Systems and methods for health data visualization, and user support tools for continuous glucose monitoring

Abstract

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

Description

Technical Field

[0001] Incorporation by reference of related applications Any and all priority claims identified in the application data sheet, or any corrections thereto, are hereby incorporated by reference into this specification in accordance with the provisions of 37 CFR 1.57. This application claims the benefit of U.S. Provisional Patent Application No. 62 / 374,539, filed on August 12, 2016. The foregoing application is hereby incorporated by reference in its entirety into this specification and is expressly made a part hereof.

[0002] The present disclosure generally relates to the continuous monitoring of analyte values received from an analyte sensor system. More specifically, the present disclosure relates to systems, methods, apparatuses, and devices for generating a dynamic data structure and a graphic display.

Background Art

[0003] Diabetes mellitus is a disease in which the pancreas is unable to produce sufficient insulin (type I or insulin-dependent) and / or insulin is ineffective (type 2 or non-insulin-dependent). In a diabetic state, the victim suffers from hyperglycemia, which causes a series of physiological deformities (renal failure, skin ulcers, or bleeding into the vitreous of the eye) associated with the deterioration of small blood vessels. Hypoglycemic reactions (hypoglycemia) can be induced by accidental overdose of insulin or after normal administration of insulin or glucose-lowering agents with abnormal exercise or insufficient food intake.

[0004] Conventionally, diabetic patients have carried self - monitoring blood glucose (SMBG) monitors, which typically require an uncomfortable finger - prick method. Due to lack of comfort and convenience, diabetic patients usually measure their blood glucose levels only 2 - 4 times a day. Unfortunately, these time intervals are currently wide, and diabetic patients are likely to be alerted too late, to hyperglycemic or hypoglycemic conditions, resulting in dangerous side effects. In fact, not only are diabetic patients less likely to take SMBG values appropriately, but due to the limitations of conventional methods, they would not know whether their blood glucose levels are rising (higher) or falling (lower).

[0005] As a result, various non - invasive, transdermal (e.g., percutaneous) and / or implantable electrochemical sensors have been developed to continuously detect and / or quantify blood glucose levels. Continuous glucose monitors are gaining popularity as an easy way to monitor blood glucose levels. Heretofore, patients have sampled their blood glucose levels several times throughout the day, such as in the morning, around lunch, and in the evening. Blood glucose levels can be measured by taking a small blood sample from the patient and measuring the blood glucose level with a test strip or a blood glucose meter. However, this technique has drawbacks in that patients prefer not to have to take a blood sample and users do not know how the blood glucose levels are between samples throughout the day.

[0006] One potentially dangerous time frame is at night, as a patient's blood glucose level can drop dangerously low during sleep. As a result, continuous glucose monitors are gaining popularity by providing sensors that continuously measure a patient's blood glucose level and wirelessly transmit the measured blood glucose level to a display. This enables the patient or the patient's caregiver to monitor the patient's blood glucose level throughout the day and even set alarms for when the blood glucose level reaches a predetermined level or experiences a defined change.

[0007] First, a continuous glucose monitor wirelessly transmits data related to glucose levels to a dedicated display. The dedicated display is a medical device designed to display glucose levels, trend patterns, and other information to the user. However, as the popularity of smartphones and software applications (apps) running on smartphones has grown, some users prefer not to have to carry a dedicated display. Instead, there are users who prefer to monitor their glucose levels using a dedicated software application that runs on a mobile computing device such as a smartphone, tablet, or wearable device such as a smartwatch or smart glasses. Still other users may prefer the flexibility of having access to glucose and glucose-related data on other mobile or stationary computing devices in addition to the dedicated display. SUMMARY OF THE INVENTION MEANS FOR SOLVING THE PROBLEM

[0008] One embodiment includes a system, the system including a continuous analyte sensor configured to obtain an analyte measurement of a receptor, and a wireless transmitter configured to receive the analyte measurement from the continuous analyte sensor and at least partially process the analyte measurement to generate one or more data sets of analyte data, each data set including an analyte concentration value associated with a time for one or more of the analyte measurements, the wireless transmitter including an energy conservation unit, a data converter unit, a processing unit, and a transmitter unit, and an analyte data processing module operable on a mobile computing device that wirelessly communicates with the wireless transmitter, the analyte data processing module configured to receive and process one or more data sets from the wireless transmitter to generate a graphic display on the mobile computing device, the graphic display including an array of analyte concentration values over a plurality of time intervals graphically modified to show one or more patterns in the analyte data.

[0009] In one aspect of the system, the analyte data processing module is further configured to aggregate the analyte data group, flag the analyte data group based on additional information corresponding to one or more graphic displays, array the flagged group of analyte concentration values, and generate a self-referencing data set from the arrayed group of analyte concentration values.

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

[0011] In one aspect, the context data includes one or more physical locations where the analyte data was obtained, the relationship between the receptor and the physical location, the frequency of visiting the physical location, the meals consumed, the type and intensity of exercise, the type and amount of insulin administered, and data indicating the likelihood that the receptor was asleep or awake when the analyte data was obtained.

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

[0013] In some embodiments, the sample data processing module is further configured to modify the graphic display by scanning a self - reference dataset for a threshold flag, modifying the graphic display based on the threshold flag, scanning a self - reference dataset for a statistical analysis flag, modifying the graphic display based on the statistical analysis flag, scanning a self - reference dataset for a sample context data flag, and modifying the graphic display based on the context data flag.

[0014] In one embodiment, modifying the graphic display includes introducing or using one or more of color, color or shade gradient, transparency, opacity, buffer area, graphic icon, arrow, animation, text, number, and gradual fading.

[0015] In one embodiment, the array includes a spatio - temporal arrangement of sample concentration values positioned along a first direction according to a first time scale and along a second direction according to a second time scale, and the sample level of the sample concentration values is constituted by one or more of shape, color, shade, or size based on the magnitude of the sample level.

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

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

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

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

[0020] In one aspect, higher sample levels are of a first color, lower sample levels are of a second color, and sample levels between higher and lower sample levels are of a third color.

[0021] In one aspect, the sample level trace includes the average sample level of the sample concentration values for a day.

[0022] In one aspect, the trace of the sample level includes the current sample level over an hourly time scale.

[0023] In another aspect, the modification of the graphic display includes color clustering, color or shading gradients, region alignment, or displaying brighter or darker shading of overlapping regions to modify an array of sample concentration values over multiple time intervals.

[0024] In one aspect, one or more patterns indicate sample concentration values regarding high and low sample level thresholds for a receptor.

[0025] In one aspect, the multiple time intervals include 24-hour periods over seven days.

[0026] In one aspect, the graphic display includes an isometric graph plotted over a 24-hour period over seven days.

[0027] In one aspect, the isometric graph can be displayed as a three-dimensional figure.

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

[0029] In another aspect, the graphic display includes a pie chart.

[0030] In one aspect, the graphic display includes one or more line graphs.

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

[0032] In some aspects, the processing further includes aggregating a group of specimen data, flagging the group of specimen data based on additional information corresponding to one or more graphic displays, arranging the flagged group of specimen concentration values, and generating a self-referencing data set from the arranged group of specimen concentration values.

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

[0034] In one aspect, the context data can include one or more physical locations where the sample data was obtained, the relationship between the receptor and the physical location, the frequency of visiting the physical location, the diet consumed, the type and intensity of exercise, the type and amount of insulin administered, and data indicating whether the receptor was asleep or awake when the sample data was obtained.

[0035] In another aspect, generating a graphic of an array of sample concentration values further includes receiving user input including a desired graphic display of the user, receiving display configuration data, regenerating a self - referential data set when the self - referential data set does not include data for forming the desired graphic display, and reformulating the self - referential data set based on the user input and the display configuration data.

[0036] In another aspect, modifying a graphic to show one or more patterns in the sample data can include scanning the self - referential data set for a threshold flag, modifying the graphic based on the threshold flag, scanning the self - referential data set for a statistical analysis flag, modifying the graphic based on the statistical analysis flag, scanning the self - referential data set for a sample context data flag, and modifying the graphic based on the context data flag.

[0037] In one aspect, modifying a graphic includes introducing or using one or more of color, color or shade gradient, transparency, opacity, buffer area, graphic icon, arrow, animation, text, number, and gradual fading.

[0038] In one aspect, the array includes a spatio - temporal arrangement of sample concentration values where the sample 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 sample level of the sample concentration values is constituted by one or more of shape, color, shade, or size based on the magnitude of the sample level.

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

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

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

[0042] In another aspect, the first time scale is hourly and the second time scale is daily, and the modified graphic includes a specimen level trace superimposed across the modified graphic such that higher specimen levels are closer to the outer curve region of the graphic and lower specimen levels are closer to the inner curved region of the graphic, or vice versa.

[0043] In one aspect, the higher specimen level is a first color, the lower specimen level is a second color, and the specimen level between the higher specimen level and the lower specimen level is a third color.

[0044] In one aspect, the specimen level trace includes the average specimen level of the specimen concentration values for one day.

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

[0046] In some aspects, modifying the graphic can include modifying an array of specimen concentration values over multiple time intervals, color clustering, color or shading gradients, region alignment, or brighter or darker shading of overlapping regions.

[0047] In some aspects, one or more patterns indicate specimen concentration values related to high and low specimen level thresholds of a receptor.

[0048] In one aspect, the plurality of time intervals includes a 24-hour period over 7 days.

[0049] In one aspect, the graphic includes an isometric graph plotted over a 24-hour period over 7 days.

[0050] In another aspect, the isometric graph can be displayed as a three-dimensional figure.

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

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

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

[0054] Another embodiment includes a system, the system includes a continuous analyte sensor configured to obtain glucose data of a receptor, and 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 insulin data, glucose data, and event data of the receptor, and generate a graphical display on a mobile computing device, and the processing module further modifies the graphical display to display a visual representation indicating one or more relationships between the insulin data, glucose data, and event data, either with each other or with time.

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

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

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

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

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

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

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

[0062] In another aspect, the visual representation includes a first graphic display that illustrates the current value of the glucose data and an indicator of the future trend of the glucose data, and a second graphic display that represents the amount of insulin, and the second graphic display can interact with the first graphic display for illustrating a possible effect of the amount of insulin on the indicator of the future trend of the glucose data.

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

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

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

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

[0067] In another aspect, generating the insulin state further includes multiplying a trend value.

[0068] In one aspect, generating the insulin state further includes multiplying one or more scores based on position, food intake amount, and exercise.

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

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

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

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

[0073] One embodiment includes obtaining glucose data of a receptor by a glucose monitoring device, transmitting the glucose data of the receptor by a wireless transmitter, receiving insulin data of the receptor, glucose data of the receptor, and event data of the receptor, and generating a graphic display on a mobile computing device, the graphic display including a display of one or more of the insulin data, glucose data, or event data, generating a visual representation showing one or more relationships, either mutual or with time, of the insulin data, glucose data, or event data, and modifying the graphic display to display the visual representation, the visual representation being shaped, configured, or scaled so as not to obscure the display of the insulin data or glucose data or event data, and the visual representation being displayed as a whole within the display of the insulin data, glucose data, or event data, including a method executed by a computer.

[0074] In some aspects, the event data includes one or more of an insulin dosage, a carbohydrate intake, or exercise.

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

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

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

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

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

[0080] In one aspect, the visual representation includes a trend graph of past glucose data and future glucose data, the future glucose data being determined based on the insulin data and operation data of the receptor.

[0081] In another aspect, the visual representation includes a first graphic display illustrating the current value of glucose data and an indicator of the future trend of the glucose data, and a second graphic display representing the amount of insulin, the second graphic display being able to interact with the first graphic display for illustrating a possible effect of the amount of insulin on the indicator of the future trend of the glucose data.

[0082] In some aspects, the method further includes generating one or more data sets based on the operation of the receptor and the prediction of the glucose data trend based on the operation of the receptor, respectively, and the visual representation includes a scrollable list including one or more modified graphs based on the one or more data sets, respectively.

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

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

[0085] In another aspect, the visual representation includes a colored display, each of the plurality of categories is associated with a different color, and the color associated with the ranked insulin score is illustrated.

[0086] In one aspect, generating the insulin state further includes multiplying a trend value.

[0087] In another aspect, generating the insulin state further includes multiplying one or more scores based on position, food intake, and exercise.

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

[0089] In one aspect, the method further includes receiving input data of a receptor related to future event data, the visual representation includes a glucose trend graph, and when the input data is modified, the visual representation is modified accordingly.

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

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

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

[0093] In one aspect, the interactive graphic display includes a trend graph of glucose data having a region between the trend graph and a glucose threshold, the region exceeding a high threshold and a region exceeding a low threshold having different colors, and the high threshold and the low threshold are adjustable by interaction of the viewer with the interactive graphic display.

[0094] In another aspect, a viewer can interact with the interactive graphic display via a scalable design layout.

[0095] In some aspects, the interactive graphic display further includes one or more animations for communicating information.

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

[0097] In some embodiments, a viewer can interact with the interactive graphic display by entering a numerical value via a graphics scroll wheel.

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

[0099] In one aspect, the interactive graphic display includes a trend graph of glucose data having regions between a trend graph and a glucose threshold that have different colors for regions exceeding a high threshold and regions exceeding a low threshold, and the high threshold and the low threshold are adjustable by the viewer's interaction with the interactive graphic display.

[0100] In another aspect, a viewer can interact with the interactive graphic display via a scalable design layout.

[0101] In one aspect, the interactive graphic display further includes one or more animations for communicating information.

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

[0103] In one aspect, a viewer can interact with the interactive graphic display by entering a numerical value via a graphics scroll wheel.

[0104] In one aspect of the system, the graphic display further includes an indicator of the receptor on which the specimen measurement is performed.

[0105] One embodiment includes a continuous sample sensor configured to obtain a measured value of a receptor in a sample, a wireless transmitter configured to receive the measured value of the sample from the continuous sample sensor, and a sample data processing module operable on a mobile computing device that wirelessly communicates with the wireless transmitter. The sample data processing module is configured to receive at least a portion of the measured value of the sample, generate a self-referencing data set based at least in part on the measured value of the sample, generate one or more graphic displays based on the self-referencing data set, modify the self-referencing data set, and display one or more modified graphic displays based on the modified self-referencing data set.

