the self-reference dataset is further modified to indicate that the current analyte measurement has reached or exceeded a threshold value for the analyte concentration in the body, and wherein the indication of the predicted future trend of the analyte measurement, the threshold line associated with reaching or exceeding the threshold, and the graphical representation of the current analyte value on the analyte graph consistently change styles and pulsate.

100. The system of claim 98, wherein the analyte data processing module is further configured to generate one or more audible alarms when an analyte threshold is reached or exceeded.

101. The system of claim 89, wherein the self-reference dataset is modified to display one or more system status messages.

102. The system of claim 89, wherein the self-reference dataset is modified to display a dark background.

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