Optimized transmission of analyte data in multi-receiver environments

Abstract

In an embodiment, one general aspect includes a method of optimizing data transmission from a device to a remote target. The method includes receiving analyte measurements from a continuous analyte monitoring (CAM) system. The method also includes determining a current status of a connection between the device and the CAM system. The method also includes conditionally transmitting data related to the analyte measurements over a network to a remote target based on the current status of the connection.

Description

OPTIMIZED TRANSMISSION OF ANALYTE DATA IN MULTI-RECEIVER ENVIRONMENTSCROSS-REFERENCE TO RELATED APPLICATIONS

[0001] This application claims priority to and benefit of U.S. Provisional Patent Application No. 63 / 701,057 filed September 30, 2024, which application is hereby expressly incorporated by reference herein in its entirety as if fully set forth below and for all applicable purposes.INTRODUCTION

[0002] Diabetes is a metabolic condition affecting hundreds of millions of people. For these people, monitoring blood glucose levels and regulating those levels to be within an acceptable range is important not only to mitigate long-term issues such as heart disease and vision loss, but also to avoid the effects of hyperglycemia and hypoglycemia. Maintaining blood glucose levels within an acceptable range can be challenging, as glucose levels are almost constantly changing over time and in response to everyday events, such as eating or exercising. Advances in medical technologies have enabled development of various systems for monitoring blood glucose, including continuous glucose monitoring (CGM) systems, which measure and record glucose concentrations in substantially real-time. CGM systems are important tools for users of these systems to ensure that measured glucose values are within the acceptable range.SUMMARY

[0003] In some embodiments, one general aspect includes a method of optimizing data transmission from a device to a remote target. The method includes receiving analyte measurements from a continuous analyte monitoring (CAM) system. The method also includes determining a current status of a connection between the device and the CAM system. The method also includes conditionally transmitting data related to the analyte measurements over a network to a remote target based on the current status of the connection.

[0004] In some embodiments, another general aspect includes a system for optimizing data transmissions from a device to a remote target. The system includes a continuous analyte monitoring (CAM) system configured to generate measurements associated with an analyte level of a patient. The system also includes a device in data communication with the CAM system. Thedevice is configured to perform one or more operations. The one or more operations include receiving analyte measurements from the CAM system, determining a current status of a connection between the device and the CAM system, and conditionally transmitting data related to the analyte measurements over a network to a remote target based on the current status of the connection.

[0005] In some embodiments, another general aspect includes a computer-program product. The computer-program product includes a non-transitory computer-usable medium having computer-readable program code embodied therein. The computer-readable program code is adapted to be executed to implement a method of optimizing data transmission from a device to a remote target. The method includes receiving analyte measurements from a continuous analyte monitoring (CAM) system. The method also includes determining a current status of a connection between the device and the CAM system. The method also includes conditionally transmitting data related to the analyte measurements over a network to a remote target based on the current status of the connection.BRIEF DESCRIPTION OF THE DRAWINGS

[0006] FIG. 1A illustrates an example of a therapy management system, in accordance with certain embodiments.

[0007] FIG. IB illustrates an example continuous analyte monitoring system including an example continuous analyte sensor(s) with sensor electronics, in accordance with certain embodiments.

[0008] FIG. 2 illustrates example inputs and example outputs that are generated based on the inputs, in accordance with certain embodiments.

[0009] FIG. 3 illustrates an example of a medical support system 300 for making a patient’s health data available to one or more other users, in accordance with certain embodiments.

[0010] FIG. 4 illustrates an example of a process for optimizing transmission of analyte data in multi-receiver environments, in accordance with certain embodiments.

[0011] FIG. 5 illustrates an example of a process for optimizing transmission of analyte data in multi-receiver environments based on a current connection status, in accordance with certain embodiments.

[0012] FIG. 6 illustrates an example of a process for optimizing transmission of analyte data in multi-receiver environments based on a combination of urgency and current connection status, in accordance with certain embodiments.

[0013] FIG. 7 illustrates an example of a process for optimizing transmission of analyte data in multi-receiver environments via inter-device communication, in accordance with certain embodiments.

[0014] FIG. 8 illustrates another example of a process for optimizing transmission of analyte data in multi-receiver environments via inter-device communication, in accordance with certain embodiments.

[0015] FIG. 9 is a block diagram depicting a computer system configured for optimizing transmission of analyte data in multi-receiver environments, in accordance with certain embodiments.DETAILED DESCRIPTION

[0016] In a continuous analyte monitoring (CAM) system, an analyte sensor measures analyte levels of a patient and communicates the raw sensor measurements to a transmitter, which can then transmit corresponding analyte values to the patient's device (e.g., a display device such as a mobile phone). The patient can use their device to monitor the health and collect health data (e.g., analyte data). An example of a CAM system is a continuous glucose monitoring (CGM) system. For illustrative purposes, examples will be periodically described herein relative to CGM systems.

[0017] Current research has shown that patients with CGM systems can benefit from having social support that helps the patient manage their health and medical conditions, such as diabetes. For example, patients with social support can have a better experience with CGM systems, better self-management, and better health outcomes than patients without social support. Such social support can involve, for example, providing emotional and mental support, monitoring the patient's glucose data (and / or other health data), encouraging the patient to meet milestones or challenges related to diabetes management, and the like.

[0018] Consequently, many applications are being developed to provide social support services to patients with certain medical conditions, such as diabetes. An example analyte monitoring application (e.g., CGM application) that provides social support services can allow apatient to publish (e.g., make available) their glucose data to one or more other users (also referred to herein as supporters). For example, the patient can invite, via the analyte monitoring application, one or more supporters to download an analyte monitoring application on the supporter's computing device (e.g., mobile phone). A supporter that receives the invite can accept the invitation, download the analyte monitoring application, and use the analyte monitoring application to monitor the patient's glucose data. For example, the analyte monitoring application can allow the supporter to view the patient's glucose data in (near) real-time, receive alerts when the patient's glucose values meet a predetermined condition (e.g., exceeds a first threshold or drops below a second threshold), and the like.

[0019] Currently, to publish the patient's glucose data to a supporter, the patient's CGM transmitter, for example, can transmit the patient's glucose data to the patient's device (e.g., a display device such as a smartphone). The patient's device can then transmit the patient's glucose data to a cloud computing environment for storage using, for example, a cellular communication connection or Wi-Fi communication connection. The cloud computing environment can then forward the patient's glucose data, and / or alerts based thereon, to the supporter's device (e.g., a display device such as a smartphone), thereby allowing the supporter to view the patient's glucose data and / or alerts substantially in real-time.

[0020] While methods such as the foregoing allow supporters to view a patient's glucose data and / or alerts related thereto, technical challenges still exist. Tn some instances, the patient’s device may experience a communication disruption that prevents the device from timely publishing glucose data to supporters. In an example, connectivity issues between the patient’s device and the cloud computing environment (e.g., hardware, software, and / or configuration problems) may prevent the patient’s glucose data from being sent to the cloud server and, hence, to the supporter’s device. In another example, connectivity issues between the patient’s device and the CGM transmitter may prevent the patient’s device from receiving the glucose data in the first place. In some cases, such connectivity issues may result from the smartphone not being with the patient during certain activities (e.g., if the patient leaves behind a smartphone to run, swim, etc.). Such disruptions can compromise patient health. If, for example, the patient's device is unable to publish or provide the patient's glucose data when the patient is experiencing a hypoglycemic or hyperglycemic episode, then the patient's device is unable to notify the supporter, and the supporter is unable to help the patient.

[0021] Certain solutions to the above problem, which are further outlined in this disclosure, can configure multiple receiver devices (c.g., display devices such as a smartphone, smartwatch, tablet, augmented reality (AR) and / or virtual reality (VR) headset, etc.) to each directly communicate with, and obtain glucose data from, a single CGM sensor. Advantageously, in certain aspects, each of the different devices, such as a smartphone and smartwatch, can then separately transmit the obtained glucose data to the cloud computing environment. In this way, if, for example, the patient leaves behind a smartphone while running or swimming, glucose data can still be transmitted to the cloud server by another device on or with the patient (e.g., the patient’s smartwatch). Similarly, if one of the patient’s devices (e.g., a display device such as a smartwatch) experiences a connectivity issue that prevents the transmission of glucose data to the cloud server, the glucose data can still be transmitted to the cloud server by another patient device not experiencing the issue (e.g., another display device such as a smartphone).