[0106] In one aspect, the sample data processing module is further configured to generate a high or low threshold of the sample concentration in the receptor, determine the time until the measured value of the sample in the receptor reaches the high or low threshold, modify one or more of the high or low thresholds when the time is less than or equal to a predetermined safety time, and regenerate the self-referencing data set to display an animation indicating the change in the threshold, based at least in part on health data obtained from the receptor, statistical analysis of the measured value of the sample, contextual data related to the measured value of the sample, health data derived from the profile of the receptor, or health data obtained from one or more health databases.

[0107] In one aspect, the modified graphic display includes a graph of the measured value of the sample versus time, and the animation includes moving a blinking threshold line from a first value of the receptor to the current sample value.

[0108] In one aspect, one or more of the desired graphic displays includes a line graph of the measured value of the sample versus time, and the sample data processing module is further configured to determine one or more predicted ranges of the sample value and modify the self-referencing data set to display the measured value of the sample based on the predicted range of the sample value.

[0109] In one aspect, the predicted range of the analyte value is based on one or more of the input from the receptor, the context data related to the measured analyte value, or the health data from the medical institution or medical authority.

[0110] In some aspects, the self - reference dataset is modified to use color, line style, animation, shading, gradient, or other visual differentiating factors for displaying the measured analyte value related to the predicted range.

[0111] In one aspect, the predicted range of the analyte value includes a target range, a caution range, and outside the target range.

[0112] In another aspect, the self - reference dataset is modified to subtract the analyte value within the target range and display only the analyte values within the caution range and outside the target range.

[0113] In some aspects, the predicted range of the analyte value is modified based on the event data obtained from the receptor.

[0114] In some aspects, one or more of the modified graphic displays include a numerical display of the current value of the measured analyte, an indicator of the predicted future trend of the measured analyte value, a text phrase indicating the current state and future prediction of the measured analyte value, a graph of the measured analyte value versus time, one or more lines indicating the high and low thresholds of the analyte concentration in the receptor, and a graphic representation of the analyte on the graph indicating the current value of the measured analyte.

[0115] In one aspect, the self - reference dataset is dynamically modified based on the measured analyte value, and the self - reference dataset is further modified to indicate the current measured analyte value that reaches or exceeds the threshold value of the analyte concentration value in the receptor, and the indicator of the predicted future trend of the measured analyte value, the threshold line associated with the threshold value that is reached or exceeded, and the graphic representation of the current analyte value with respect to the analyte graph change style and vibrate together.

[0116] In another aspect, the sample data processing module is further configured to generate one or more audible representation alarms when the sample threshold is reached or exceeded.

[0117] In one aspect, the self - reference dataset is modified to display one or more system status messages.

[0118] In another aspect, the self - reference dataset is modified to display a dark background.

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

Brief Description of the Drawings

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Best Mode for Carrying Out the Invention

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

[0122] Embodiments of the present disclosure are directed to systems, methods, and devices for generating dynamic data structures and graphic displays. In various arrangements described herein, the sample data is glucose data generated by a sample sensor system configured to connect to a display device or the like. As described in detail herein, by implementing aspects of the present disclosure, the graphic display of the sample data can be modified in a simple and efficient manner that shows patterns in the sample data. Further, by implementing aspects of the present disclosure, one or more relationships between glucose data, insulin data, and a user's actions can also be shown simply. Specifically, such aspects of the present disclosure relate to, for example, generating a self-referential data structure and modifying a graphic display based on that data structure to convey information related to diabetes management.

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

[0124] Summary In some embodiments, a system for continuous measurement of an analyte at a receptor is provided. The system can include a continuous analyte sensor configured to continuously measure the concentration of the analyte at the receptor and a sensor electronics module physically connected to the continuous analyte sensor during sensor use. In certain embodiments, the sensor electronics circuit module includes electronics configured to process a data stream associated with the analyte concentration measured by the continuous analyte sensor to generate sensor information, such as, for example, raw sensor data, converted sensor data, and / or any other sensor data. The sensor electronics module may be further configured to generate sensor information customized for each display device such that different display devices can receive different sensor information.

[0125] As used herein, the term "sample" is a broad term and should be given its ordinary and customary meaning to one of ordinary skill in the art (and not limited to a special or customized meaning), and further, without limitation, refers to substances or chemical components in biological fluids that can be analyzed (e.g., blood, interstitial fluid, cerebrospinal fluid, lymph, urine, sweat, saliva, etc.). A sample can include naturally occurring substances, artificial substances, metabolites, and / or reaction products. In some implementations, the sample for measurement by a method or device is glucose. However, without limitation, the following: acarboxyprothrombin; acetoacetic acid; acetone; acetyl CoA; acyl carnitine; adenine phosphoribosyltransferase; adenosine deaminase; albumin; α-fetoprotein; amino acid profile (arginine (Krebs cycle), histidine / urocanic acid, homocysteine, phenylalanine / tyrosine, tryptophan); androstenedione; antipyrine; arabinitol enantiomer; arginase; benzoylecgonine (cocaine); biotinidase; biopterin; c-reactive protein; carnitine; carnosinase; CD4; ceruloplasmin; chenodeoxycholic acid; chloroquine; cholesterol; cholinesterase; β-conjugated 1-hydroxy cholic acid; cortisol; creatine kinase; creatine kinase MM isozyme; cyclosporine A; d-penicillamine; deethylchloroquine; dehydroepiandrosterone sulfate; DNA (acetylation agent 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, Leber hereditary optic neuropathy, MCAD, RNA, PKU, Plasmodium malariae, gonadal differentiation, 21-deoxycortisol); desbutylhalofantrine; dihydropteridine reductase; diphtheria / tetanus antitoxin; erythrocyte arginase; erythrocyte protoporphyrin; esterase D; fatty acid / acyl glycine;Triglyceride; Glycerol; Free β-human chorionic gonadotropin; Free erythrocyte porphyrin; Free thyroxine (FT4); Free triiodothyronine (FT3); Fumarylacetoacetate; Galactose / gal-1-phosphate; Galactose-1-phosphate uridyltransferase; Gentamicin; Glucose-6-phosphate dehydrogenase; Glutathione; Glutathione peroxidase; Glycocholic acid; Glycosylated hemoglobin; Halofantrine; Hemoglobin variant; Hexosaminidase A; Human erythrocyte carbonic anhydrase I; 17-α-hydroxyprogesterone; Hypoxanthine phosphoribosyltransferase; Immunoreactive trypsin; Ketone bodies; Lactate; Lead; Lipoproteins ((a), B / A-1, β); Lysozyme; Mefloquine; Netilmicin; Phenobarbital; Phenytoin; Phytanic acid / pristanic acid; Progesterone; Prolactin; Prolidase; Purine nucleoside phosphorylase; Quinidine; Reverse triiodothyronine (rT3); Selenium; Serum pancreatic lipase; Sisomicin; Somatomedin C; Specific antibodies (adenovirus, antinuclear antibody, anti-zeta antibody, arbovirus, OESK virus, Medina worm, Echinococcus granulosus, Entamoeba histolytica, enterovirus, Giardia lamblia, Helicobacter pylori, hepatitis B virus, herpes virus, HIV-1, IgE (atopic disease), influenza virus, isoprene (2-methyl-1,3-butadiene), Leishmania donovani, Leptospira, measles / mumps / rubella, Mycobacterium leprae, Mycoplasma pneumoniae, Myoglobin, Spirometra mansoni, parainfluenza virus, Plasmodium falciparum, poliovirus, Pseudomonas aeruginosa, respiratory syncytial virus, Rickettsia (scrub typhus), Schistosoma mansoni, Toxoplasma gondii, Treponema pallidum, Trypanosoma cruzi / Langer, vesicular stomatitis virus, bancroftian filariasis, flavivirus (e.g., tick-borne encephalitis, dengue fever, Powassan, West Nile, yellow fever, or Zika virus); Specific antigens (hepatitis B virus, HIV-1), Succinylacetone, Sulfadoxine, Theophylline, Thyrotropin (TSH), Thyroxine (T4), Thyroxine-binding globulin, Trace elements, Transferrin; UDP-galactose-4-epimerase; Urea;Uroporphyrinogen I synthase; vitamin A; white blood cells; and other specimens containing zinc protoporphyrin are similarly considered. Salts, sugars, proteins, fats, vitamins, and hormones that naturally exist in blood or interstitial fluid can also constitute specimens in certain implementations. Specimens can naturally exist in biological fluids, such as metabolites, hormones, antigens, antibodies, etc. Alternatively, specimens can be endogenous or exogenous to the body, such as imaging contrast agents, radioisotopes, chemical agents, fluorocarbon-based synthetic blood, or, without limitation, insulin; glucagon, ethanol; cannabis (marijuana, tetrahydrocannabinol, hashish); inhalants (nitrous oxide, amyl nitrite, butyl nitrite, chlorinated hydrocarbons, hydrocarbons); cocaine (crack cocaine); stimulants (amphetamine, methamphetamine, Ritalin, Cylert, Preludin, Dexedrine, Prestate, Bolarnyl, Sandrex, Plegine); depressants (barbiturates, methaqualone, barium, Librium, Miltown, Serax, Equanil, Tranquilen, etc., psychotropic drugs); hallucinogens (fenciclovir, lysergic acid, mescaline, peyote, psilocybin); narcotics (heroin, codeine, morphine, opium, meperidine, Percocet, Percodan, Tussionex, fentanyl, Darvon, Talwin, Romotil); synthetic narcotics (fentanyl, meperidine, amphetamine, methamphetamine, analogs of fenciclovir, such as ecstasy); anabolic steroids; and nicotine can be introduced into drugs or pharmaceutical compositions. Metabolites of drugs and pharmaceutical compositions are also considered specimens. For example, specimens such as ascorbic acid, uric acid, dopamine, norepinephrine, 3-methoxythyramine (3MT), 3,4-dihydroxyphenylacetic acid (DOPAC), homovanillic acid (HVA), 5-hydroxytryptamine (5HT), and 5-hydroxyindoleacetic acid (FHIAA), as well as intermediates in the citric acid cycle, such as neurochemicals and other chemicals generated in the body, can also be analyzed.;

[0126] Alert In certain embodiments, one or more alerts are associated with the sensor electronics module. For example, each alert may include one or more alert conditions that indicate when each respective alert was triggered. For example, a low blood glucose alert may include an alert condition that indicates a minimum blood glucose value. The alert conditions may also be based on transformed sensor data such as trend data and / or sensor data from multiple different sensors (e.g., the alert may be based on sensor data from both a glucose sensor and a temperature sensor). For example, a low blood glucose alert may include an alert condition that indicates a minimum required trend in the blood glucose value of the receptor that must exist before triggering the alert. As used herein, the term "trend" generally refers to data that indicates some attribute of data acquired over time, such as 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, including transformed or raw sensor data.

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

[0128] In certain embodiments, multiple delivery operations (e.g., each having a respective delivery option) may be associated with a single alert, and displayable sensor information having different content and formats may be sent to respective display devices, for example, in response to a trigger of the single alert. For example, a mobile phone may receive a data package containing minimal displayable sensor information (which may be specifically formatted for display on the mobile phone) while a desktop computer may receive a data package containing most (or all) of the displayable sensor information generated by a sensor electronics module in response to a trigger of a common alert. Advantageously, the sensor electronics module is not coupled to a single display device but rather is configured to communicate directly, systematically, simultaneously (e.g., via broadcast), periodically, cyclically, randomly, on demand, in response to a query, based on an alert or alarm, and / or the like, with a plurality of different display devices.

[0129] In some embodiments, provide a clinical risk alert that combines alert conditions with an intelligent and dynamic estimation algorithm that estimates current or predicted risks with greater accuracy, more rapid timing of pending risks, avoidance of false alarms, and less nuisance to the patient. Generally, the clinical risk alert includes dynamic and intelligent estimation algorithms based on analyte values, rates of change, accelerations, clinical risks, statistical probabilities, known physiological constraints, and / or individual physiological patterns, thereby providing appropriate, clinically safe, and patient-friendly alarms. U.S. Patent Publication No. 2007 / 0208246, which is incorporated herein by reference in its entirety, describes some systems and methods associated with the clinical risk alerts (or alarms) described herein. In some embodiments, the clinical risk alert can be triggered for a predetermined period to enable the user to respond to his / her condition. Further, the clinical risk alert can be deactivated when leaving the clinical risk region so as not to bother the patient with repeated clinical alarms (e.g., visual representations, auditory representations, or vibrations) when the patient's condition is improving. In some embodiments, the dynamic and intelligent estimation determines the likelihood that the patient will avoid clinical risk based on analyte concentration, rate of change, and other aspects of the dynamic and intelligent estimation algorithm. If the likelihood of avoiding clinical risk is minimal or non-existent, the clinical risk alert will be triggered. However, if there is a likelihood of avoiding clinical risk, the system is configured to wait for a predetermined amount of time and re-analyze the likelihood of avoiding clinical risk. In some embodiments, if there is a likelihood of avoiding clinical risk, the system is further configured to provide a target, treatment recommendation, or other information that can assist the patient in actively avoiding clinical risk.

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

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

[0132] In some embodiments, the sensor electronics module is configured to wait for a period of time in response to a receptor-triggered alert (e.g., by pressing or selecting a snooze and / or off function and / or button on the sensor electronics module and / or display device), and then additional alerts are triggered (e.g., in an escalation manner) until one or more alerts are responded to. In some embodiments, the sensor electronics module is configured to send a control signal (e.g., a stop signal) to a medical device associated with an alarm condition (e.g., hypoglycemia) such as an insulin pump, and the stop alert triggers the cessation of insulin delivery via the pump.