[0022] Although utilization of multiple patient devices can provide greater communication reliability, such utilization presents further technical challenges. For example, when multiple different receiver devices receive CGM data directly from a single sensor, each device may transmit the same or overlapping CGM data to the cloud computing environment, which data may then be received and stored by the cloud computing environment. Furthermore, the cloud computing environment may present redundant alerts to supporters, where each of these redundant alerts may need to be viewed by the supporting user as if it represents distinct information regarding an event or condition. Redundancies such as the foregoing potentially waste storage, compute resources, and network bandwidth of multiple devices and systems, including, but not limited to, the patient devices, supporter devices, and the cloud computing environment.

[0023] Due to the aforementioned redundancies, supporters may be confused by, and / or lose trust in, received glucose data. As a result, supporters may be hesitant to act on such information. This hesitance may negatively impact the health of the patient providing the glucose data. In some cases, the supporter’s confusion may result in the patient being given the wrong treatment, such as a wrong amount treatment (e.g., an excess amount of glucose or insulin), based on a mistaken belief that the redundancy indicates elevated urgency.

[0024] Additionally, some software applications, for example, on a supporter device, may show and analyze deltas between incoming readings. Duplicate data may negatively impact thisanalysis. For example, the delta for two duplicate readings may be shown as zero, which may be misleading and, moreover, mask a much more serious condition. For example, duplicate readings of 75 mg / dL may trigger an erroneous belief that the patient’s glucose levels are stable when, in actuality, the levels may be rapidly progressing towards hypoglycemia.

[0025] When the above redundancy problems are viewed collectively across a population of patients whose supporters are all experiencing the same or similar' redundancies, the potential for resource inefficiency and confusion is immense. Resource inefficiency and confusion may have the cumulative effect of discouraging utilization by supporters and / or cause supporters to be less attentive to glucose data and alerts, either of which could negatively impact the health of significant numbers of patients.

[0026] Additionally, redundancies of the type described above are technically challenging to eliminate. Different patient devices may be in range of a CGM transmitter at different times. For example, a smartphone and a smartwatch may each be with the patient at some times but not others. Current systems generally lack real-time information regarding which devices are available to receive CGM data at any given instant in time.

[0027] In response to the above problems, the present disclosure describes certain aspects of optimizing transmission of analyte data in multi-receiver environments. In certain aspects, to reduce or eliminate possible redundancy, an analyte monitoring application on each patient device can be configured to conditionally transmit analyte data to a remote target, such as a server system or cloud computing environment, based on predetermined criteria, such that transmission is enabled if the criteria is satisfied and prevented otherwise. The predetermined criteria can relate, for example, to the device, which other devices are connected to the same analyte sensor, the analyte data itself, and / or other data.

[0028] In certain aspects, the conditional transmission of analyte data can be based on a current status of a device’s connection with a transmitter associated with an analyte sensor. For example, the analyte monitoring application on a given patient device can enable the device to transmit the analyte data to the remote target if it is the only device currently connected to an analyte sensor, or if it is the highest priority such device according to any suitable criteria (e.g., criteria based on user ranking, device type, device capabilities, etc.). Conversely, according to this example, the analyte monitoring application can prevent such transmission if another, higher priority device iscurrently connected to the analyte sensor, thus deferring to the higher priority device. Advantageously, in certain embodiments, the prevention of transmission can eliminate potential redundant transmission and improve resource utilization, particularly when multiple analyte monitoring applications on multiple patient devices execute the same or consistent conditional transmission logic. In some cases, the analyte monitoring application can verify other device connections via inter-device communication.

[0029] In certain aspects, the conditional transmission of analyte data can be based on urgency criteria related to the analyte data. The urgency criteria can correspond, for example, to dangerously high or low analyte levels, such as hyperglycemic or hypoglycemic thresholds in the case of glucose levels. For example, if the analyte monitoring application on a given patient device determines that the analyte data does not satisfy the urgency criteria, the analyte monitoring application can enable or prevent transmission based on a connection status or other criteria, as discussed above. However, if the analyte monitoring application determines that the analyte data satisfies the urgency criteria, the analyte monitoring application can enable the device to transmit the analyte data to the remote target, regardless of whether other devices may also transmit the same data.

[0030] The techniques described herein for optimizing transmission of analyte data are described more fully herein with respect to FIGS. 1A-B and 2-7 below. Note that although certain aspects herein are described with respect to the management of diabetes, a CGM system, a CGM application, and the transmission of analyte measurements between devices, the protocols and techniques described herein are similarly applicable to any type of health management system that includes any type of analyte sensor (e.g., lactate sensor, ketone sensor, etc.), any type of health management application, and / or transmission of any type of analyte data. For example, a lactate sensor may be used to monitor for events indicative of sepsis based on lactate thresholds, or a ketone sensor may be used to monitor for ketoacidosis based on ketone thresholds. Additionally, note that, hereinafter, although certain aspects described herein may periodically refer to an analyte monitoring device performing various techniques described herein for transmitting analyte data, it is the transmitter in the analyte monitoring device that performs the various techniques described herein for transmitting analyte data.

[0031] As used herein, the term “continuous” analyte monitoring refers to monitoring one or more analytes in a fully continuous, semi-continuous, periodic manner, which results in a data stream of analyte values over time. A data stream of analyte values over time is what allows for meaningful data and insights to be derived using the algorithms described herein for optimizing transmission of analyte data in multi-receiver environments. In other words, single point-in-time measurements collected as a result of a patient visiting their health care professional every few months results in sporadic data points (e.g., that are, at best, months apart in timing) that cannot form the basis of any meaningful data or insight to be derived. As such, without the CAM system of the embodiments herein, it is simply impossible to continuously optimize transmission of analyte data in multi-receiver environments, as described herein.

[0032] Further, the data stream of analyte values collected over time, with the CAM system presented herein, include real-time analyte values, which allows for deriving meaningful data and insight in real-time using the systems and algorithms described herein. The derived real-time data and insight in turn allows for optimizing transmission of analyte data in multi-receiver environments. Real-time analyte values herein refer to analyte values that become available and actionable within seconds or minutes of being produced as a result of at least one sensor electronics module of the CAM system (1) converting sensor current(s) (i.e., analog electrical signals) generated by the continuous analyte sensor(s) into sensor count values, (2) calibrating the count values to generate at least glucose and / or other analyte concentration values using calibration techniques described herein to account for the sensitivity of the continuous analyte sensor(s), and (3) transmitting measured glucose and / or other analyte concentration data, including glucose and / or other analyte concentration values, to a display device via wireless connection.

[0033] For example, the at least one sensor electronics module may be configured to sample the analog electrical signals at a particular sampling period (or rate), such as every 1 second (1 Hz), 5 seconds, 10 seconds, 30 seconds, 1 minute, 3 minutes, 5 minutes, etc., and to transmit the measured glucose and / or other analyte concentration data to a display device at a particular transmission period (or rate), which may be the same as (or longer than) the sampling period, such as every 1 minute (0.016 Hz), 5 minutes, 10 minutes, etc.

[0034] The real-time analyte data that is continuously generated by the CAM system described herein, therefore, allows the therapy management system herein to optimize transmission ofanalyte data in multi-receiver environments, in real-time, which is technically impossible to perform using existing or conventional techniques or systems. Further, because of the real-time nature of this data, it is also humanly impossible to continuously process a real-time data stream of analyte values over time to derive meaningful data and insight using the algorithms and systems described herein to optimize transmission of analyte data in multi-receiver environments. In other words, deriving meaningful data and insight from a stream of real-time data that is continuously generated, processed, calibrated, and analyzed, using the algorithms and systems described herein, is not a task that can be mentally performed. For example, executing the algorithms described in relation to FIGS. 3-7, in real-time and on a continuous basis, which would involve using a stream of real-time data that is continuously generated by a patient’s CAM system and / or significantly large amount of population data (e.g., hundreds or thousands of data points for each one of thousands or millions of patients in the patient population) is not a task that can be mentally performed, especially in real-time at times.

[0035] Further, certain embodiments herein are directed to a technical solution to a technical problem associated with CAM systems. In particular, each CAM system that is manufactured by a CAM system manufacturer might perform slightly differently. As such, there might be inconsistencies between sensors and the measurements they generate once in use. Accordingly, certain embodiments herein are directed to determining the performance of a CAM system during a manufacturing calibration process in vitro), which includes quantifying certain sensor operating parameters, such as a calibration slope (also known as calibration sensitivity), a calibration baseline, etc.

[0036] Generally, calibration sensitivity refers to the amount of electrical current produced by an analyte sensor of a CAM system when immersed in a predetermined amount of a measured analyte. The amount of electrical current may be expressed in units of picoAmps (pA) or counts. The amount of measured analyte may be expressed as a concentration level in units of milligrams per deciliter (mg / dL), and the calibration sensitivity may be expressed in units of pA / (mg / dL) or counts / (mg / dL). The calibration baseline refers to the amount of electrical current produced by the analyte sensor when no analyte is detected, and may be expressed in units of pA or counts.

[0037] The calibration sensitivity, calibration baseline, and other information related to the sensitivity profile for the CAM system may be programmed into the sensor electronics module ofthe CAM system during the manufacturing process, and then used to convert the analyte sensor electrical signals into measured analyte concentration levels. For example, the calibration slope (calibration sensitivity) may be used to predict an initial in vivo sensitivity (Mo) and a final in vivo sensitivity (Mf), which are programmed into the sensor electronics module and used to convert the analyte sensor electrical signals into measured analyte concentration levels.

[0038] In certain embodiments, during in vivo use, the sensor electronics module of a CAM system samples the analog electrical signals produced by the analyte sensor to generate analyte sensor count values, and then determines the measured analyte concentration levels based on the analyte sensor count values, the initial in vivo sensitivity (Mo), and the final in vivo sensitivity (Mf). For example, measured analyte concentration levels may be determined using a sensitivity function M(t) that is based on the initial in vivo sensitivity (Mo) and the final in vivo sensitivity (Mf). The sensitivity function M(t) may expressed in several different ways, such as a simple correction factor that is not dependent on elapsed time (ti) of in vivo use, a linear relationship between sensitivity and time (ti), an exponential relationship between sensitivity and time (ti), etc. Equation 1 presents one technique for determining a measured analyte concentration level (ACL) from an analyte sensor count value (count) at a time L:ACL = count / M(ti) Eq. 1A calibration baseline (baseline) may also be used to determine a measured analyte concentration level (ACL) from an analyte sensor count value (count) at a time ti, and Equation 2 presents one technique:ACL = (count - baseline) I M(ti) Eq. 2

[0039] FIG. 1A illustrates an example of a therapy management system 100 for optimizing transmission of analyte data in multi-receiver environments, in accordance with certain embodiments of the disclosure. The therapy management system 100 may be utilized for generating and presenting information related to user health, for example, using various user interfaces associated with system 100. Each user of system 100, such as user 102, may interact with a mobile health application, such as mobile health application (“application”) 106 (e.g., a diabetes intervention application that provides therapy management guidance), and / or a health monitoring device, such as a CAM system 104 (e.g., a CGM system). User 102, in certain embodiments, may be the patient or, in some cases, the patient’s caregiver. In the embodimentsdescribed herein, the user is assumed to be the patient for simplicity only, but is not so limited. As shown, CAM system 100 may include a CAM system 104, a display device 107 that executes application 106, a therapy management engine 112, and a user database 110.

[0040] CAM system 104 may be configured to generate time-series data, such as analyte measurements (e.g., sensor data), for the user 102, e.g., on a continuous basis, and transmit the analyte measurements to the display device 107 for use by application 106. In some embodiments, the CAM system 104 may transmit the analyte measurements to the display device 107 through a wireless connection (e.g., Bluetooth connection). In certain embodiments, display device 107 is a small phone. However, in certain embodiments, display device 107 may instead be any other type of computing device such as a laptop computer, a smartwatch, a tablet, or any other computing device capable of executing application 106.

[0041] Note that, while in certain examples the CAM system 104 is assumed to be a CGM system, CAM system 104 may operate to monitor one or more additional or alternative analytes. As discussed, the term “analyte” as used herein is a broad term, and is to be given its ordinary and customary meaning to a person of ordinary skill in the ait (and is not to be limited to a special or customized meaning), and refers without limitation to a substance or chemical constituent in the body or a biological sample (e.g., bodily fluids, including, blood, serum, plasma, interstitial fluid, cerebral spinal fluid, lymph fluid, ocular fluid, saliva, oral fluid, urine, excretions, or exudates).

[0042] Analytes can include naturally occurring substances, artificial substances, metabolites, and / or reaction products. In some embodiments, the analyte measured and used by the devices and methods described herein may include albumin, alkaline phosphatase, alanine transaminase, aspartate aminotransferase, bilirubin, blood urea nitrogen, calcium, CO2, chloride, creatinine, glucose, gamma-glutamyl transpeptidase, hematocrit, lactate, lactate dehydrogenase, magnesium, oxygen, pH, phosphorus, potassium, ketones, sodium, total protein, uric acid, metabolic markers, and / or drugs.

[0043] Other analytes are contemplated as well, including but not limited to acetaminophen, dopamine, ephedrine, terbutaline, ascorbate, uric acid, oxygen, d-amino acid oxidase, plasma amine oxidase, xanthine oxidase, NADPH oxidase, alcohol oxidase, alcohol dehydrogenase, pyruvate dehydrogenase, diols, Ros, NO, bilirubin, cholesterol, triglycerides, gentisic acid, ibuprophen, L-Dopa, methyl dopa, salicylates, tetracycline, tolazamide, tolbutamide,acarboxyprothrombin; acylcamitine; adenine phosphoribosyl transferase; adenosine deaminase; albumin; alpha-fctoprotcin; amino acid profiles (arginine (Krebs cycle), histidinc / urocanic acid, homocysteine, phenylalanine / tyrosine, tryptophan); andrenostenedione; antipyrine; arabinitol enantiomers; arginase; benzoylecgonine (cocaine); biotinidase; biopterin; c-reactive protein; carnitine; camosinase; CD4; ceruloplasmin; chenodeoxycholic acid; chloroquine; cholesterol; cholinesterase; conjugated 1- hydroxy-cholic acid; cortisol; creatine kinase; creatine kinase MM isoenzyme; cyclosporin A; d-penicillamine; de-ethylchloroquine; dehydroepiandrosterone sulfate; DNA (acetylator polymorphism, alcohol dehydrogenase, alpha 1 -antitrypsin, cystic fibrosis, Duchenne / Becker muscular dystrophy, glucose-6-phosphate dehydrogenase, hemoglobin A, hemoglobin S, hemoglobin C, hemoglobin D, hemoglobin E, hemoglobin F, D-Punjab, betathalassemia, hepatitis B virus, HCMV, HIV-1, HTLV-1, Leber hereditary optic neuropathy, MCAD, RNA, PKU, Plasmodium vivax, sexual differentiation, 21 -deoxy corti sol); desbutylhalofantrine; dihydropteridine reductase; diptheria / tetanus antitoxin; erythrocyte arginase; erythrocyte protoporphyrin; esterase D; fatty acids / acylglycines; free 0-human chorionic gonadotropin; free erythrocyte porphyrin; free thyroxine (FT4); free tri-iodothyronine (FT3); fumarylacetoacetase; galactose / gal- 1 -phosphate; galactose- 1 -phosphate uridyltransferase; gentamicin; glucose-6-phosphate dehydrogenase; glutathione; glutathione perioxidase; glycocholic acid; glycosylated hemoglobin; halofantrine; hemoglobin variants; hexosaminidase A; human erythrocyte carbonic anhydrase I; 17-alpha-hydroxyprogesterone; hypoxanthine phosphoribosyl transferase; immunoreactive trypsin; lactate; lead; lipoproteins ((a), B / A-l, 0); lysozyme; mefloquine; netilmicin; phenobarbitone; phenyloin; phytanic / pristanic acid; progesterone; prolactin; prolidase; purine nucleoside phosphorylase; quinine; reverse triiodothyronine (rT3); selenium; serum pancreatic lipase; sissomicin; somatomedin C; specific antibodies (adenovirus, anti-nuclear antibody, anti-zeta antibody, arbovirus, Aujeszky's disease virus, dengue virus. Dracunculus medinensis, Echinococcus granulosus, Entamoeba histolytica, enterovirus, Giardia duodenalisa, Helicobacter pylori, hepatitis B virus, herpes virus, HIV-1, IgE (atopic disease), influenza virus, Leishmania donovani, leptospira, measles / mumps / rubella, Mycobacterium leprae, Mycoplasma pneumoniae, Myoglobin, Onchocerca volvulus, parainfluenza virus, Plasmodium falciparum, poliovirus, Pseudomonas aeruginosa, respiratory syncytial virus, rickettsia (scrub typhus), Schistosoma mansoni, Toxoplasma gondii, Trepenoma pallidium, Trypanosoma cruzi / rangeli, vesicular stomatis virus, Wuchereria bancrofti, yellowfever virus); specific antigens (hepatitis B vims, 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 zinc protoporphyrin. Salts, sugar, protein, fat, vitamins, and hormones naturally occurring in blood or interstitial fluids can also constitute analytes in certain embodiments.