[0133] In some embodiments, the sensor electronics module is configured to transmit alert information directly, systematically, simultaneously (e.g., via broadcast), periodically, cyclically, randomly, in response to a request, in response to a query (from the display device), based on an alert or alarm, and / or the like, in response to a receptor-triggered alert (e.g., by pressing or selecting a snooze and / or off function and / or button on the sensor electronics module and / or display device). In some embodiments, the system further includes a repeater that can increase the wireless communication distance of the sensor electronics module, for example, to 10, 20, 30, 50, 75, 100, 150, or 200 meters or more, and the repeater is configured to repeat the wireless communication from the sensor electronics module to a display device located remotely from the sensor electronics module. The repeater can be useful for families with children with diabetes. For example, it allows a parent to carry or place a medium-sized display device in a stationary position at a distance from a child while the child is sleeping in a large house.

[0134] Display device In some embodiments, the sensor electronics module is configured to search for and / or attempt wireless communication with a display device from a list of display devices. In some embodiments, the sensor electronics module is configured to search for and / or attempt wireless communication using a list of display devices in a predetermined and / or programmable order (e.g., ranking and / or escalation), such that a failure to communicate and / or attempt an alarm with a first display device triggers a communication and / or attempt an alarm with a second display device, and so on. In an exemplary embodiment, the sensor electronics module is configured to sequentially use a list of display devices such as (1) a default display device or a custom specimen monitoring device, (2) a mobile phone via text messages to a recipient and / or care provider, voice messages to a recipient and / or care provider, and / or audible and / or visual presentation methods such as 911, (3) a tablet, (4) a smart watch or bracelet, and / or (5) smart glasses or other wearable display devices to search for a recipient or care provider and attempt an alarm.

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

[0136] In some embodiments, a particular display device can communicate wirelessly directly with a sensor electronics module, but intermediate network hardware, firmware, and / or software can be included within the direct wireless communication. In some embodiments, a repeater (e.g., a Bluetooth® repeater) can be used to retransmit transmitted displayable sensor information to locations further away than the immediate range of the telemetry module of the sensor electronics module, and 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) can be used to retransmit transmitted displayable sensor information onto a TV screen in a different format, such as a text message if possible, and the receiver enables direct wireless communication when no substantial processing of the sensor information occurs. In one embodiment, the sensor electronics module directly 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.

[0137] In certain 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, a challenge response protocol, such as password authentication, is provided to authenticate data communication between the sensor electronics module and the display device, the challenge being a request for a password and a valid response being the correct password, such that pairing between the sensor electronics module and the display device can be achieved via a password by the user and / or manufacturer. This can, in some cases, be referred to as two-way authentication.

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

[0139] In some embodiments, the display device is configured to query a database in the memory of the sensor electronics module and / or request structured or constructible packages of data content therefrom for certain types of data content, i.e., the data stored within the sensor electronics module is configurable, searchable, pre-determined, and / or pre-packaged based on the display device with which the sensor electronics module is communicating. In some further or alternative embodiments, the sensor electronics module generates displayable sensor information based on its knowledge of which display device should receive a particular transmission. Additionally, some display devices can obtain calibration information and wirelessly transmit the calibration information to the sensor electronics module through automatic input of the calibration information, automatic distribution of the calibration information, and / or an integrated reference specimen monitor incorporated into the display device. U.S. Patent Publications Nos. 2006 / 0222566, 2007 / 0203966, 2007 / 0208245, and 2005 / 0154271, all of which are hereby incorporated by reference in their entirety, describe systems and methods for providing an integrated reference specimen monitor incorporated into a display device and / or other calibration methods that can be implemented using the embodiments disclosed herein.

[0140] Generally, a plurality of display devices (e.g., custom analyte monitoring devices (which may also be referred to as analyte display devices), mobile phones, tablets, smartwatches, reference analyte monitors, drug delivery devices, medical devices, and personal computers) can be configured to wirelessly communicate with a sensor electronics module. The plurality of display devices can be configured to display at least some of the displayable sensor information wirelessly communicated from the sensor electronics module. The displayable sensor information can include sensor data such as raw data and / or transformed sensor data, for example, analyte concentration values, rate of change information, trend information, alert information, sensor diagnostic information, and / or calibration information, etc.

[0141] Analyte Sensor Referring to FIG. 1A, in some embodiments, the analyte sensor 10 includes a continuous analyte sensor, such as a subcutaneous, transdermal (e.g., percutaneous), or intravascular device. In some embodiments, such sensors or devices can analyze multiple intermittent blood samples. The present disclosure includes embodiments of glucose sensors, although such embodiments can be similarly used for other analytes. The glucose sensor can use any known method of glucose measurement, including enzymatic, chemical, physical, electrochemical, spectrophotometric, polarimetric, calorimetric, iontophoretic, radiometric, immunochemical, etc.

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

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

[0144] In certain embodiments, the analyte sensor 10 is an implantable glucose sensor as described with reference to U.S. Patent No. 6,001,067 and U.S. Patent Publication No. US-2005-0027463-A1. In embodiments, the analyte sensor 10 is a transcutaneous glucose sensor as described with reference to U.S. Patent Publication No. US-2006-0020187-A1. In embodiments, the analyte sensor 10 is configured to be implanted within a receptor's lumen or extracorporeally, as described in U.S. Patent Publication No. US-2007-0027385-A1, filed Oct. 4, 2006, co-pending U.S. Patent Publication No. US-2008-0119703-A1, filed Mar. 26, 2007, U.S. Patent Publication No. US-2008-0108942-A1, filed Mar. 26, 2007, and U.S. Patent Application No. US-2007-0197890-A1, filed Feb. 14, 2007. In embodiments, the continuous glucose sensor includes, for example, a transcutaneous sensor as described in U.S. Patent No. 6,565,509 to Say et al. In embodiments, the analyte sensor 10 is a continuous glucose sensor including a subcutaneous sensor as described with reference to U.S. Patent No. 6,579,690 to Bonnecaze et al. or U.S. Patent No. 6,484,046 to Say et al. In embodiments, the continuous glucose sensor includes, for example, a refillable subcutaneous sensor as described with reference to U.S. Patent No. 6,512,939 to Colvin et al. The continuous glucose sensor may include, for example, an intravascular sensor as described with reference to U.S. Patent No. 6,477,395 to Schulman et al. The continuous glucose sensor may include, for example, an intravascular sensor as described with reference to U.S. Patent No. 6,424,847 to Mastrototaro et al.

[0145] Figures 2A and 2B are perspective and side views of a housing 200 that may be used in connection with an implementation of an analyte sensor system 8 according to certain aspects of the present disclosure. The housing 200 includes, in certain embodiments, a mounting unit 214 and a sensor electronics module 12 attached thereto. The housing 200 is shown in a functional position and includes a mounting unit 214 and a sensor electronics module 12 meshed and engaged therein. In some embodiments, the mounting unit 214, also referred to as a housing or sensor pod, includes a base 234 adapted to be secured to a receptor or a user's skin. The base 234 may be formed from various rigid or flexible materials and may include a low profile to minimize protrusion of the device from the receptor during use. In some embodiments, the base 234 is at least partially formed from a flexible material and, unfortunately, may provide a number of advantages over other transcutaneous sensors that may be subject to motion-related artifacts associated with movement of the receptor while the receptor is using the device. The mounting unit 214 and / or the sensor electronics module 12 may be disposed across the sensor insertion site to protect the site and / or provide a minimal footprint (utilization of the surface area of the receptor's skin).

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

[0147] In some embodiments, the contact 238 is mounted on or within an assembly hereinafter referred to as a contact subassembly 236 configured to fit within a base 234 of the mounting unit 214 and the hinge 248 that allows the contact subassembly 236 to pivot between a first position (for insertion) and a second position (for use) relative to the mounting unit 214. As used herein, the term "hinge" is a broad term and includes, without limitation, any of various pivoting, articulating, and / or hinge mechanisms such as adhesive hinges, slide joints, etc., and is used in its ordinary sense to refer to, and the term "hinge" does not necessarily mean a pivot point or fixed point where articulation occurs. In some embodiments, the contact 238 is formed from a conductive elastomeric material such as carbon black elastomer through which the sensor 10 extends.

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

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

[0150] Exemplary Configuration Referring again to FIG. 1A, a system 100 that can be used in connection with implementing aspects of a sample sensor system is illustrated. In some cases, system 100 can be used to implement various systems described herein. System 100 in an embodiment includes a sample sensor system 8 according to a particular aspect of the present disclosure, and display devices 110, 120, 130, and 140. The sample sensor system 8 in the illustrated embodiment includes a sensor electronics module 12 and a continuous sample 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 an embodiment, 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 examples, the display devices 110-140 can also wirelessly communicate with the server system 134 and / or the medical device 136.

[0151] In certain embodiments, the sensor electronics module 12 includes electronic circuitry associated with the measurement and processing of continuous analyte sensor data, including future algorithms associated with the processing and calibration of sensor data. The sensor electronics module 12 can be physically connected to the continuous analyte sensor 10, integrated with the continuous analyte sensor 10 (non - removably attached), or removably attached. The sensor electronics module 12 can include hardware, firmware, and / or software that enables the measurement of analyte levels via a glucose sensor. For example, the sensor electronics module 12 can include a potentiostat, a power source for powering the sensor, other components useful for signal processing and data storage, and a telemetry module for transmitting data from the sensor electronics module to one or more display devices. The electronics can be fixed to a printed circuit board (PCB) or the like and can take various forms. For example, the electronics can be in the form of an integrated circuit (IC) such as an application - specific integrated circuit (ASIC), a microcontroller, and / or a processor.

[0152] The sensor electronics module 12 can include sensor electronics configured to process sensor information such as sensor data and generate transformed sensor data and displayable sensor information. Examples of systems and methods for processing sensor analyte data are described in more detail herein and in U.S. Patent Nos. 7,310,544 and 6,931,327 and U.S. Patent Application Publication Nos. 2005 / 0043598, 2007 / 0032706, 2007 / 0016381, 2008 / 0033254, 2005 / 0203360, 2005 / 0154271, 2005 / 0192557, 2006 / 0222566, 2007 / 0203966, and 2007 / 0208245, all of which are hereby incorporated by reference in their entirety for all purposes.

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

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

[0155] Referring further to FIG. 1A, the plurality of display devices can include a custom display device specifically designed to display certain types of displayable sensor information (e.g., in some embodiments, numerical values and arrows) associated with the analyte data received from the sensor electronics module 12. The analyte display device 110 is an example of such a custom device. In some embodiments, one of the 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 can include a tablet 130, a smartwatch 140, a medical device 136 (e.g., an insulin delivery device or a blood glucose meter), and / or other handheld devices such as a desktop or laptop computer.

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

[0157] As further illustrated in FIG. 1A, system 100 may also include a wireless access point (WAP) 138 that can be used to interconnect one or more of the sample sensor system 8, the plurality of display devices, the server system 134, and the medical device 136. 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 of system 100. The server system 134 can be used to collect sample data from the sample sensor system 8 and / or the plurality of display devices and perform, for example, an analysis thereon, generate a general or individualized model for blood glucose values and profiles, etc.

[0158] Referring now to FIG. 3A, system 300 is illustrated. System 300 may be used in connection with implementing the disclosed system, method, and device embodiments. By way of example, the various components described below in FIG. 3A may be used between a sample sensor system, such as that shown in FIG. 1A, and a plurality of display devices, medical devices, servers, etc. to provide wireless communication of glucose data.

[0159] As shown in FIG. 3A, system 300 may include a sample sensor system 308 and one or more display devices 310. Further, in the illustrated embodiment, system 300 includes a server system 334 that includes a server 334a that is next coupled to a processor 334c and a storage device 334b. The sample sensor system 308 may be coupled to the display device 310 and / or the server system 334 via a communication medium 305.

[0160] As described in detail herein, the sample sensor system 308 and the display device 310 may exchange messaging via the communication medium 305, which may also be used to distribute sample data to the display device 310 and / or the server system 334. As mentioned above, the display device 310 may include various electronic computing devices such as, for example, smartphones, tablets, laptops, wearable devices, etc. The display device 310 may also include the sample display device 110 and the medical device 136. Here, it will be noted that the GUI of the display device 310 can receive user input and perform the function of displaying menus and information derived from the sample data. The GUI may be provided by various operating systems known in the art such as, for example, iOS, Android, Windows Mobile, Windows, Mac OS, Chrome OS, Linux®, Unix, game platform OSs (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, etc., and / or wired protocols and media.

[0161] In various embodiments, the elements of the 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 consideration of the present disclosure, one of ordinary skill in the art will understand that the system 300 may include multiple sample sensor systems, the communication medium 305, and / or the server system 334.

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

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

[0164] Server 334a can include, for example, an Internet server, a router, a desktop or laptop computer, a smartphone, a tablet, a processor, a module, etc., and can be implemented in various forms including, for example, an integrated circuit or an assembly thereof, a printed circuit board or an assembly thereof, or a separate housing / package / rack or a plurality of them. In an embodiment, server 334a at least partially directs communications performed via communication medium 305. Such communications include delivery and / or messaging (e.g., advertisements, instructions, or other messaging) and analyte data. For example, server 334a can process and exchange messages between analyte sensor system 308 and display device 310 related to, for example, frequency band, transmission timing, security, alarms, etc. Server 334a can update information stored on analyte sensor system 308 and / or display device 310, for example, by delivering an application thereto. Server 334a can transmit / receive information to / from analyte sensor system 308 and / or display device 310 in real time or sporadically. Further, server 334a can implement cloud computing capabilities for analyte sensor system 308 and / or display device 310.

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

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

[0167] The protocol can be further configured to establish communication channels with multiple devices while implementing an interference avoidance scheme. In some embodiments, the protocol may utilize an adaptive isochronous network topology that defines various time slots and frequency bands for communication with some devices. Thus, the protocol can modify the transmission window and frequency in response to interference and to assist communication with multiple devices. Accordingly, the wireless protocol can use a time and frequency division multiple access (TDMA) based scheme. The wireless protocol may also use 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 like Wi-Fi, Bluetooth®, and Bluetooth® Low Energy (BLE). The wireless protocol can operate in various frequency bands such as the open ISM band at 2.4 GHz. Further, to reduce power consumption, the wireless protocol can adaptively configure the data rate according to the power consumption.