[0044] The analyte can be naturally present in the biological fluid, for example, a metabolic product, a hormone, an antigen, an antibody, and the like. Alternatively, the analyte can be introduced into the body, for example, a contrast agent for imaging, a radioisotope, a chemical agent, a fluorocarbon-based synthetic blood, or a drug or pharmaceutical composition, including but not limited to insulin; ethanol; cannabis (marijuana, tetrahydrocannabinol, hashish); inhalants (nitrous oxide, amyl nitrite, butyl nitrite, chlorohydrocarbons, hydrocarbons); cocaine (crack cocaine); stimulants (amphetamines, methamphetamines, Ritalin, Cylert, Preludin, Didrex, PreState, Voranil, Sandrex, Plegine); depressants (barbituates, methaqualone, tranquilizers such as Valium, Librium, Miltown, Serax, Equanil, Tranxene); hallucinogens (phencyclidine, lysergic acid, mescaline, peyote, psilocybin); narcotics (heroin, codeine, morphine, opium, meperidine, Percocet, Percodan, Tussionex, Fentanyl, Darvon, Talwin, Lomotil); designer drugs (analogs of fentanyl, meperidine, amphetamines, methamphetamines, and phencyclidine, for example, Ecstasy); anabolic steroids; and nicotine. The metabolic products of drugs and pharmaceutical compositions are also contemplated analytes. Analytes such as neurochemicals and other chemicals generated within the body can also be analyzed, such as ascorbic acid, uric acid, dopamine, noradrenaline, 3 -methoxy tyramine (3MT), 3,4-dihydroxyphenylacetic acid (DOPAC), homovanillic acid (HVA), 5 -hydroxy tryptamine (5HT), histamine, Advanced Glycation End Products (AGEs) and 5-hydroxyindoleacetic acid (FHIAA).

[0045] Application 106 may be a mobile health application that is configured to receive and analyze time-series data, including analyte measurements, from the CAM system 104 and / or other devices, as described in greater detail relative to FIGS. IB and 2. In some embodiments, application 106 may transmit analyte measurements received from the CAM system 104 to a user database 110 (and / or the therapy management engine 112), and the user database 110 (and / or the therapy management engine 112) may store the analyte measurements in a user profile 118 of user 102 for processing and analysis, for example, by the therapy management engine 112. In someembodiments, application 106 may store the analyte measurements in a user profile 118 of user 102 locally for processing and analysis, for example, by the therapy management engine 112.

[0046] In certain embodiments, application 106 is configured to provide various interfaces for receiving from the user 102, data of the type discussed previously. In an example, the application 106 can provide a user interface that enables the user 102 to graphically respond to the therapy management engine 112 to confirm HTs (e.g., suggestions of CHO dosages) from the therapy management engine 112 for user 102, and / or that enables the application 106 to perform other functions such as indicating a CHO dosage.

[0047] In certain embodiments, therapy management engine 112 refers to a set of software instructions with one or more software modules, including a data analysis module (DAM) 111. In some embodiments, therapy management engine 112 executes entirely on one or more computing devices in a private or a public cloud. In some other embodiments, therapy management engine 112 executes partially on one or more local devices, such as display device 107 (e.g., via application 106) and / or CAM system 104, and partially on one or more computing devices in a private or a public cloud. In some other embodiments, therapy management engine 112 executes entirely on one or more local devices, such as display device 107 (e.g., via application 106) and / or CAM system 104. In certain embodiments, therapy management engine 112, via the application 106, may provide interfaces for suggesting and confirming recommended CHO dosages.

[0048] In certain embodiments, DAM 111 of therapy management engine 112 may be configured to receive and / or process a set of inputs 127 (described in more detail below) (also referred to herein as “input data”) to determine one or more outputs 130 (also referred to herein as “metrics data”). Inputs 127 may be stored in the user profile 118 in the user database 110. DAM 111 can fetch inputs 127 from the user database 110 and compute a plurality of outputs 130 which can then be stored as application data 126 in the user profile 118. Such outputs 130 may include health-related metrics.

[0049] In certain embodiments, application 106 is configured to take as input information relating to user 102 and store the information in a user profile 118 for user 102 in user database 110. For example, application 106 may obtain and record user 102’ s demographic info 119, disease progression info 121, and / or medication info 122 in user profile 118. In certain embodiments, demographic info 119 may include one or more of the user’s age, body mass index (BMI),ethnicity, gender, etc. In certain embodiments, disease progression info 121 may include information about the user 102’ s disease, such as, for diabetes, whether the user is Type I, Type II, pre-diabetes, or whether the user has gestational diabetes. In certain embodiments, disease progression info 121 also includes the length of time since diagnosis, the level of disease control, level of compliance with disease management therapy, predicted pancreatic function, other types of diagnosis (e.g., heart disease, obesity) or measures of health (e.g., heart rate, exercise, stress, sleep, etc.), and / or the like. In certain embodiments, medication info 122 may include information about the amount and type of medication taken by user 102, such as insulin or non-insulin diabetes medications and / or non-diabetes medication taken by user 102.

[0050] In certain embodiments, application 106 may obtain demographic info 119, disease progression info 121, and / or medication info 122 from the user 102 in the form of user input or from other sources. In certain embodiments, as some of this information changes, application 106 may receive updates from the user 102 or from other sources. In certain embodiments, user profile 118 associated with the user 102, as well as other user profiles associated with other users are stored in a user database 110, which is accessible to application 106, as well as to the therapy management engine 112, over one or more networks (not shown).

[0051] In certain embodiments, application 106 collects inputs 127 through user 102 input and / or a plurality of other sources, including CAM system 104, other applications running on display device 107, and / or one or more other sensors and devices. In certain embodiments, such sensors and devices include one or more of, but are not limited to, an insulin pump, other types of analyte sensors, sensors or devices provided by display device 107 (e.g., accelerometer, camera, global positioning system (GPS), heart rate monitor, etc.) or other user accessories (e.g., a smartwatch), or any other sensors or devices that provide relevant information about the user 102. In certain embodiments, user profile 118 also stores application configuration information indicating the current configuration of application 106, including its features and settings.

[0052] User database 110, in some embodiments, refers to a storage server that may operate in a public or private cloud. User database 110 may be implemented as any type of data store, such as relational databases, non-relational databases, key-value data stores, file systems including hierarchical file systems, and the like. In some exemplary implementations, user database 110 is distributed. For example, user database 110 may comprise a plurality of persistent storage devices,which are distributed. Furthermore, user database 110 may be replicated so that the storage devices arc geographically dispersed.

[0053] User database 110 may include other user profiles 118 associated with a plurality of other users served by therapy management system 100. More particularly, similar to the operations performed with respect to the user 102, the operations performed with respect to these other users may utilize an analyte monitoring system, such as CAM system 104, and also interact with the same application 106, copies of which execute on the respective display devices of the other users 102. For such users, user profiles 118 are similarly created and stored in user database 110.

[0054] FIG. IB is a diagram 150 conceptually illustrating an example CAM system 104 including example continuous analyte sensor(s) with sensor electronics, in accordance with certain aspects of the present disclosure. For example, CAM system 104 may be configured to continuously monitor one or more analytes of a patient, in accordance with certain aspects of the present disclosure.

[0055] CAM system 104 in the illustrated embodiment includes sensor electronics module 138 and one or more continuous analyte sensor(s) 140 (individually referred to herein as continuous analyte sensor 140 and collectively referred to herein as continuous analyte sensors 140) associated with sensor electronics module 138. Sensor electronics module 138 may be in wireless communication (e.g., directly or indirectly) with one or more of display devices 107a, 107b, 107c, and 107d. In certain embodiments, sensor electronics module 138 may also be in wireless communication (e.g., directly or indirectly) with one or more medical devices, such as medical devices 108 (individually referred to herein as medical device 108 and collectively referred to herein as medical devices 108), and / or one or more other non-analyte sensors 142 (individually referred to herein as non-analyte sensor 142 and collectively referred to herein as non-analyte sensor 142).