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

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

[0170] In some embodiments, when a standardized communication protocol is used, an off-the-shelf transceiver circuit incorporating a processing circuit for handling low-level data communication functions such as managing data encoding, transmission frequency, handshake protocol, etc. can be utilized. In these embodiments, the processors 335, 380 do not need to manage these activities, but rather provide the desired data values for transmission, manage high-level functions such as power-up or power-down, and set the speed at which messages are transmitted, etc. The instructions and data values for performing these high-level functions can be provided to the transceiver circuit via a data bus and transfer protocol established by the manufacturer of the transceivers 320, 360.

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

[0172] The analyte sensor system 308 typically aggregates analyte data from the sensor 375 and transmits this to the display device 310. Data points regarding analyte values can be aggregated and transmitted over the lifespan of the sensor 375 (e.g., within a range of 1 day to 30 days or more). New measurements can be transmitted at a frequency sufficient to adequately monitor glucose levels. Rather than having respective transmit and receive circuits in the analyte sensor system 308 and the display device 310 that continuously communicate the analyte sensor system 308 and the display device 310, the analyte sensor system 308 and the display device 310 can establish a communication channel between them periodically and / or intermittently. Thus, the analyte sensor system 308 can, in some cases, communicate wirelessly via transmission with the display device 310 (e.g., a handheld computing device, a medical device, or a proprietary device) at a predetermined time interval. The duration of the predetermined time interval can be selected to be long enough such that the analyte sensor system 308 does not consume too much power by transmitting data more frequently than necessary, but can be selected to be frequent enough to provide substantially real-time sensor information (e.g., values or analyte data) for output to the user by the display device 310 (e.g., via the display 345). The predetermined time interval is 5 minutes in some embodiments, but it is understood that this time interval can be modified to any desired length of time.

[0173] Continuing to refer to FIG. 3B, the connection interface 315 interfaces the display device 310 to the communication medium 305 such that the display device 310 can be communicatively coupled to the analyte sensor system 308 via the communication medium 305. The transceiver 320 of the connection interface 315 can include a plurality of transceiver modules operable in different wireless standards. The transceiver 320 can be used to receive analyte data and related instructions and messages from the analyte sensor system 308. Further, the connection interface 315 can optionally include additional components for controlling wireless and / or wired connections such as a baseband and / or Ethernet® modem, audio / video codec, etc.

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

[0175] In various embodiments, a user may interact with the analyte sensor application 330 via the GUI 340, which may be provided by the display 345 of the display device 310. By way of example, the display 345 may be a touch screen display that receives various hand gestures as input. The application 330 may process and / or present analyte-related data received by the display device 310 according to the various operations described herein, and such data may be presented via the display 345. Further, the application 330 may be used to obtain, access, display, control, and / or interface with analyte data associated with the analyte sensor system 308, as well as associated messaging and processes, as described in further detail herein.

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

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

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

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

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

[0181] It should be noted at this time that elements of the same name between the display device 310 and the sample sensor system 308 may include similar features, structures, and / or capabilities. Thus, with respect to such elements, the description of the display device 310 above may, in some cases, be applicable to the sample sensor system 308.

[0182] In some aspects according to the systems, devices, and methods of the present disclosure, health-related and non-health-related data are aggregated, structured, and / or transformed to intelligently generate outputs including new sample data structures, displays, and controls of the devices of the system and the devices of other systems. Such health-related information can include glucose and related data (e.g., insulin, diet, activity, etc.), and non-health-related data can include location data, user demographic data, etc. Implementations according to such aspects of the current technology are recognized to improve the operation of the system, for example, by reducing the complexity of data processing and data transmission between devices, reducing the amount of data and the processing algorithms to be stored and operated, and thereby accelerating the performance of the system as described herein. Further, implementations according to such aspects of the present technology are envisioned to improve the user's ability to manage their diabetes or other diseases using continuous sample monitoring. Examples of techniques and tools for generating such outputs related to glucose status, trends, history, context, and insights are disclosed below to assist the user in making informed decisions in the management of their diabetes. Also, the disclosed techniques, systems, devices, and tools can be applied to other health impairments.

[0183] In the management of diabetes, an increasing number of users of CGM systems, which are a type of diabetes device, desire to view more glucose data over time within the context of their lives, such as how blood glucose levels vary during their eating habits (generally, those specific to a particular diet), their lifestyle (e.g., work days and hours at home or play), physical activity, etc. However, display screens are limited in size, resolution, and other technical parameters. Moreover, even with a larger display screen or squeezing more data onto the screen, the effectiveness of data display is not necessarily improved, or it does not necessarily assist the understanding of the user viewing the data presented on the screen. To address such limitations in CGM systems, data display should be intelligently designed and constructed to avoid information overload and confusion that can lead to data misinterpretation, chaos, lack of information, etc., or even worse, poor decision-making. For example, inadequate data display can ultimately lead to poor decision-making by the user, which can be harmful to their glucose management and health.

[0184] Furthermore, while more contextually meaningful data is being demanded, manufacturers of CGM systems must pay attention to the regulations and standards defined by regulatory authorities, such as the FDA (Federal Drug Administration). In some cases, specific restrictions or requirements that can affect the classification of CGM devices and related software applications may apply to the data displayed within a "feasible period" such as within 3 hours of real time. These regulations and restrictions also impact the cost of their target products, software, or services.

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

[0186] Visualization of Glucose Patterns As discussed above, the specimen data collected by the specimen sensor system 308 may include raw sensor data. Since the user may potentially miss important information buried in the clutter of voluminous or unmodified raw sensor data, an unmodified graphic representation of the raw sensor data may be of little value to the user. As a result, the embodiments described herein include systems and methods for constructing a data structure or arrangement of specimen data that facilitate the display of specimen data in a modified graphic representation, the features of which are to conveniently show patterns and / or information valuable to the user's health.

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

[0188] In some exemplary implementations, the analyte sensor system 308 or the display device 310 processes a data set to generate a graphical display viewable on the display device 310, the graphical display including, for example, an array of analyte concentration values over a plurality of graphically modified time intervals to indicate one or more patterns in the analyte data. In some examples, the array of analyte concentration values for the graphical display includes a spatio-temporal organization of analyte concentration values positioned along a first direction according to a first time scale and along a second direction according to a second time scale. The analyte level of the analyte concentration values can be modified and is represented in the graphical display by one or more of the modifications in the graphical display by introducing or using shape, color, shading, gradient of color or shading, different shadings, transparency, opacity, buffer regions, graphic icons, arrows, animations, text, numbers, or various intensities or contrasts of gradual fading based on various health parameters, size of the analyte level, and / or statistical metrics associated with the analyte level or group of analyte levels. In some implementations, an analyte application 330 operable on the display device 310 processes a data set to generate a graphical display viewable on the display 345 and can modify or adjust according to the size and / or metric of the analyte level(s).

[0189] FIG. 4A is an illustration of a modified graphic display in which analyte concentration values are arranged and presented over a plurality of time intervals so that a viewer can easily detect patterns in the analyte data. The data structure or arrangement of analyte data generated by the embodiments described herein may use color, shape, shading, size, or other visual representations to generate a modified graphic display to more easily create detection patterns in the analyte data for the viewer. Analyte application 330 can receive intermittent analyte concentration values corresponding to a raw data set and generate a data structure or arrangement of analyte data that can generate a modified graphic display such as graph 400A. Graph 400A illustrates analyte concentration values 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. In the example shown in FIG. 4A, the first time scale is an hourly time scale over a 24-hour day, and shows analyte concentration values over a day or multiple days over a daily time scale. The second time scale is a daily time scale over a one-week (7-day) period, and shows analyte concentration values over a week or multiple weeks over a weekly time scale. In the exemplary graph 400A, the concentration of analyte values over 24 hours for a one-week period is shown, but other time intervals can be used. For example, the first direction 402 can be an hourly time scale over a one-day period, and the second direction 404 can be another selected period including a one-month period (e.g., several days of a particular month), a weekday period (e.g., 5 days from Monday to Friday), a weekend period, or a period selected by the user on the user interface of display device 310. Additional data can be extended or included using averaging or other numerical / statistical techniques. For example, at the daily scale 404, the average value or other statistically driven data of the analyte concentration values for a particular day over a particular period can be represented as the analyte concentration value for that day (e.g., the analyte concentration values for Sundays over the past 3 months).Thus, graph 400A or other 7-day / 24-hour graphs are not limited to only the values of the past seven days, and the graphs 400A and other graphical displays described herein can be implemented using the fusion of data over any period of the user's or system's choice.

[0190] The exemplary graph 400A can be an isometric graph in which the magnitude of the analyte concentration value is represented by a shape along a vertical axis perpendicular to the first and second directions 402 and 404. The size of each shape can correspond to the magnitude of the analyte concentration value. In some implementations, color can be used to further indicate the magnitude of the analyte concentration value or convey additional information about the analyte data. In other embodiments, various shadings can be used to distinguish different magnitudes of the analyte concentration value. For example, if shading 406, 408, 410, 412, 414, 416, 418, or color is used, yellow can be used for the regions of graph 400A where the analyte concentration value exceeds a high threshold. Shadings 420, 422, 424, and 426 can be used to indicate the regions of graph 400A where the analyte concentration value is below a low threshold. If color is used, red can be used to indicate the regions where the analyte concentration value is below the low threshold. In the arrangement of the analyte concentration values in the exemplary graph 400A, a viewer can readily determine at a glance the time when the analyte concentration value exceeds the high threshold by observing the peak in the data, or if color is used, the viewer can quickly determine the time when the analyte concentration value exceeds the high threshold by observing the yellow regions. The arrangement of the analyte data as shown in the exemplary graph 400A enables a viewer to easily observe patterns in the analyte data. For example, in the exemplary graph 400A, the regions 406, 408, 410, 412, 414, 416, and 418 corresponding to the analyte concentration values around 6 PM either show a peak or, if shading is used, the regions 406, 408, 410, 412, 414, 416, and 418 are shown in a darker color (compared to other regions), indicating that there is a tendency for the analyte concentration value to rise around 6 PM during the period when the analyte concentration value is shown. If color is used, a similar pattern can be observed. By observing such patterns in the analyte concentration values, a patient or a caregiver of the patient can make better decisions in the health management of the patient.

[0191] FIG. 4B is a graphical representation composed of an aerial view of graph 400A, shown as graph 400B. Using graph 400B, a user can easily observe patterns in the sample data. In some implementations, graph 400A can be displayed on display 345 in an interactive manner that allows the displayed graph 400A to be rotated, twisted, yawed, and / or zoomed in or out to manipulate the viewability of graph 400A. In this regard, display 345 presents graph 400A and allows the user to change the display to graph 400B. Similar to graph 400A, graph 400B is modified to represent the magnitude of the sample concentration value by a shape on a planar graph (e.g., along one or both of the first and second directions 402 and 404) to identify features in the sample data such as high sample concentration levels illustrated by the enlarged portion of the plot for each day at a particular time and low sample concentration levels illustrated by the reduced portion of the plot for each day at a particular time. Similar to graph 400A, graph 400B can also be modified to present a shadow or other visual representation associated with a feature that produces an effect that allows a viewer to quickly determine, for example, by observing the modification of the graphical display within the data, the time when the sample concentration value exceeds or falls below a high or low threshold.

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

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

[0194] An array of analyte data as shown in the exemplary graph 500 enables a viewer to observe patterns in the analyte data. For example, by a cursory glance at the exemplary graph 500, a viewer can quickly observe that for several days of the week, the analyte concentration value exceeds the high threshold around 12:00 am.

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

[0196] In some embodiments, the user can obtain additional information for a given day by, for example, touching one of the rings of graph 500 or by providing an input to the analyte sensor app 330. Instead of or in addition to graph 500, an additional graph showing more details for the day corresponding to the touched ring may be shown. FIG. 6 illustrates a modified graphical display corresponding to the data structure and arrangement of analyte concentration values over a time interval. The data structure and arrangement of analyte concentration values can generate graph 600A or 600B, where the analyte concentration values are shown in relation to a high threshold, a low threshold, and the shape of the target region. The time interval shown in graph 600A or 600B can be the 24-hour period corresponding to the touched ring in graph 500. Other time intervals can also be used. Graph 600A or 600B can be displayed parallel to, instead of, or in addition to graph 500 when the user indicates a point on graph 500. Further, the user can indicate different points along graph 600A using a pointing device or touch screen, and graph 600A can be updated and modified to display analyte data corresponding to the indicated point of the user within the central region 614 of graph 600A. The updated analyte data can 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 indicates a desire to view analyte data corresponding to 5:00 am on June 24 by touching the touch display or by rotating point 616 on the display of graph 600A. Graph 600B is a modified graph 600A indicating that the user desires to view the analyte data value corresponding to 9:00 am on June 24. The analyte concentration value and corresponding time are accordingly modified and updated in the central region 614.

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

[0198] In some embodiments, graph 600A or 600B can utilize shading, gradients, or colors corresponding to the magnitude of the sample concentration value. For example, graph 600A or 600B can be generated or modified to utilize various intensities and / or contrasts of shading to indicate the sample concentration value. Shadings 602, 604, 606, and similar shadings can be used to indicate where the sample concentration value exceeds a high threshold. The intensity of the shading can correspond to the magnitude of the sample concentration value. Shadings 608, 610, 612, and similar shadings can be used within the region of graph 600A or 600B where the sample concentration value is below a low threshold. A neutral shading, for example, shading 618, can be used to indicate a sample concentration value within a target range. One of ordinary skill in the art can understand that the shadings as described above are exemplary, and other shadings, textures, gradients, and / or other visual representations including colors can be used.

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

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

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

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

[0203] Figure 8 is an illustration of a modified graphic display generated by the data structure and arrangement of analyte data over a plurality of time intervals. The data structure and arrangement of analyte concentration values can generate a graph 800 in which the analyte concentration values are shown over a plurality of time intervals over 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. However, other time periods may be configured and displayed. Each line graph 806, 808, 810, etc. represents analyte concentration values over different 24-hour periods. For example, analyte concentration values over a week can be represented by line graphs 806, 808, 810, etc. The fusion of analyte data for each day being displayed can also be used to generate line graphs 806, 808, 810, etc. Each line graph can visually distinguish the analyte concentration values of different time intervals by utilizing the area under the curve shaded with different opacities. The user can indicate a point on graph 800 using a pointing device or via a touch screen, and a callout window 812 can be shown that includes the measured value of the analyte concentration value corresponding to the selected point on graph 800.