[0056] In certain embodiments, a continuous analyte sensor 140 may comprise one or more sensors for detecting and / or measuring analyte(s). The continuous analyte sensor 140 may be a multi-analyte sensor configured to continuously measure two or more analytes or a single analyte sensor configured to continuously measure a single analyte as a non-invasive device, a subcutaneous device, a transcutaneous device, a transdermal device, and / or an intravascular device. In certain embodiments, the continuous analyte sensor 140 may be configured tocontinuously measure analyte levels of a patient using one or more techniques, such as enzymatic techniques, chemical techniques, physical techniques, electrochemical techniques, spectrophotometric techniques, polarimetric techniques, calorimetric techniques, iontophoretic techniques, radiometric techniques, immunochemical techniques, and the like. The term “continuous,” as used herein, can mean fully continuous, semi-continuous, periodic, etc. In certain aspects, the continuous analyte sensor 140 provides a data stream indicative of the concentration of one or more analytes in the patient. The data stream may include raw data signals, which are then converted into a calibrated and / or filtered data stream used to provide estimated analyte value(s) to the patient.

[0057] In certain embodiments, the continuous analyte sensor 140 may be a multi-analyte sensor, configured to continuously measure multiple analytes in a patient’s body. For example, in certain embodiments, the continuous multi-analyte sensor 140 may be a single sensor configured to measure lactate, glucose, ketones (e.g., 3-beta-hydroxybutyrate, acetoacetate, acetone, etc.), glycerol, and / or free fatty acids in the patient’s body.

[0058] In certain embodiments, one or more multi-analyte sensors may be used in combination with one or more single analyte sensors. As an illustrative example, a multi-analyte sensor may be configured to continuously measure lactate and glucose and may, in some cases, be used in combination with an analyte sensor configured to measure only ketones or only potassium. Information from each of the multi-analyte sensor(s) and single analyte sensor(s) may be combined to provide therapy management support using methods described herein. In further embodiments, other non-contact and or periodic or semi-continuous, but temporally limited, measurements for physiological information may be integrated into the system such as by including weight scale information or non-contact heart rate monitoring from a sensor pad under the patient while in a chair or bed, through an infra-red camera detecting temperature and / or blood flow patterns of the patient, and / or through a visual camera with machine vision for height, weight, or other parameter estimation without physical contact.

[0059] In certain embodiments, the continuous analyte sensor(s) 140 may comprise a percutaneous wire that has a proximal portion coupled to the sensor electronics module 138 and a distal portion with several electrodes, such as a measurement electrode and a reference electrode. The measurement (or working) electrode may be coated, covered, treated, embedded, etc., withone or more chemical molecules that react with a particular analyte, and the reference electrode may provide a reference electrical voltage. The measurement electrode may generate the analog electrical signal, which is conveyed along a conductor that extends from the measurement electrode to the proximal portion of the percutaneous wire that is coupled to the sensor electronics module 138. After the CAM system 104 has been applied to epidermis of the patient, continuous analyte sensor(s) 140 penetrates the epidermis, and the distal portion extends into the dermis and / or subcutaneous tissue under epidermis. Other configurations of continuous analyte sensor(s) 140 may also be used, such as a multi-analyte sensor that includes multiple measurement electrodes, each generating an analog electrical signal that represents the concentration levels of a particular analyte.

[0060] Generally, a single-analyte sensor generates an analog electrical signal that is proportional to the concentration level of a particular analyte. Similarly, each multi-analyte sensor generates multiple analog electrical signals, and each analog electrical signal is proportional to the concentration level of a particular analyte. As an illustrative example, continuous analyte sensor 140 may include a single- analyte sensor configured to measure lactate concentration levels, and another single-analyte sensor configured to measure glucose concentration levels of the patient. As another illustrative example, continuous analyte sensor(s) 140 may include a single-analyte sensor configured to measure glucose concentration levels, and one or more multi-analyte sensors configured to measure lactate concentration levels, ketone concentration levels, creatinine concentration levels, etc. As yet another illustrative example, continuous analyte sensor(s) 140 may include a multi-analyte sensor configured to measure lactate concentration levels, glucose concentration levels, ketone concentration levels, creatinine concentration levels, etc. Accordingly, continuous analyte sensor(s) 140 is configured to generate at least one analog electrical signal that is proportional to the concentration level of a particular analyte, and sensor electronics module 138 is configured to convert the analog electrical signal into an analyte sensor count values, calibrate the analyte sensor count values based on the sensitivity profile of the continuous analyte sensor(s) 140 to generate measured analyte concentration levels, and transmit the measured analyte concentration level data, including the measured analyte concentration levels, to a display device, such as display devices 107b, 107c, and / or 107d, via a wireless connection. For example, sensor electronics module 138 may be configured to sample the analog electrical signal at a particular sampling period (or rate), such as every 1 second (1 Hz), 5 seconds,10 seconds, 30 seconds, 1 minute, 3 minutes, 5 minutes, etc., and to transmit the measured analyte concentration data to the display device at a particular transmission period (or rate), which may be the same as (or longer than) the sampling period, such as every 1 minute (0.016 Hz), 5 minutes, 10 minutes, 30 minutes, at the conclusion of the wear period, etc. Depending on the sampling and transmission periods, the measured analyte concentration data transmitted to the display device include at least one measured analyte concentration level having an associated time tag, sequence number, etc.

[0061] In certain embodiments, continuous analyte sensor(s) 140 may incorporate a thermocouple within, or alongside, the percutaneous wire to provide an analog temperature signal to the sensor electronics module 138, which may be used to correct the analog electrical signal or the measured analyte data for temperature. In other embodiments, the thermocouple may be incorporated into the sensor electronics module 138 above the adhesive pad, or, alternatively, the thermocouple may contact the epidermis of the patient through openings in the adhesive pad.

[0062] In certain embodiments, the sensor electronics module 138 includes, inter alia, processor 133, storage element or memory 134, wireless transmitter / receiver (transceiver) 136, one or more antennas coupled to wireless transceiver 136, analog electrical signal processing circuitry, analog to-digital (A / D) signal processing circuitry, digital signal processing circuitry, a power source for continuous analyte sensor(s) 140 (such as a potentiostat), etc.

[0063] Processor 133 may be a general-purpose or application- specific microprocessor, an application-specific integrated circuit (ASIC), a field programmable gate array (FPGA), etc., that executes instructions to perform control, computation, input / output, etc. functions for the sensor electronics module 138. Processor 133 may include a single integrated circuit, such as a micro processing device, or multiple integrated circuit devices and / or circuit boards working in cooperation to accomplish the appropriate functionality. In certain embodiments, processor 133, memory 134, wireless transceiver 136, the A / D signal processing circuitry, and the digital signal processing circuitry may be combined into a system-on-chip (SoC).

[0064] Generally, processor 133 may be configured to sample the analog electrical signal using the A / D signal processing circuitry at regular intervals (such as the sampling instant or period) to generate analyte sensor count values based on the analog electrical signals produced by the continuous analyte sensor(s) 140, calibrate the analyte sensor count values based on the sensitivityprofile of the continuous analyte sensor(s) 140 to generate measured analyte concentration levels, and generate measured analyte data from the measured analyte concentration levels, generate sensor data packages that include, inter alia, the measured analyte concentration level data. Processor 133 may store the measured analyte concentration level data in memory 134, and generate the sensor data packages at regular intervals (such as the transmission period) for transmission by wireless transceiver 136 to a display device, such as display devices 107b, 107c, 107d, and / or 107a. Processor 133 may also add additional data to the sensor data packages, such as supplemental sensor information that includes a sensor identifier, a sensor status, temperatures that correspond to the measured analyte data, etc. The sensor data packages are then wirelessly transmitted over a wireless connection to the display device. In certain embodiments, the wireless connection is a Bluetooth or Bluetooth Low Energy (BLE) connection. In such embodiments, the sensor data packages are transmitted in the form of Bluetooth or BLE data packets to the display device.