[0204] In some embodiments, one or more side tabs can be utilized to visually separate the specimen data and present a more focused view. For example, if line graphs 806, 808, 810, etc. represent one week of specimen data, a set of side tabs or buttons 806-1, 808-1, ..., 810-1 can be used, and the actuation of side tab or button 806-1 causes line graph 806 and its corresponding region to be displayed more prominently under the curves and opacities related to the other displayed specimen data. The unselected specimen data can be displayed in a less prominent shadow. Side tab or button 814 can actuate all the specimen data and display it prominently.

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

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

[0207] FIG. 9 is an illustration of a modified graphic display generated by the data structure and arrangement of sample data over a plurality of time intervals. The data structure and arrangement of the sample concentration values can generate a graph 900 in which the sample concentration values are shown over a plurality of time intervals over a time scale 902. The magnitude of the sample concentration values can be represented on a vertical axis 904. The time scale 902 can represent a 24-hour period. However, other time periods may be configured and displayed. Each of the exemplary line graphs 906, 908, 910, etc. represents sample concentration values over different 24-hour periods. For example, sample concentration values over a one-week period can be represented by line graphs 906, 908, 910, etc. The user can point to any part of the graph 900 via a pointing device, for example, by moving a mouse pointer across the graph 900 or by touching a touch screen display that displays the graph 900. An icon or an overlay graphic display, a callout window 912, etc. can be shown on the graph 900 pointed to by the user, and the callout window can display the measured value of the sample data corresponding to the point selected by the user. If the user clicks or points to a portion of the graph 900 where duplicate or future data has been detected, a graphic display 914 appears within the area of the graph 900 and can instruct the user to click for further information. When the user clicks on the graphic display 914, an additional graphic display, for example, a text box 916, appears within the area of the graph 900 and can provide the user with additional information.

[0208] In some embodiments, the line graphs 906, 908, 910, etc. can be rendered in different line shapes or styles depending on the reliability of the underlying sample data they represent. For example, a dashed line style can indicate uncertain sample data. A continuous line can indicate sample data that has been reliably tracked. A dotted line 924 can indicate predicted future sample data. A graph key 918 can be included in the display of the graph 900 along with an explanation of each line graph style.

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

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

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

[0212] FIG. 12 is an illustration of an exemplary graphic display in which analyte concentration values are arrayed and presented over a plurality of time intervals and shown on a clock dial graph 1200, enabling a viewer to readily detect one or more patterns in the analyte data over the plurality of time intervals. In one implementation, graph 1200 may utilize different shadings corresponding to analyte concentration values that exceed a high threshold, fall below a low threshold, or are within a target value, respectively. The analyte concentration values for several time intervals (e.g., several days) may be overlaid to construct graph 1200. In this scenario, a gradient can be generated to show the pattern over the plurality of time intervals illustrated in graph 1200. For example, using a dark shading 1208 to indicate analyte concentration values that fall below a low threshold, the analyte concentration values from 12:00 AM to 12:00 PM for 7 days are overlaid to construct graph 1200, and the gradient of shading 1208 for the time between 3:00 AM and 6:00 AM may indicate the decrease in analyte values during that time over 7 days. The user can readily array this pattern in the analyte data over 7 days and take appropriate measures for better self-health management. In some embodiments, the analyte trend value graphic may also be included in graph 1200 that shows the change in analyte concentration values using a line graph 1202.

[0213] In some implementations, line graph 1202 may be an analyte level trace overlaid on clock dial graph 1200 such that higher analyte levels are closer to the outer curved region of graph 1200 and lower analyte levels are closer to the inner curved region of graph 1200, or vice versa. As described, graph 1200 may use various gradients and / or contrasting shadings 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 over an hourly time scale.

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

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

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

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

[0218] In block 1320, the processor 335 can flag or embed the sample data with additional data used to generate the graphics at block 1308 of FIG. 13A or to generate the modified graphics at block 1310. The graphics can include the graphic displays described above, particularly in relation to graphics 400A, 400B, 500, 600, 700, 800, 900, 1000, 1100, and 1200 among other graphics. The additional data can include one or more time scales, one or more sets of high and low thresholds of the sample data in a receptor or group of receptors, the relationship of the tagged or tabulated sample data, context information related to the aggregated sample data collected at block 1318, and any other information that can be later called upon or otherwise used to flag the sample data or aggregate the sample data based on generating or modifying the graphic displays of the graphs described above. In some implementations, as shown in block 1322, after analyzing the data, a process is executed to flag the additional data with the sample data or to embed the additional data using the sample data.

[0219] In block 1322, the processor 335 analyzes the grouped specimen concentration values. In some implementations, the processor 335 may determine the maximum and / or minimum value(s) of the grouped values. In some implementations, the processor 335 may determine the average value, median value, standard deviation value, or other statistical metric of the grouped values. Further, the processor 335 can perform a Fourier transform, Laplace transform, and / or sampling technique on the grouped specimen concentration values, for example, to assist in forming a modified graphic display that shows patterns in the specimen data in block 1310 of FIG. 13A. In some implementations, the process in block 1320 is performed on the analysis group of specimen concentration values after block 1322, and the analysis group of specimen concentration values can flag or embed additional data for use in modifying the graphic in block 1310. For example, the analyzed group of specimen concentration values may have an average value, median value, standard deviation value, etc. that exceeds a predetermined threshold or is outside a predetermined range, and can flag or embed additional data.

[0220] In block 1324, the processor 335 arranges the analysis group of specimen concentration values based on spatial or temporal parameters associated with the type of modified graphic as described above, associated with graphs 400A, 400B, 500, 600, 700, 800, 900, 1000, 1100, and 1200. For example, if the graphic includes a second time scale, the processor 335 can arrange the analysis group of specimen concentration values according to those times of day values for the second time scale, such as days of the week, days of the month, selected days of a period (work days, holidays, or other user-selected time frames, etc.).

[0221] In block 1326, the processor 335 forms a dataset of an ordered analysis group of specimen data. The dataset is configured to be processed by the processor 335, for example, as a basis for forming a graphic display that can be displayed on the display 345 in block 1308 of FIG. 13A. As described above, the dataset generated in block 1326 is self-referential and includes information for generating the graphic in block 1308 of FIG. 13A or the modified graphic in block 1310 of FIG. 13A.

[0222] Some advantages of the present method and system may include the following. The self-referential dataset (SRDS) generated in block 1326 eliminates the need for the processor 335 to search for and call the necessary information from various parts of the system 302 to generate the graphics of blocks 1308 and 1310. Otherwise, for example, without the self-referential dataset generated in block 1326, the processor 335 would have to search, query, and / or call various parts of the system 302 each time the user requests a different graphic or requests a modification of the displayed graphic. Thus, the self-referential dataset generated in block 1326 improves the operation of the system 302 by reducing the complexity in data processing and data transmission among various parts of the system 302. For example, using the SRDS, the system does not need to store or process additional algorithms such as pattern recognition algorithms to generate an output such as a display for communicating pattern information to the user. Further, the self-referential dataset generated in block 1326 can reduce the amount and frequency of data to be transmitted for the purpose of generating the graphic displays of blocks 1308 and 1310 of FIG. 13A. Accordingly, the related processing algorithms or graphic algorithms to be stored and operated are also reduced, and the performance of the system 302 is improved.

[0223] Process 1306 ends at block 1328, and further processing is taken over by block 1308 of FIG. 13A.

[0224] FIG. 13C illustrates flowchart 1308 of an exemplary method for implementing the process identified at block 1308 of FIG. 13A to generate a graphic of an array of analyte concentration values. Although this exemplary method is described as being implemented by processor 335 of display device 310, it is understood that other devices of the system may be configured to implement the method. Process 1308 begins at block 1330. At block 1332, processor 335 receives user input data related to the user's desired graphic display. These may include the type of graphic display desired (e.g., text, bar, pie, or other chart such as a chart, and / or graphic displays such as 400A, 400B, 500, 600, 700, 800, 900, 1000, 1100, and 1200, or other graphic displays), and / or the range of time scales for which the user desires to view a graphic display of the data set of process 1306.

[0225] In block 1334, the processor 335 may receive hardware or software data related to the display device 310 or the display 345. The display data may include, for example, the available viewing area, the available orientation, and the size, dimensions, or resolution of the available input device. In block 1336, the processor 335 can determine whether the self - reference data set formed in block 1326 contains all the information necessary to generate the user - desired graphic. As an example, the user may be requesting the display of sample data that is outside the range captured within the self - reference data set. In these cases, process 1306 can be repeated to form a more comprehensive self - reference data set. However, in most cases, the self - reference data set is formed in such a way that it contains all the information and data necessary to generate the user - desired graph.

[0226] In block 1338, the processor 335 reformats the self - reference data set based on the user input data and the display device data and generates a formatted self - reference data set. For example, if the user - desired display range is smaller than the range of data captured within the self - reference data set, the processor 335 in block 1338 can filter out the unwanted or out - of - range data by erasing that data from the self - reference data set. In block 1340, the processor 335 generates a graphic of an array of analyte concentration values based on the formatted self - reference data set. The processing involved in block 1340 may depend on the type of graphic selected by the user and the data of the display device. For example, if the user desires a graph 400A as described above in relation to FIG. 4A, the processor 335 can determine the correct scale for generating graph 400A based on the available viewing area and the orientation of the display device 345.

[0227] Process 1308 ends at block 1342, and further processing is taken over by block 1310 in FIG. 13A.

[0228] FIG. 13D illustrates flowchart 1310 of an exemplary method for implementing the process identified at block 1310 in FIG. 13A to modify a graphic to show one or more characteristics in the analyte concentration value. Although this exemplary method is described as being implemented by processor 335 of display device 310, it is understood that other devices of the system may be configured to implement this method. In response to the graphic display selected by the user, processor 335 can modify the graphic generated by process 1308 to show one or more characteristics and / or patterns in the analyte data. Further, the modified graphic can present the data in a form that reduces information overload and possible user misunderstanding of the presented data. For example, if the user selects a three-dimensional graph, such as graphic display 400A, a particular portion of the graphed analyte data may block other portions of the graphed data. Process 1310 can detect such instances and modify the graphed data accordingly, such as by making portions of the graphed analyte data transparent in the overlapping regions.

[0229] Process 1310 may use color to modify the graphics generated by Process 1308. For example, Process 1310 can add various shaded colors to the graphed specimen data associated with one or more sets of high and low thresholds. Process 1310 can color-code the graphed data using the flagged or additional embedded information obtained at block 1320 of Process 1306. For example, the processor 335 may detect a portion of the graphed data corresponding to a specimen value that is 20% to 30% higher than the high threshold. The graphed specimen data can be modified using yellow or shading to indicate these values. If the graphed specimen data in another portion is 40% to 50% higher than the high threshold, a contrasting shade (e.g., a darker shade of a gray gradient if color is used, or a darker shade of yellow) can be used to indicate that portion of the specimen data. The processor 335 can detect and modify portions of the graphed data associated with the high and low thresholds by referring to the flags or embedded additional data in the self-referencing data set.

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

[0231] In some implementations, the SRDS may include flags or embedded information based on the context of the sample data. The context of the sample data can be obtained or derived from various sources. For example, if the sample values obtained on a particular day of the week match a mobile display device 310 detected at a restaurant, the SRDS may include a flag or embedded information indicating this correlation. The frequency of the detected correlation between the sample data and the context of the data can also be included within the SRDS. The processor 335 can modify the graphed data to include features according to the flags based on the context found within the SRDS, to visually represent the pattern of a user's behavior related to the sample data over a period of time. The user can make decisions related to partial health or diabetes based on the modified graphed sample data and the features described herein.

[0232] In some implementations, the processor 335 can modify the graphed data, where the modification is based on detecting a pattern of flags or embedded information in the SRDS. For example, the SRDS may include flags indicating the peaks and valleys of the sample data. The processor 335 can detect in a two-dimensional graph having a number of concentrated peaks that different sections of the graphed sample data may visually merge, making it difficult for a viewer to identify these peaks. In such a case, the processor 335 can increase or introduce buffer regions between different sections of the graphed sample data to correct this scenario. The processor 335 refers to the flags or additional embedded data in the SRDS to detect the peaks and valleys of the data, determines whether there is a pattern where the peaks are graphed too closely together, and modifies the graphed data to include the new or increased buffer regions, so as to assist in the easy visual interpretation of the graphed data.

[0233] Process 1310 begins at block 1344. Next, process 1310 proceeds to a series of decisions where the graphed data is modified to show characteristics of the sample data. For example, the graphed data showing one or more patterns of the sample concentration values can be modified by modifying the graphic to show one or more characteristics at the sample concentration values. One of ordinary skill in the art will readily recognize that the techniques of the present invention are not limited to the series of decisions and modifications disclosed herein, and that additional series of decisions and modifications can be devised and implemented without departing from the spirit of the techniques of the present invention. Also, in all implementations, all of the disclosed decision and modification steps are not necessarily required. Depending on the desired graphic display of the user, one or more decision and modification steps may be removed, or other steps may be added.

[0234] In decision block 1346, processor 335 scans the SRDS to detect whether there is a flag or embedded additional data related to the relationship between the sample data and one or more high and low thresholds. The SRDS may contain various such flags or additionally embedded information. For example, the sample data in the SRDS can flag or correlate to thresholds where different time scales within the sample values of the SRDS can have their own associated thresholds. The sample data in the SRDS can be flagged based on the percentage or range by which the sample data exceeds or falls below a high or low threshold. In block 1348, depending on the configuration of the threshold flags and the type of graphic requested by the user, processor 335 modifies the graphed data to show the characteristics and / or patterns of the sample data.

[0235] In some implementations, the modification may include using color, gradient color, shading, various degrees of transparency or opacity, and varying the color, gradient, or transparency based on overlapping and underlying regions to enable visual detection of features and / or patterns in the specimen data as described above in connection with the modified graphic displays 400A, 400B, 500, 600, 700, 800, 900, 1000, 1100, and 1200.