[0065] In certain aspects, the transceiver 136 maintains, in the memory 134, a connection list that indicates each device currently connected thereto. In certain aspects, the connection list can also be maintained in other storage locations (e.g., in a cloud computing environment, on each individual display device, etc.). A device may be identified as “currently connected” to the transceiver 136 if the device has successfully engaged in the wireless or wired communication of data (e.g., by requesting and / or receiving at least a predetermined amount of analyte data) with the transceiver 136 via one or more predetermined communication protocols within a predetermined period of time from the current time, has performed and successfully completed one or more wired or wireless transmission security protocols with the transceiver 136 within a predetermined period of time from the current time, etc. In certain aspects, the transceiver 136 can advertise on a regular interval (e.g., every five minutes), such that devices are removed from the connection list after a predetermined number of connections are missed (e.g., one, two, three, etc.). The connection list may include, for each device indicated therein, an identifier of the device (e.g., device identifier, user assigned identifier, transceiver 136 assigned identifier, etc.), a timestamp of last connection, signal strength, an indication of any recent transmission errors, and / or other information.

[0066] In various embodiments, memory 134 may include volatile and nonvolatile medium. For example, memory 134 may include combinations of random access memory (RAM), dynamic RAM (DRAM), static RAM (SRAM), read only memory (ROM), flash memory, cache memory,and / or any other type of non-transitory computer-readable medium. Memory 134 may store one or more CAM system applications, modules, instruction sets, etc. for execution by processor 133, such as instructions to generate measured analyte data from the analyte sensor count values, etc.

[0067] Memory 134 may also store certain sensor operating parameters 135, such as a calibration slope (or calibration sensitivity), a calibration baseline, etc. In particular, the calibration sensitivity, calibration baseline, and other information related to the sensitivity profile for the sensor electronics module 138 may be programmed into the sensor electronics module 138 during the manufacturing process, and then used to convert the analyte sensor electrical signals into measured analyte concentration levels. For example, as discussed above, the calibration slope may be used to predict an initial in vivo sensitivity (Mo) and a final in vivo sensitivity (Mf), which are stored in memory 134 and used to convert the analyte sensor electrical signals into measured analyte concentration levels. In certain embodiments, calibration sensitivity (Mcc) 146 and / or calibration baseline 147 may be stored in memory 134.

[0068] In certain embodiments, sensor electronics module 138 includes electronic circuitry associated with measuring and processing the continuous analyte sensor data, including prospective algorithms associated with processing and calibration of the sensor data. Sensor electronics module 138 can be physically connected to continuous analyte sensor(s) 140 and can be integral with (non-releasably attached to) or releasably attachable to continuous analyte sensor(s) 140. Sensor electronics module 138 may include hardware, firmware, and / or software that enable measurement of levels of analyte(s) via continuous analyte sensor(s) 140. For example, sensor electronics module 138 can include a potentiostat, a power source for providing power to the sensor, other components useful for signal processing and data storage, and a telemetry module for transmitting data from the sensor electronics module to, e.g., one or more display devices. Electronics can be affixed to a printed circuit board (PCB), or the like, and can take a variety of forms. For example, the electronics can take the form of an integrated circuit (IC), such as an Application-Specific Integrated Circuit (ASIC), a microcontroller, and / or a processor.

[0069] Display devices 107b, 107c, 107d, and / or 107a are configured for displaying displayable sensor data, including analyte data, which may be transmitted by sensor electronics module 138. Each of display devices 107b, 107c, 107d, or 107a may include a display such as a touchscreen display 109b, 109c, 109d, and / or 109a for displaying sensor data to a patient and / orfor receiving inputs from the patient. For example, a graphical user interface (GUI) may be presented to the patient for such purposes. In certain embodiments, the display devices may include other types of user interfaces such as a voice user interface instead of, or in addition to, a touchscreen display for communicating sensor data to the patient of the display device and / or for receiving patient inputs. Display devices 107a, 107b, 107c, and 107d may be examples of display device 107 illustrated in FIG. 1 used to display sensor data to a patient of the system of FIG. 1 and / or to receive input from the patient.

[0070] In certain embodiments, one, some, or all of the display devices are configured to display or otherwise communicate (e.g., verbalize) the sensor data as it is communicated from the sensor electronics module (e.g., in a customized data package that is transmitted to display devices based on their respective preferences), without any additional prospective processing required for calibration and real-time display of the sensor data.

[0071] The plurality of display devices may include a custom display device specially designed for displaying certain types of display able sensor data associated with analyte data received from sensor electronics module. In certain embodiments, the plurality of display devices may be configured for providing alerts / alarms based on the displayable sensor data. Display device 107b is an example of such a custom device. In certain embodiments, one of the plurality of display devices is a smartphone, such as display device 107c which represents a mobile phone, using a commercially available operating system (OS), and configured to display a graphical representation of the continuous sensor data (e.g., including current and historic data). Other display devices can include other hand-held devices, such as display device 107d which represents a tablet, display device 107a which represents a smart watch or fitness tracker, medical device 108 (e.g., an insulin delivery device or a blood glucose meter), and / or a desktop or laptop computer (not shown).

[0072] Because different display devices provide different user interfaces, content of the data packages (e.g., amount, format, and / or type of data to be displayed, alarms, and the like) can be customized (e.g., programmed differently by the manufacture and / or by an end user, such as the patient) for each particular display device. Accordingly, in certain embodiments, a plurality of different display devices can be in direct wireless communication with a sensor electronics module (e.g., such as an on-skin sensor electronics module 138 that is physically connected to continuousanalyte sensor(s) 140) during a sensor session to enable a plurality of different types and / or levels of display and / or functionality associated with the displayable sensor data.

[0073] As mentioned, sensor electronics module 138 may be in communication with a medical device 108. Medical device 108 may be a passive device in some example embodiments of the disclosure. For example, medical device 108 may be an insulin pump for administering insulin to a patient. For a variety of reasons, it may be desirable for such an insulin pump to receive and track lactate, glucose, ketones, glycerol and free fatty acid values transmitted from CAM systems 104, where continuous analyte sensor 140 is configured to measure lactate, glucose, ketones, glycerol, and / or free fatty acids.

[0074] Further, as mentioned, sensor electronics module 138 may also be in communication with other non-analyte sensors 142. Non-analyte sensors 142 may include, but are not limited to, an altimeter sensor, an accelerometer sensor, a global positioning system (GPS) sensor, a temperature sensor, a respiration rate sensor, etc. Non-analyte sensors 142 may also include monitors such as heart rate monitors, blood pressure monitors, pulse oximeters, caloric intake monitors, indirect calorimetry devices, continuous positive airway pressure machines, and medicament delivery devices. One or more of these non-analyte sensors 142 may provide data to therapy management engine 112 described further below. In some aspects, a patient may manually provide some of the data for processing by the therapy management engine 112 of FIG. 1.

[0075] In certain embodiments, non-analyte sensors 142 may further include sensors for measuring movement or activity, skin temperature, core temperature, sweat rate, and / or sweat composition.

[0076] In certain embodiments, the non-analyte sensors 142 may be combined in any other configuration, such as, for example, combined with one or more continuous analyte sensors 140. As an illustrative example, a non-analyte sensor, e.g., a temperature sensor, may be combined with a continuous glucose sensor 140 to form a glucose / temperature sensor used to transmit sensor data to the sensor electronics module 138 using common communication circuitry. As another illustrative example, a non-analyte sensor, e.g., a temperature sensor, may be combined with a multi-analyte sensor 140 configured to measure lactate and glucose to form a lactate / glucose / temperature sensor used to transmit sensor data to the sensor electronics module 138 using common communication circuitry.

[0077] In certain embodiments, a wireless access point (WAP) may be used to couple one or more of CAM system 104, the plurality of display devices, medical dcvicc(s) 108, and / or nonanalyte sensor(s) 142 to one another. For example, such WAP may provide Wi-Fi and / or cellular connectivity among these devices. Near Field Communication (NFC) and or Bluetooth may also be used among devices depicted in diagram 150 of FIG. IB.

[0078] FIG. 2 illustrates example inputs and example metrics that are generated based on the inputs in accordance with certain embodiments of the disclosure. In particular, FIG. 2 illustrates example inputs 127 on the left, application 106 and therapy management engine 112, with DAM 111, in the middle, and example outputs 130 on the right. In certain embodiments, application 106 may obtain inputs 127, in the form of time-series data, through one or more channels (e.g., continuous analyte sensor(s) 140, non-analyte sensor(s) 142, various applications executing on display device 107, etc.). Inputs 127 may be further processed by DAM 111 to output a plurality of metrics, such as outputs 130. Further, inputs (e.g., inputs 127) and metrics (e.g., outputs 130) may be used by the DAM 111 and / or any computing device in the system 100 to perform various processes. Any of inputs 127 may be used for computing any of outputs 130. In certain embodiments, each one of outputs 130 may correspond to one or more values, e.g., discrete numerical values, ranges, or qualitative values (high / medium / low or stable / unstable). In some embodiments, some or all of outputs 130 may include time-series data and / or be provided in the form of time- series data.

[0079] In certain embodiments, inputs 127 include food consumption information. Food consumption information may include information about one or more of meals, snacks, and / or beverages, such as one or more of the size, content (carbohydrate, fat, protein, etc.), sequence of consumption, and time of consumption. In certain embodiments, food consumption may be provided by the user through manual entry, by providing a photograph through an application that is configured to recognize food types and quantities, and / or by scanning a bar code or menu. In various examples, meal size may be manually entered as one or more of calories, quantity (e.g., 'three cookies'), menu items (e.g., 'Royale with Cheese'), and / or food exchanges (1 fruit, 1 dairy). In some examples, meals may also be entered with the user's typical items or combinations for this time or setting (e.g., workday breakfast at home, weekend brunch at restaurant). In some examples, meal information may be received via a convenient user interface provided by application 106.

[0080] In certain embodiments, inputs 127 include activity information. Activity information may be provided, for example, the one or more non-analytc sensors 142 of FIG. IB. In certain embodiments, activity information may additionally be provided through manual input by user 102. Activity information may include, for example, a time series for each of heart rate, activity minutes, step count, floors climbed, location information (e.g., GPS data), calories burned, sleep duration and / or quality, activity level (e.g., light, medium, or heavy), and / or similar information. In addition, or alternatively, the activity information can include one or more time series for recorded activities of one or more defined activity types (e.g., walk, run, sprint, swim, weightlift etc.), where each activity is associated with a duration and / or time period.

[0081] In certain embodiments, inputs 127 include patient statistics, such as one or more of age, height, weight, body mass index, body composition (e.g., % body fat), stature, build, or other information. Patient statistics may be provided through a user interface, by interfacing with an electronic source such as an electronic medical record, and / or from measurement devices. The measurement devices may include one or more of a wireless, e.g., Bluetooth-enabled, weight scale and / or camera, which may, for example, communicate with the display device 107 to provide patient data.

[0082] In certain embodiments, inputs 127 include information relating to the user’s medication intake. For example, the user’s medication intake may include the user’s insulin delivery. Such information may be received, via a wireless connection on a smart pen, via user input, and / or from an insulin pump (e.g., medical device 108). Insulin delivery information may include one or more of insulin volume, time of delivery, etc. Other configurations, such as insulin action time or duration of insulin action, may also be received as inputs.

[0083] In certain embodiments, inputs 127 include physiological information received from non-analyte sensor(s) 142 , which may detect one or more of heart rate, respiration, oxygen saturation, body temperature, etc. (e.g., to detect illness, stress levels, etc.). In certain embodiments, inputs 127 include time, such as time of day, or time from a real-time clock.

[0084] In certain embodiments, inputs 127 include analyte data, which may be provided as input from CAM system 104, for example, in any of the ways described with respect to FIG. 1A. An example of analyte data is glucose data, which may be provided and / or stored as a time series corresponding to time-stamped glucose measurements over time. Other types of analyte data, suchas ketone data, potassium data, lactate data, etc., may similarly be provided and / or stored as a time scries.

[0085] As described above, in certain embodiments, DAM 111 generates, determines, and / or computes outputs 130 based on inputs 127 associated with user 102. An example list of outputs 130 is illustrated in FIG. 2. In certain embodiments, outputs 130 generated, determined, or computed by DAM 111 include metabolic rate. Metabolic rate is a metric that may indicate or include a basal metabolic rate (e.g., energy consumed at rest) and / or an active metabolism, e.g., energy consumed by activity, such as exercise or exertion. In some examples, basal metabolic rate and active metabolism may be tracked as separate metric. In certain embodiments, the metabolic rate may be calculated by DAM 111 based on one or more of inputs 127, such as one or more of activity information, sensor input, time, user input, etc.

[0086] In certain embodiments, outputs 130 generated, determined, or computed by DAM 111 include an activity level metric. The activity level metric may indicate a level of activity of the user. In certain embodiments, the activity level metric may be determined, for example based on input from an activity sensor or other physiologic sensors. In certain embodiments, the activity level metric may be calculated by DAM 111 based on one or more of inputs 127, such as one or more of activity information, physiological information, analyte data, time, user input, etc. Activity level may indicate whether the user is exercising, at rest, sleeping, etc.

[0087] In certain embodiments, outputs 130 generated, determined, or computed by DAM 111 include an insulin resistance metric (also referred to herein as an “insulin resistance”). The insulin resistance metric may be determined using historical data, real-time data, or a combination thereof, and may, for example, be based upon one or more inputs 127, such as one or more of food consumption information, blood glucose information, insulin delivery information, the resulting glucose levels, etc. In certain embodiments, the insulin on board metric may be determined using insulin delivery information, and / or known or learned (e.g., from patient data) insulin time action profiles, which may account for both basal metabolic rate (e.g., update of insulin to maintain operation of the body) and insulin usage driven by activity or food consumption.

[0088] In certain embodiments, outputs 130 generated, determined, or computed by DAM 111 include a meal state metric. The meal state metric may indicate the state the user is in with respect to food consumption. For example, the meal state may indicate whether the user is in one of afasting state, pre-meal state, eating state, post-meal response state, or stable state. In certain embodiments, the meal state may also indicate nourishment on board, e.g., meals, snacks, or beverages consumed, and may be determined, for example from food consumption information, time of meal information, and / or digestive rate information, which may be correlated to food type, quantity, and / or sequence (e.g., which food / beverage was eaten first.).

[0089] In certain embodiments, outputs 130 generated, determined, or computed by DAM 111 include health and sickness metrics. Health and sickness metrics may be determined, for example, based on one or more of user input (e.g., pregnancy information or known sickness information), from non-analyte sensor(s) 142, such as physiologic sensors (e.g., temperature), activity sensors, or a combination thereof. In certain embodiments, based on the values of the health and sickness metrics, for example, the user’s state may be defined as being one or more of healthy, ill, rested, or exhausted. In certain embodiments, health and sickness metric may indicate the user’s heart rate, stress level, etc.

[0090] In certain embodiments, outputs 130 generated, determined, or computed by DAM 111 include analyte level metrics. Analyte level metrics may be determined from analyte data (e.g., glucose measurements obtained from CAM system 104). In some examples, an analyte level metric may also be determined, for example, based upon historical information about analyte levels in particular situations, e.g., given a combination of food consumption, insulin, and / or activity. An analyte level metric may include a rate of change of the analyte, time in range, time spent below a threshold level, time spent above a threshold level, or the like. In certain embodiments, an analyte trend may be determined based on the analyte level over a certain period of time. As described above, example analytes may include glucose, ketones, lactate, potassium and others described herein.

[0091] In certain embodiments, outputs 130 generated, determined, or computed by DAM 111 include a disease stage. For example disease stages for Type II diabetics may include a pre-diabetic stage, an oral treatment stage, and a basal insulin treatment stage. In certain embodiments, degree of glycemic control (not shown) may also be determined as an outcome metric, and may be based, for example, on one or more of glucose levels, variation in glucose level, or insulin dosing patterns.

[0092] In certain embodiments, outputs 130 generated, determined, or computed by DAM 111 include clinical metrics. Clinical metrics generally indicate a clinical state a user is in with respectto one or more conditions of the user, such as diabetes. For example, in the case of diabetes, clinical metrics may be determined based on glycemic measurements, including one or more of A1C, trends in A1C, time in range, time spent below a threshold level, time spent above a threshold level, and / or other metrics derived from glucose values. In certain embodiments, clinical metrics may also include one or more of estimated A1C, glycemic variability, hypoglycemia, and / or health indicator (time magnitude out of target zone).

[0093] FIG. 3 illustrates an example of a medical support system 300 for making a patient’s health data available to one or more other users (referred to herein as supporters), in accordance with certain embodiments. Medical support system 300 includes the CAM system 104 of FIGS. 1 A-B, the patient display devices 107a and 107c of FIG. 1 B, a supporter device 311 , and a server system 330. The patient display devices 107a and 107c, the supporter device 311, and the server system 330 are interconnected via a network 316. The network 316 can be a local area network (LAN), wide area network (WAN), a cellular network, the Internet, or any other group of connected computing devices.