[0236] In block 1350, the processor 335 scans the SRDS to detect whether a flag or embedded additional data related to the statistical analysis performed in process 1306 is present within the SRDS. The processor 335 can modify the graphed data based on the flag or embedded additional data in the SRDS, where the flag or embedded additional data is based on the statistical analysis. For example, the specimen data in the SRDS can be flagged based on the relationship between the specimen data and a standard deviation value, an average value, a variance value, or other statistical parameters related to the underlying specimen data. In some implementations, the specimen data in the SRDS can be flagged if it is outside the range of an acceptable multiplier of the standard deviation value of the specimen data. The corresponding graphic modification of the graphed specimen data can be based on these flags. Or, specimen data within two multipliers of the standard deviation value of the specimen data can be flagged and later the graphed data can be modified using color.

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

[0238] In block 1354, the processor 335 can scan the SRDS to detect whether there is embedded additional data related to the context of the flags or specimen data. Some examples of the context of the specimen data can include context information regarding the user's location when the specimen data was collected (e.g., whether the user was at a restaurant, gym, home, workplace, or school, and how often the user appeared at this location there), the relationship between the specimen data and various activities of the user (e.g., whether the specimen data was collected when the user had just eaten, or participated in exercise, or was awake or asleep, whether insulin was ingested, and how much was ingested). The context specimen data can be obtained automatically without user intervention or can be input by the user.

[0239] Context specimen data is not limited to the examples listed in this specification, and those skilled in the art can easily determine other context specimen data that can be flagged, embedded, or otherwise referenced in the SRDS. In block 1356, the processor 335 can modify the graphed data based on the context flag or the embedded data in the SRDS. Various graphic modifications corresponding to various contexts can be programmed in process 1310. The context modification can include using color, color gradient, shadow, various degrees of transparency or opacity to enable visual detection of features and / or patterns in the specimen data as described above in connection with the modified graphic displays 400A, 400B, 500, 600, 700, 800, 900, 1000, 1100, and 1200.

[0240] The graphic modification of process 1310 is not limited to the examples listed above. Various graphics can be used for modification to show features, patterns, or trends in the specimen data and to conveniently alert or convey health or diabetes-related data to the user. The processor 335 can use graphics or graphic techniques such as graphic icons, animations, text or text boxes, fonts and formatted text or numbers, arrows, gradual fading, or other techniques for modifying the graphed data in process 1310.

[0241] In block 1358, the processor 335 may scan the flags in the SRDS and the graphics generated by process 1308 to determine whether other modifications to the graphed data can further improve readability, reduce confusion, and better show features and / or patterns in the specimen data. For example, as described above, if the processor 335 detects a number of concentrated peaks in the graphed data and associated flags in the SRDS based on the type of graphed data, in block 1360, the processor 335 may modify the graphed data by introducing or adding one or more buffer regions to improve readability and better show features and / or patterns in the specimen data. The processor 335 may also analyze the graphed data generated by process 1308 and the flagged data in the SRDS to detect whether overlapping regions are rendered in a way that reduces the transmission of information in the graphed data. In block 1360, the processor 335 may modify the color, shading, gradient, spacing, or transparency within the overlapping regions to visually distinguish the overlapping regions and improve the ability of the graphed data to convey features, patterns, or trends in the specimen data. One skilled in the art can readily determine additional analyses of the flags and graphed data and the modifications associated therewith to improve the transmission of health or diabetes-related data. Process 1310 ends at block 1362, and further processing is taken over by block 1312 in FIG. 13A.

[0242] In some implementations, the process of generating the SRDS, the graphed data, and the modified graphed data are described in relation to past or collected specimen data, but the systems and methods of the technology of the present invention can be used with future or predicted specimen data, or a combination of past collected and future specimen data.

[0243] Visualization of Insulin The embodiments described herein are not limited to generating a data structure based on sample data. Raw data about other compounds related to a patient's health can also be received, and the system can generate a data structure and data array capable of generating a modified graphic display based on such data. For example, the system can receive data corresponding to a patient's Insulin on Board (IOB) level and generate a data structure or data array capable of generating a modified graphic display to conveniently show useful information about the patient's health. The methods associated with FIGS. 13A - 13D can be implemented to generate a modified graphic display associated with insulin data.

[0244] FIG. 14 is an illustration of a modified graphic display 1400 generated from a data structure and an array of insulin data. Display 1400 may include a ring 1402, and the complete circular ring may represent the Duration of Insulin Action (DIA). The overlay ring 1404 may represent the remaining time with respect to the amount of insulin on board. The size of the overlay ring 1404 may be determined as a fraction of the complete circular DIA. For example, if 1 hour out of a 4 - hour DIA remains, the remaining time will be 1 / 4 of the total DIA. In this case, the overlay ring 1404 may overlap only 1 / 4 of the ring 1402. When the user takes a dose of insulin, the overlay ring 1404 overlaps the entire ring 1402. As time passes and the insulin is metabolized, the overlay ring 1404 gradually decreases. In some embodiments, the ring 1402 and the overlay ring 1404 may each be rendered with different shades to better visually distinguish the two. In some embodiments, color is used to better visually distinguish the two. A graphic representation 1406 corresponding to the remaining time may be shown at the center of the ring 1402. In some embodiments, the graphic representation 1406 includes a number representing the amount of insulin on board.

[0245] If the overlay ring 1404 is gradually decreased over a long period of time, the gradual decrease may be difficult to identify for some viewers. In some embodiments, when the graphic display 1400 is generated, the overlay ring 1404 is shown to initially completely overlap the ring 1402, and the graphic representation 1406 is shown to correspond to the DIA. Over a short period of time, the size of the overlay ring 1404 is rapidly reduced to correspond to the remaining time relative to the current amount of residual insulin. Over the same amount of time, the graphic representation 1406 can be shown to decrease to settle on the current amount of residual insulin. For example, if numbers are used for the graphic display 1406, the numbers can decrease in a manner similar to a rapid countdown counter and can settle on the current amount of residual insulin. By showing such graphics for the overlay ring 1404 and the graphic representation 1406 over a short period of time, it can help viewers identify what information the graphic display 1400 is conveying.

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

[0247] In some embodiments, the sample sensor app 330 can be configured to receive event data, which may include information about the user's actions and activities related to health management or diabetes. For example, the event data can include the meals consumed, the type, duration, and intensity of exercise, and the amount and type of insulin taken. The sample sensor app 330 can then generate a modified graphic display that visually represents one or more relationships between the sample data, insulin data, and event data, either with each other or over a period of time or in relation to a period of time. For example, based on the visually represented configuration generated from the SRDS, the user of the system 302 can easily make health-related decisions or detect features and / or patterns without excessive mental activity.

[0248] Figures 15 and 16 illustrate modified graphic displays 1500 and 1600 generated from a data structure and arrangement of data according to an embodiment, where the graphic displays 1500 and 1600 include visual representations showing one or more relationships between insulin data, sample data, and events, either with each other or over a period of time or in relation to a period of time. In various implementations of the modified graphic displays 1500 and 1600, the display can include a display of one or more of the insulin data, sample data, or event data, and these displays can be further modified to display visual representations showing one or more relationships between the insulin data, sample data, or event data, either with each other or over a period of time. The visual representation can be shaped, configured, or scaled so as not to obscure the display of the insulin data, sample data, or event data. Further, the visual representation can be displayed in its entirety within the display of the insulin data, glucose data, or event data.

[0249] The graphic display 1500 may include a specimen trend graph 1502. Time is represented on the horizontal axis 1504. The magnitude of specimen data is represented on the vertical axis 1506. The specimen trend graph 1502 can be represented in relation to a high threshold and a low threshold 1508 and 1510. Although not shown in all embodiments, the specimen trend graph 1502 can be rendered in various colors, line styles, or shades associated with the high threshold and the low threshold 1508 and 1510 to visually represent the relationship between the specimen data and the high threshold and the low threshold 1508 and 1510. The graphic display 1500 may further include an event data display area 1512. In the example of FIG. 15, no event data is shown in the event data display area 1512, but it can also be displayed there. An example of event data is shown later in FIG. 16, and various icons and graphic displays are shown in the event data display area 1612. Referring back to FIG. 15, the graphic display 1500 may further include a graph of insulin data 1514. The horizontal axis 1516 may represent time. The vertical axis 1518 may represent the magnitude of the insulin data. The user can expand or contract the period during which the specimen trend graph 1502 and the insulin graph 1514 are displayed via different time tabs 1520. The graphic display or icon 1522 can indicate to the user that by changing the orientation of the mobile computing device from portrait to landscape or vice versa, the user can obtain different visual representations of the relationship between the specimen data, the insulin data, the event data, and time. The event display area 1512 may include a display of a graphic array of event data including one or more of carbohydrate intake, the amount of time spent exercising, the amount of calories burned, or the heart rate reaching its threshold or time.

[0250] Referring to FIG. 16, the graphic display 1600 is similar to the graphic display 1500. The event data display area 1612 may enable easy access to indicators when the user takes an action that may be considered in relation to the user's diabetes management. For example, food intake can be indicated by a label or graphic icon 1616, or an exercise session can be indicated by a label or graphic icon 1618. The event display area 1612 can be generated for quick access to the patient's actions related to diabetes management and can be shown to the patient's caregiver. In some implementations, a series of graphic icons of actions that may be related to diabetes management 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 took those actions. For example, the user can drag the meal event graphic icon 1616 and drop the icon onto the analyte trend graph 1602 around 12:00 PM. The event display area 1612 can then be updated to show the graphic icon 1616 corresponding to the user having taken a meal around 12:00 PM. Similarly, the user can add an exercise icon around 6:30 PM. In some embodiments, the user can also input event information via voice recognition or keyboard input, and the event display area 1612 can be automatically updated based on the user's input showing related icons such as the meal icon 1616 and the exercise icon 1618.

[0251] The user can use a pointing device or touch screen to point to or touch a point on the specimen trend graph 1602 and activate the callout window 1620. The callout window 1620 can include more detailed information related to the event data displayed in the event data display area 1612. The callout window 1620 can include, for example, a timestamp, the type or amount of food the user consumed, the type, intensity, and duration of any exercise the user performed, some indicator of the user's general mood, and the type and amount of insulin the user took. The callout window 1620 can include a graphic array of insulin data, such as one or more of insulin data including bolus or basal insulin, the administration time of bolus insulin, the administration time of basal insulin, or the value of residual insulin.

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

[0253] FIG. 18 illustrates a modified graphic display 1800 generated from a data structure and an arrangement of data, according to an embodiment in which the graphic display 1800 includes a visual representation showing one or more relationships of insulin data and sample data. The modified graphic display 1800 may include a sample trend graph 1802. Time is represented on the horizontal axis 1804. The magnitude of the sample data is represented on the vertical axis 1806. The amount of one or more residual insulin (IOB) data can be represented above or on the sample trend graph 1802 by utilizing one or more arrows 1808 and 1810, and the sizes of the arrows 1808 and 1810 correspond to the amount of residual insulin (IOB). Optionally, one or more numerical representations of the amount of residual insulin (IOB) can be displayed on or above the arrows 1808 and 1810, for example, as text.

[0254] In an exemplary example of the use of the modified graphic display 1800, the dataset structure can be formed to enable an intuitive visual representation of the meaning or effect of the IOB data it contains and displays. For example, instead of just numbers, residual insulin is visually represented as a downward arrow on a glucose trend chart. This can be intuitive since physiologically it is understood that insulin pushes down glucose. The more residual insulin there is, the larger the arrow becomes (the greater the pushing force). The number of units can optionally also be displayed with the arrow. In the case of an exemplary use where the user eats a meal and takes insulin, it can be a useful note that the user does not necessarily have to take more insulin again because the insulin did not act, and can then prevent the stacking of insulin. In the case of the opposite use, for example, if the user forgets to take insulin, the absence (or small arrow) of the arrow can be a note that reminds the user of the forgetfulness.

[0255] Visualization of Algorithms and Decision Support Diabetes can be a complex disease where patients must constantly and frequently make treatment decisions. Thus, the mental demands and stress in managing diabetes can potentially be a heavy burden on patients. The system 302 can utilize available data to present a graphic display that illustrates one or more relationships between sample data and the past, current, and future actions of the user to assist in the analysis and health management of the patient.

[0256] Figures 19A and 19B illustrate modified graphic displays 1900A and 1900B generated from the data structure and arrangement of data according to an embodiment in which graphic displays 1900A and 1900B include a visual representation of one or more relationships of insulin data and analyte data based on historical, current, and predicted analyte values. The modified graphic 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. The graphic display 1900A may include the current value of the analyte data 1912. The graphic display 1900A may be a prediction trend graph based on actions and may include one or more prediction graph lines 1904, 1906, and 1908 based on the user's actions. These actions may include, for example, eating, exercising, or not performing an action. The prediction graph 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 illustrated as a range 1910 as illustrated in the graphic display 1900B. Depending on one or more confidence parameters and the underlying prediction algorithm, the graphic displays 1900A and 1900B may be displayed as a general range prediction similar to a hurricane estimated path visualization, or the graphic displays 1900A and 1900B may be displayed as a single or multiple lines. The graphic displays 1900A and 1900B may be modified according to process 1310 as described above based on flags in the SRDS corresponding to parameters related to the certainty or confidence of the prediction. The modification may include fading out prediction ranges where one or more confidence parameters decrease. The graphic display of the prediction visually communicates the relationship between the user's actions and their possible effects on the analyte data, thereby reducing the patient's stress in making treatment decisions.

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

[0258] FIG. 21 illustrates a modified graphic display 2100 according to an embodiment in which a scrollable list of user activity data and trends in future analyte values are shown. In some implementations, a user may be provided with a graphic interface module that includes a button 2102 to enable addition of events (e.g., activities the user has performed, including meals, boluses, exercise, stress, etc.). The system 302 may generate a modified graphic display to show a scrollable list diagram of input events (e.g., meal event 2104 or meal + exercise event 2106) for the current time or a recent time frame, and one or more snapshots of analyte trend values 2108 and 2110 for a period after the event time. A user may visually represent the causal relationship between their activities (input events) and their analyte levels. A user's clinical team may recognize patterns and react accordingly to better manage the user's health. Optionally, in some implementations, an algorithm may be used to infer or automatically suggest and / or link multiple events according to patterns in the analyte data to determine one or more trends in future analyte data.

[0259] FIG. 22 illustrates a modified graphic display that depicts relationships among a number of complex variables in a simplified display 2200. Diabetic patients often have to consider a number of complex variables and their relationships when making decisions about their diabetes management. The modified graphic display 2200 simplifies the mental processes associated with analyzing the many complex variables informing a diabetic patient's decisions. In some implementations, current analyte values can be compared to a high threshold and a low analyte threshold to produce an analyte score. Residual insulin amounts can be compared to a high residual insulin threshold and a low residual insulin threshold to produce an IOB score. An insulin status score can be generated by multiplying the analyte score and the IOB score. In some implementations, other diabetes parameters can be analyzed and scores determined for each. The scores can be part of the insulin status score as additional multipliers. These diabetes parameter scores can include, for example, an analyte trend score, a score based on the GPS location (e.g., a bar or restaurant or physical location where past data may indicate the influence of location on analyte values), a food-related score, a physical activity score, and others.

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

[0261] In some implementations, the look-ahead module enables the user to selectively increase or decrease data related to the current amount or type of insulin, exercise (intensity, type, etc.), food intake (composition, amount, etc.), stress, or other parameters that affect the health management and glucose levels of a diabetic patient. For example, the user may use a swipe gesture on a touch screen or, alternatively, indicate an increase or decrease in an input current or future event, activity, or glucose-related parameter and view a projection effect on a real-time glucose trend graph. The predicted effects can be generated using models based on the patient population and their glucose-related data and / or can be based on machine learning over time for a particular user. The look-ahead module helps the user make better diabetes-related decisions by observing predictions based on the cumulative effects of combinations of factors on glucose levels. For example, a patient observing a current glucose level of 100 mg / dL can consider whether to eat a snack, go for a run, or take a small dose of insulin. The look-ahead module will enable the user to play around with snack size / contents, type of exercise, duration or intensity, and type and size of insulin dose to find the desired combination for proper glucose control. The look-ahead module can operate in combination with other devices. For example, Time Travel on an Apple Watch can trigger a prediction.

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

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

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

[0265] Interactive UI Representation Some graphical displays that illustrate glucose, insulin, or diabetes-related data may be overly cluttered in a scientifically looking graph and display. The technology of the present invention assumes a modified graphical display that is gentle, orderly, and easy to understand.

[0266] Figure 24A illustrates a modified graphical display in which a scalable design layout is utilized when the user desires to view more details. The user can display one or more modified graphical displays one at a time or all at once as needed. For example, the modified graphical display 2402 illustrates a 3-hour sample trend graph 2410 in an enlarged view and IOB data 2412 in a reduced view. The user can click or touch the reduced IOB figure 2412 to obtain an enlarged IOB figure 2414 in the modified display 2404. The user can click or touch the enlarged sample trend graph 2410 to obtain a reduced figure 2416 in the modified display 2406 or a reduced figure 2420 in the modified display 2408. Some illustrations of the data can repeat the various display forms to illustrate the same data in multiple understandable formats. For example, the user can click on the enlarged IOB figure 2414 to obtain a different graphical representation 2418 of the IOB data as shown in the modified graphical display 2408. Subsequent clicks or touches by the user can reduce the IOB figure 2418 back to the IOB figure 2412 as shown in the modified display 2402.

[0267] Figures 24B and 24C illustrate display screens presenting graphics that can be generated and modified according to embodiments of the disclosed method and system. In the example shown in Figure 24B, display screens 2422, 2424, 2426, and 2428 include exemplary graphic displays presenting current glucose 2430, glucose trend graph 2434, or residual insulin 2432 information in other health-related information. The display 2422 is characterized in that user interaction receives user input (e.g., through touching a specific graphic feature of the display) and enables the generation of additional information based on the selected feature. For example, if the user should select the IOB feature 2432, the display 2422 can be modified to generate the display 2428, which presents an enhanced view of the IOB data (e.g., formatted differently in some implementations and / or enlarged in some implementations) including explanatory information about what the residual insulin is and what it means, e.g., within the context of the user's current glucose information. In the example shown in Figure 24C, the display screen including the graphic display can be operable via software application icons (e.g., icon 2436) and / or event or notification display screens 2438 of the operating system of the mobile computing device.

[0268] The modified graphic display of the technology of the present invention can use animation to better convey information. In some implementations, various animations including pulsation and blinking can be used in combination with the graphic display as described above. FIG. 25 illustrates a modified graphic display that can use animation to convey health-related information. Pulsations or blinks of various speeds and rates can be used to convey different information. For example, pulsations in the pattern of a heartbeat can indicate that the modified graphic display is depicting raw data. By utilizing such animations, the graphic display can be presented in a more dynamic and lively human-like light, thereby eliminating or reducing the possibility of user errors due to misunderstandings of the graphic display. In some implementations, the arrow (the numerical value of the current glucose concentration at the center of a circle having a small arrow within the circumference of the circle indicating the future trend of the glucose value) in the modified graphic display including the magic glass 2502 can pulsate at different speeds to indicate information. For example, pulsation at a high speed can indicate urgency. In some implementations, various points on the glucose trend graphs 2504, 2506, and 2508 can pulsate at different speeds to indicate additional information. For example, the latest point 2510 on the trend graph 2504 can pulsate to indicate the current value. The pulsation can be different at different times, for example, pulsating at a slower speed at night when the user is sleeping. Modifying the graphic display with animation can also cause the system to reconfirm to the user that the system is operating and the monitoring is up-to-date. Alternatively, the absence of animation may indicate to the user that the system is offline or that the illustrated data may be outdated.

[0269] If the modified graphic display includes personalized customization from the user, the user is more likely to interact with the modified graphic display with interest and attention. FIG. 26 illustrates modified graphic displays 2602, 2604, 2606, and 2608 in which the user can customize one or more background images of the graphic display to illustrate the user's health data in the theme selected by the user. The background within display 2602 is customized to the background of the Star Wars (registered trademark) theme. The background within display 2604 is customized to a nature, religious, or motivational theme. The background of display 2606 is modified to reflect or assist in the study of the SAT exam. The background of display 2608 is customized to reflect a retro look and feel. SRDS can be generated using the customized background image or other user customizations. When one or more of the graphic displays as described above are modified, the customized background image or the user-selected theme can be incorporated into the modified graphic display and presented to the user.

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

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

[0272] In some implementations, as part of the setup procedure for a new receiver or a receiver used by a new user, the user will be asked to select a unique identifiable mark such as initials, screen background, color theme, screen saver, animation, or a combination thereof as described above. The user's selection can be displayed as part of a modified graphic display as described above. If initials, for example, initials 2804 in the modified display 2802 of FIG. 28, are selected, the initials 2804 can be displayed in a corner of the screen 2802 or in the status bar 2806 of the modified display 2808. If the screen is not displaying a modified graphic display, a screen saver can be applied. The selected theme can be flagged in the SRDS and applied to the entity's font, background, etc. when generating a modified graphic display as described above. The selected animation can also be flagged and referenced in the SRDS so that it is displayed when generating a modified graphic display as described above.

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

[0274] For example, when the blood glucose level drops by 70 mg / dL or more, or when the user's blood glucose level falls below the low threshold 2906, a hypoglycemia alarm state can be preset to trigger an alarm. The graphic display 2900 is generated to illustrate the analyte trend graph 2904, the low threshold line 2906, and other relevant diabetes management data such as the magic glass 2902. Other data obtained regarding the blood glucose reading and the user's state can enable the system 302 to predict that a modification of the previously set alarm state is desirable. For example, the user analyte measurement value and event data can suggest that the user's current blood glucose level is 110 mg / dL and is decreasing at a rate of 2 mg / dL per minute. At this rate, the user's blood glucose level can reach the alarm level of 70 mg / dL in about 20 minutes. In some cases, it may be undesirable or unsafe to delay corrective measures for 20 minutes. For example, there may be a need for a safety time of more than 20 minutes to effectively take corrective measures and achieve results before the analyte concentration value reaches an unhealthy range. When the system 302 determines that the user will reach the threshold in a time shorter than the safety time, it can overwrite the existing threshold linked to the alarm state, trigger the alarm state, and notify the user immediately. The system 302 can modify the graphic 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 generated immediately and the user is notified. The user can take corrective measures to avoid a serious condition.

[0275] The modification of the graphic display 2900 and the threshold 2906 can be accompanied by an audible alarm and a visual cue to notify the user of the change that has been made. For example, the low threshold line 2906 can move upward to its new position 2910, and the movement of the threshold line can be accompanied by an audible alarm and a blinking or sweeping motion of the line 2906 to its new position 2910. The arrow 2912 indicates the direction of movement and can prompt attention to the change by blinking, pulsating, or otherwise changing.

[0276] Figure 30 illustrates modified graphic displays 3002, 3004, 3006, 3008, and 3010 generated from a data structure and an arrangement of data, according to an embodiment in which the graphic displays 3002, 3004, 3006, 3008, and 3010 include a visual representation showing ranges of sample data. System 302 can define various ranges of the concentration of the sample data by default or automatically via user input. For example, the target range of the sample concentration can be defined as when the sample concentration value is a value between a desired high threshold and a low threshold. The attention range can be defined as a value close to one of these thresholds such that the sample concentration value is between the desired high threshold and the low threshold but can exceed the desired high threshold or fall below the desired low threshold in a short time. Outside the target range can be defined as when the concentration of the sample value exceeds the high threshold or falls below the low threshold. The high threshold and the low threshold used to determine the range of the sample data can be edited based on the anonymized data of other users and / or the sample data similarly placed by the user. The target range, the attention range, and outside the target range can be defined by the user or automatically by system 302 based on guidelines from a medical institution or a medical authority. For example, the target range can be defined from the guidelines of the American Diabetes Association (ADA) assuming that the fasting blood glucose level is less than 100 mg / dL and the blood glucose level two hours after a meal is less than 140 mg / dL. In some implementations, a sample concentration value exceeding 20% of the ADA guidelines can be considered within the attention range. For example, a sample concentration value less than 80 mg / dL when fasting is considered within the target range, a sample concentration value between 80 mg / dL and 100 mg / dL when fasting is considered within the attention range, and a sample concentration value exceeding 100 mg / dL is considered outside the target range.

[0277] Graphic displays 3002, 3004, 3006, 3008, and 3010 illustrate the magnitude of the sample data on the vertical axis and time on the horizontal axis. When generating graphic displays 3002, 3004, 3006, 3008, and 3010, various visual representation techniques can be used to modify the sample data to show the range of the sample data. Graphic display 3002 illustrates a modified graphic display of a graph of sample concentration values versus time magnitude, and the graphic is modified to illustrate the range of sample data with variable contrast or line style. In other implementations, color coding can be used to distinguish the target range, the attention range, and outside the target range. The self-referencing dataset that generates display 3002 can be modified when the sample data is flagged by an indicator of its range (e.g., target range, attention range, and outside the target range). When generating graphic display 3002, each flag can be given a line style, contrast, thickness, or other distinguishable visual representation indicator, and subsequent pixels can be generated on display 3002 based on these indicators. In exemplary embodiment 3002, sample data within the target range can be flagged and indicated by line style 3012. Sample data within the attention range can be flagged, and their corresponding flags can be associated with line style 3014. Sample values outside the target range can be flagged, and their corresponding flags can be assigned line style 3016. As described, other visual representation indicators such as color, gradient, other line styles, or animations can be used. Visual representation indicators associated with the attention range or outside the target range can be selected to quickly draw attention to the information being conveyed. For example, a darker contrast line 3016 can be used to indicate sample values outside the target range.

[0278] The graphic display 3004 is similar to the graphic display 3002. Specimen data within the target range can be further displayed via a rectangle 3018 surrounding the target specimen value. Specimen values within the attention range can be highlighted in the area under the curve shaded in style 3020. Specimen values outside the target range can be highlighted in the area under the curve shaded in a style 3022 different from style 3020 to provide a visual difference and draw the user's attention.

[0279] The graphic display 3006 is similar to the graphic display 3004. Specimen values within the target range are subtracted and not shown to highlight specimen values outside the attention range and outside the target range that may cause health problems and may require attention and corrective measures. The graphic display 3006 enables the user to view specimen values 3024 within the attention range and specimen values 3026 outside the target range.

[0280] The graphic displays 3008 and 3010 use adaptive target region technology, whereby the graphic display is modified to account for variations in specimen data expected to occur regardless of diabetes status. For example, non-diabetics may experience a peak in blood glucose levels after a meal, similar to diabetics. For example, the graphic display 3008 can be modified to adjust the attention region 3028 based on event data obtained from the user and / or sensor. Such adjustments may be desirable to avoid unnecessarily alarming the user. For example, if a meal event is detected, an increase in the user's blood glucose level may be expected and normal. The attention range 3028 within the relevant time frame can be adjusted to account for the expected increase in blood glucose level, for example, by shading the area under the curve within the attention region 3028 having the same shading as used within the target specimen value. The graphic display 3010 uses the same adaptive target region technology described in relation to display 3008, but specimen values within the target range are subtracted and specimen values within the attention range 3030 and outside the target range 3032 are further highlighted and not shown to draw attention.

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

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

[0283] Display 3106 is similar to display 3102. The user's current blood glucose level 3116 has dropped to 54 mg / dL, which is the lower limit of the desired analyte concentration value. The trend indicator 3118 is updated to show the current and future trends of the analyte concentration value. The arrow 3117 has changed shape and is updated to point dramatically downward. The circle 3122 is updated and filled with a shadow style 3138 different from the shadow style of circle 3122 to draw attention to the current analyte concentration value. The text description 3120 is also updated with appropriate text indicating that the analyte concentration value is low and continues to drop rapidly. The low threshold line 3130 is updated and rendered in a style 3140 different from line style 3130 to draw attention to the current low value of the analyte concentration. In some embodiments, the different style of line 3140 may include rendering the line in a larger, higher-contrast style to draw attention. The dot 3126 is updated and rendered in a style 3142 different from the style used to generate dot 3126 to draw additional attention to the low value of the analyte concentration. The dot 3142 and the circle 3138 can be rendered in the same style, and the fading ring surrounding them can pulsate at the same rate to draw attention to the low analyte concentration value. In some embodiments, the low threshold line 3140 can pulsate at the same rate as the dot 3142, the circle 3138, or the fading ring surrounding them.

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

[0285] As described above, the specimen graph 3124 of the specimen data value can be displayed at a location where the magnitude of the specimen value is plotted over a certain period. The current value of the specimen data can be indicated by a pulsation graphic 3126, for example, a graphic including one or two concentric circles that fade stepwise in the radial direction. The specimen graph 3124 and the data structure that generates the specimen graph 3124 can be dynamically updated based on the current specimen sensor data. The displays 3102, 3104, 3106, or the data structure that generates a similar display can be modified to display one or more pulsation animations that can pulsate synchronously to further attract the user's attention to information related to health management. Examples of display elements that can be modified or rendered with a pulsating animation include the trend indicator 3118, the current specimen value dot 3126, and the threshold lines 3128 and 3130.

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

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

[0288] For example, without limitation, the monitoring systems and methods described may include sensors that measure the concentration of one or more analytes (e.g., glucose, lactate, potassium, pH, cholesterol, isoprene, and / or hemoglobin) and / or receptors and / or other blood or body fluids of or related to another party.

[0289] By way of example, without limitation, embodiments of the monitoring systems and methods described herein may include finger stick blood sampling, blood analyte test strips, non-invasive sensors, wearable monitors (e.g., smart bracelets, smart watches, smart rings, smart necklaces or pendants, exercise monitors, fitness monitors, health and / or medical monitors, clip-on monitors, etc.), adhesive monitors, smart textiles and / or clothing-integrated sensors, shoe inserts and / or insoles containing sensors, transdermal (i.e., through the skin) sensors, and / or ingestible, inhaled, or implantable sensors.

[0290] In some embodiments, without limitation, the monitoring systems and methods may include an inertial measurement unit including an accelerometer, gyroscope, magnetometer, and / or barometer; movement, altitude, position, and / or location sensors; biometric sensors; optical sensors such as, for example, a photoplethysmogram (PPG) / pulse oximeter, fluorescence monitor, and camera; wearable electrodes; electrocardiogram (EKG or ECG), electroencephalogram (EEG), and / or electromyogram (EMG) sensors; chemical sensors; flexible sensors for measuring, for example, stretch, displacement, pressure, weight, or shock; galvanometric sensors, capacitive sensors, electrolytic sensors, temperature / thermal sensors, microphones, vibration sensors, ultrasonic sensors, piezoelectric / piezoresistive sensors, and / or other sensors instead of or in addition to the sensors described herein, such as transducers for measuring information of or related to a receptor and / or another party.

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

[0292] Various embodiments have been described with reference to their specific exemplary features. However, it will be apparent that various modifications and changes can be made to them without departing from the broader spirit and scope of the various embodiments recited in the appended claims. Accordingly, the specification and figures should be regarded in an illustrative rather than a limiting sense.

[0293] Although described above from the perspective of various exemplary embodiments and implementations, the various features, aspects, and functions described in one or more of the individual embodiments are not limited in their applicability to the particular embodiments in which they are described. Instead, such features can be applied, alone or in various combinations, to one or more of the other embodiments of the present application, regardless of whether such embodiments are described and whether such features are presented as part of the embodiments in which they are described. Thus, the breadth and scope of the present application should not be limited by any of the exemplary embodiments described above.

[0294] The terms and phrases used in this application, and variations thereof, should be construed liberally rather than restrictively, unless otherwise specified. By way of example, the term "comprising" should be read to mean "including but not limited to", the term "example" is used to provide illustrative examples of the item under consideration and is not an exhaustive or limiting list, the term "one" or "a" should be read to mean "at least one", "one or more", etc., and adjectives such as "conventional", "conventional type", "ordinary", "standard", "known", etc. and terms of similar meaning should not be construed as limiting the item described to items available during a given period or with respect to a given time, but rather should be read to include conventional, conventional type, ordinary, or standard technology that is available or may become known at any time, present or future. Similarly, when this specification refers to technology that is apparent or known to those of ordinary skill in the art, such technology includes technology that is apparent or known to those of ordinary skill in the art at any time, present or future.

[0295] The presence of broad phrases and terms such as "one or more", "at least", "including but not limited to", or other similar phrases in some examples is not to be read as meaning that a narrower case is intended and required in examples where such broad phrases may not be present. The use of the term "module" does not imply that components or functions described or claimed as part of a module are all configured in a common package. In fact, any or all of the various components of a module may be combined in a single package, whether they are control logic or other components, or may be maintained separately, or may be distributed among multiple groups or packages, or in multiple locations.

[0296] Furthermore, the various embodiments described herein are presented from the perspectives of exemplary block diagrams, flowcharts, and other illustrations. As will be apparent to those skilled in the art after reading this specification, the illustrated embodiments and their various alternatives can be implemented without being limited to the illustrated examples. For example, the block diagrams and their accompanying descriptions should not be construed as requiring a particular architecture or configuration.

Description of Reference Numerals

[0297] 8 Specimen Sensor System 10 Specimen Sensor 12 Sensor Electronic Equipment Module 100 System 110 Specimen Display Device 120 Mobile Phone 130 Tablet 140 Smart Watch 112, 122, 132, 142 Touch Screen Display 134 Server System 136 Medical Device 138 Wireless Access Point 200 Housing 208 Adhesive Pad 214 Mounting Unit 234 Base 236 Contact Sub-Assembly 238 Contact 248 Hinge 300 System 302 System 305 Communication Medium 308 Specimen Sensor System 310 Display Device 315, 355 Connection Interface 320, 360 Transceiver 325, 365 Storage Device 330 Specimen Sensor Application 334 Server System 334a Server 334b Storage Device 334c Processor 335, 380 Processor / Microprocessor 340 Graphic User Interface 345 Display 350, 385 Real-Time Clock 370 Sensor Measurement Circuit 375 Sensor

Claims

1. It is a system, A continuous sample sensor configured to obtain receptor sample data, The system includes a wireless transmitter configured to receive sample data from the continuous sample sensor and transmit the sample data to a processing module, The processing module receives the sample data and event data of the receptor, Generating a graphic display on a mobile computing device to display a visual representation showing one or more relationships between the sample data and the event data, either mutually or in relation to time, wherein the display of the sample data or the event data is enlarged or reduced in response to user operation, and the display includes the heart rate at which the event data reaches a threshold. A system configured to automatically correct the graphic display upon receiving user input and to isolate areas of the sample data that exceed one or more threshold sample values.

2. The aforementioned sample data includes glucose data, The processing module is further configured to receive insulin data from the receptor, The system according to claim 1, wherein the visual representation shows one or more relationships between the insulin data, the glucose data, and the event data, either with respect to each other or with respect to time, and the display of the insulin data, the sample data, or the event data is enlarged or reduced in response to user operation.

3. The system according to claim 2, wherein the insulin data includes a value of residual insulin, and the visual representation includes a colored ring indicating the residual insulin and an estimated remaining time for the residual insulin.

4. The system according to claim 2, wherein the visual representation includes a trend graph of glucose data and an interactive callout window associated with the region or feature of the trend graph, which is presented when the user selects a region or feature of the trend graph on the graphic display, and the presented callout window includes at least some of the insulin data or the event data.

5. The system according to claim 4, wherein the presented callout window is configured to display a graphic array of insulin data, which includes one or more of the following: bolus or basal insulin, bolus insulin administration time, basal insulin administration time, or residual insulin value.

6. The system according to claim 4, wherein the presented callout window is configured to display a graphic array of the event data, including one or more of the following: carbohydrate intake, time spent exercising, calories burned, or heart rate associated with time at which a threshold is reached.

7. The system according to claim 2, wherein the visual representation includes an arrow corresponding to the insulin data and a glucose reading including a glucose trend graph corresponding to the glucose data, the arrow being displayed in close proximity to the glucose trend graph and indicating the effect of the insulin data on the glucose data.

8. The system according to claim 2, wherein the visual representation includes trend graphs of past glucose data and future glucose data, and the future glucose data is determined based on the insulin data and behavioral data of the receptor.

9. The aforementioned visual representation, A first graphic display illustrating the current value of the glucose data and an indicator of the future trend of the glucose data, The system according to claim 2, comprising: a second graphic representation of the amount of insulin based on the insulin data, wherein the second graphic representation interacts with the first graphic representation to illustrate the possible effect of the amount of insulin on the index of the future trend of the glucose data.

10. The one or more threshold sample values ​​include a high glucose threshold and a low glucose threshold, and the processing module is The current glucose level is compared with the high glucose threshold and the low glucose threshold to generate a glucose score. The current residual insulin level is compared to high and low insulin thresholds to generate an IOB score, and The glucose score and the IOB score are multiplied to generate an insulin state, The system according to claim 2, further configured to rank the insulin score into one of several categories.

11. The system according to claim 10, wherein the plurality of categories include good categories, caution categories, and bad categories.

12. The system according to claim 11, wherein the visual representation includes a colored display, each of the multiple categories being associated with a different color, and the color associated with the ranked insulin score is illustrated.

13. The aforementioned processing module The system is further configured to generate one or more datasets based on the operation of the receptor and the prediction of the sample data trend based on the operation of the receptor, respectively. The system according to claim 1, wherein the visual representation includes a scrollable list containing one or more modified graphs based on one or more datasets.

14. The system according to claim 1, further comprising a look-ahead module configured to receive input data for the receptor associated with current or future event data, wherein the visual representation includes a sample trend graph, and the processing module is further configured to modify the visual representation based on the input data to show the predicted effect of the current or future event data on the sample trend of the receptor.

15. The system according to claim 14, wherein the current or future event data includes data indicating at least one of exercise, insulin administration, food intake, stress, and disease.

16. The system according to claim 14, wherein the predicted effect is generated using a model based on a patient population and sample-related data of the patient population.

17. The system according to claim 14, wherein the processing module is further configured to modify the graphic display in response to user input to display a scrollable list of current or future event data and one or more visual representations showing sample trend values ​​influenced by the current or future event data.

18. The system according to claim 1, wherein the one or more threshold sample values ​​include a high sample threshold and a low sample threshold, the visual representation includes a trend graph of the sample data, the region between the trend graph and the high sample threshold is a first color, and the region between the trend graph and the low sample threshold is a second color.

19. The system according to claim 1, wherein the processing module is configured to generate the graphic display by forming one or more datasets including at least some of the sample data and the event data; flagging additional information or embedding the additional information into at least some of the one or more datasets; and generating a self-referencing dataset containing all the information and data necessary to generate the graphic display within a graphically modified array that shows one or more features in the data.

20. The user input includes the user selection of a high threshold region or feature in the graphic display. The one or more threshold sample values ​​include a high threshold sample value, The system according to claim 1, wherein the processing module is configured to automatically correct the graphic display and separate the regions of the sample data that exceed one or more threshold sample values, and further comprising the processing module being configured to automatically correct the graphic display and separate the regions of the sample data that exceed a high threshold sample value.

21. The user input includes the user selection of a low threshold region or feature in the graphic display. The one or more threshold sample values ​​include a low threshold sample value, The system according to claim 1, wherein the processing module is configured to automatically correct the graphic display and separate the regions of the sample data that exceed one or more threshold sample values, and further comprising the processing module being configured to automatically correct the graphic display and separate the regions of the sample data that exceed the low threshold sample value.

22. The system according to claim 1, wherein the region of the sample data that exceeds one or more threshold sample values ​​is separated by visual representation and distinguished by at least one of shading, gradient, or color intensity which is different from the other region of the sample data that does not exceed one or more threshold sample values.

23. The system according to claim 22, wherein the processing module is further configured to modify the graphic display in response to user input to display an icon or visual representation indicating the percentage of the sample data that exceeds one or more threshold sample values.

24. The system according to claim 23, wherein the thickness, color intensity, or opacity of the icon or visual representation displayed on the display is determined based on the percentage.

25. A method performed by a computer, The sample monitoring device obtains sample data for receptors, The wireless transmitter transmits the sample data of the receptor, The processing module receives the sample data and event data of the receptor, and generates a graphic display on a mobile computing device to display a visual representation showing one or more relationships between the sample data and the event data, either mutually or in time, wherein the display of the sample data or the event data is enlarged or reduced in response to user operation, and the display includes the heart rate at which the event data reaches a threshold. A method comprising: receiving user input, automatically correcting the graphic display to isolate areas of the sample data that exceed one or more threshold sample values.

26. The aforementioned sample data includes glucose data, The processing module is further configured to receive insulin data from the receptor, The visual representation shows one or more relationships between the insulin data, glucose data, and event data, either with respect to each other or with respect to time, and the display of the insulin data, sample data, or event data is enlarged or reduced in response to user operation. The method according to claim 25, wherein the event data includes one or more of insulin administration, carbohydrate intake, or exercise.

27. The system according to claim 15, wherein the current or future event data includes data indicating at least one of the following: type of exercise, duration of exercise, intensity of exercise, type of insulin administration, amount of insulin administration, amount of food, and content of food.

28. A non-temporary computer-readable storage medium storing executable program instructions, wherein when the executable program instructions are executed by one or more computing devices, the one or more computing devices... By using a continuous sample sensor, sample data of receptors can be obtained, The wireless transmitter receives and transmits the sample data of the receptor, The processing module receives the sample data and event data of the receptor, To generate a graphic display on a mobile computing device and display a visual representation showing one or more relationships between the sample data and the event data, either mutually or in relation to time, wherein the display of the sample data or the event data is enlarged or reduced in response to user operation, and the display includes the heart rate at which the event data reaches a threshold. A non-temporary computer-readable storage medium that, upon receiving user input, performs an operation including modifying the graphic display to isolate areas of the sample data that exceed one or more threshold sample values.

29. The method further includes receiving diabetes-related data from the receptor and generating an interactive graphic display on the mobile computing device, A non-temporary computer-readable storage medium according to claim 28, wherein a viewer can interact with the interactive graphic display.

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