[0094] The user 102 can use one or both of the patient display devices 107a and 107c to collect sensor data and monitor their health. More particularly, in the illustration of FIG. 3, the patient display devices 107a and 107c are examples of multiple receiver devices, namely, a smartphone and a smartwatch, that each directly communicate with, and obtain sensor data from, the CAM system 104 worn by the user 102, where such sensor data can be transmitted by the CAM system 104 in the fashion described relative to FIGS. 1A-B. According to the example of FIG. 3, the patient display devices 107a and 107c may each be included in the connection list discussed relative to the transceiver 136 of FIG. IB. Although two receiver devices are shown in FIG. 3, it should be appreciated that, in various implementations, any number of devices may directly receive such sensor data including, for example, any one or more of display devices 107a, 107b, 107c, and 107d of FIG. IB. Display devices 107a and 107c may include touchscreen displays 109a and 109c, respectively, as discussed relative to FIG. IB. As shown, display devices 107a and 107c execute application 106-1 and application 106-2, respectively, which applications each correspond to instances of the application 106 discussed relative to FIGS. 1A-B and 2.

[0095] In certain aspects, a supporter 308 uses the supporter device 311 to help the user 102 manage their health or medical condition, such as diabetes. The supporter device 311 can executean application 306, which can access at least selected health data of the user 102 (e.g., analyte data and / or alerts related thereto) from the server system 330 and can display the health data via a display 309 of the supporter device 311. In some aspects, the application 306 can operate as described relative to the application 106 of FIG. 1. Although the supporter 308 and the supporter device 311 are shown singly in FIG. 3, it should be appreciated that, in various implementations, the supporter 308 and / or the supporter device 311 may be representative of multiple supporters and / or supporter devices, respectively.

[0096] In the example of FIG. 3, the server system 330 is an example of a remote target that facilitates, for example, publishing or providing health data of the user 102 to the supporter 308. In some aspects, the server system 330 is operable in a cloud computing environment (e.g., a private or public cloud) and can provide application services and / or features for the CAM system 104 and / or applications 106-1, 106-2, and / or 306. In certain aspects, the server system 330 implements at least a portion of the therapy management engine 112 described with respect to FIG. 1A. The server system 330 can receive and store data generated by the CAM system 104 (via transmissions initiated by the applications 106-1 and / or 106-2), monitor operating parameters of the CAM system 104 (via the applications 106-1 and / or 106-2), publish or provide health data to the supporter device 311, push updates to the applications 106-1, 106-2 and / or 306, etc.

[0097] The server system 330 includes a processor 331 configured to execute one or more software applications stored in a memory 332. For example, the processor 331 can execute a data sharing application generally configured to enable the supporter 308 to receive health data of the user 102 and monitor the health of the user 102. For example, in some aspects, once the user 102 opts into receiving services provided by the server system 330, the server system 330 is able to receive the health data transmitted by the patient display devices 107a and / or 107 and to store the health data in a storage system (e.g., data store 310). Once the user 102 opts into allowing the supporter 308 to receive information related to the health of the user 102, the server system 330 can allow the supporter 308 to also access the health data within the storage system.

[0098] In general, to enable publication of health data of the user 102 to the supporter 308, the CAM system 104 may be configured to generate time-series sensor data, such as analyte measurements, for the user 102, e.g., on a continuous basis. The CAM system 104 transmits the sensor data to each patient device connected thereto via, for example, the transceiver 136 discussedrelative to FTG. IB. For example, the CAM system 104 can transmit the sensor data to each device included in the connection list discussed relative to the transceiver 136 of FIG. IB. In the example of FIG. 3, the sensor data may be transmitted to each of the patient display devices 107a and 107c for use by the application 106-1 and the application 106-2, respectively.

[0099] In some cases, as a result of the foregoing, the patient display devices 107a and 107c may each directly receive, from the CAM system 104, the same or overlapping sensor data. In certain aspects, to reduce or eliminate possible redundancy of data transmitted to the server system 330, the applications 106-1 and 106-2 can each be configured to execute the same, or consistent, conditional transmission logic. For example, the applications 106- 1 and 106-2 can cause the patient display devices 107a and 107c, respectively, to each conditionally transmit the sensor data to the server system 330 according to predetermined criteria, such that transmission is enabled (and, in some cases, caused to occur) if the criteria is satisfied and prevented otherwise. The predetermined criteria can relate, for example, to the individual device (e.g., whether the device is a smartphone or smartwatch), which other devices are connected to the CAM system 104 (e.g., whether the device is the only device currently connected to the CAM system 104), the analyte data itself (e.g., whether the data indicates an urgent event such as hypoglycemia or hyperglycemia), and / or other data. Examples of conditional transmission of analyte data will be described in greater detail relative to FIGS. 4-7.

[0100] Therefore, in certain aspects, one or both of the patient display device 107a and the patient display device 107c may transmit the sensor data to the server system 330. The server system 330 can forward the sensor data and / or alerts or other health data based on the sensor data to the supporter device 311, thereby allowing the supporter 308 to view the patient's glucose data and / or alerts substantially in real-time. In some aspects, any resulting redundant transmissions to the server system 330 can be de-duplicated upon receipt of the sensor data, upon transmission of alerts, for example, to the supporter device 311, and / or the like. The redundant transmissions can be de-duplicated, for example, based on timestamps, a combination of timestamps and data content, and / or the like.

[0101] In addition, in certain aspects, the patient display device 107a and the patient display device 107c can communicate with each other. For example, in certain aspects, the patient display device 107a and the patient display device 107c can perform inter-device communication, forexample, to determine or verify a current connection status with the CAM system 104. In some aspects, the intcr-dcvicc communication can occur over the network 316. In addition, or alternatively, the inter-device communication can occur directly between the two devices without the network 316. Examples of performing inter-device communication will be discussed relative to FIGS. 7 and 8.

[0102] FIG. 4 illustrates an example of a process 400 for optimizing transmission of analyte data in multi-receiver environments, in accordance with certain embodiments. In some embodiments, the process 400 can be executed, for example, by the therapy management engine 112 of FIGS. 1A-B and 2. In addition, or alternatively, the process 400 can be executed, for example, by the application 106 of FIGS. 1 A-B and 2. In addition, or alternatively, the process 400 can be executed generally by any of the display devices 107 of FIGS. 1A-B and 2.

[0103] Although any number of systems, in whole or in part, can implement the process 400, to simplify discussion, the process 400 will be described as being performed by the application 106 of FIGS. 1 A-B and 2, with particular reference to the medical support system 300 of FIG. 3. With reference to the medical support system 300 of FIG. 3, in some aspects, the process 400 can be executed by each of the applications 106-1 and 106-2 before each potential transmission by the patient display devices 107a and 107c, respectively, to the server system 330. In addition, or alternatively, the process 400 can be executed by the application 106-1 and the application 106-2 at any suitable interval (e.g. every 5 minutes, every 10 minutes, every 15 minutes, every other transmission, etc.). Other variations will be apparent to one skilled in the art after a detailed review of the present disclosure.

[0104] At block 402, at the patient display device 107, the application 106 receives analyte data (e.g., analyte measurements) from the CAM system 104. The analyte data may be received, for example, via the transceiver 136 of the CAM system 104, as discussed relative to FIGS. 1A-B and 3.

[0105] At block 404, the application 106 determines a current status of a connection between the patient display device 107 and the CAM system 104. It should be appreciated that the aforementioned connection may more specifically refer to a connection between the patient display device 107 and the transceiver 136 of the CAM system 104. For clarity, however, the current status will be described in relation to the CAM system 104.

[0106] In general, the current status can characterize the connection between the patient display device 107 and the CAM system 104 and / or connections between other patient devices and the CAM system 104. In an example, the current status may indicate that the patient display device 107 is the only device currently connected to the CAM system 104. In another example, the current status may indicate that the patient display device 107 is one of a plurality of devices currently connected to the CAM system 104. In some aspects, when more than one device is currently connected to the CAM system 104, the current status may indicate a priority of the patient display device 107 relative to other connected devices according to any suitable criteria (e.g., criteria based on user ranking, device type, device capabilities, etc.). Examples of determining the current status will be described in greater detail relative to FIG. 5.

[0107] At block 406, the application 106 causes the patient display device 107 to conditionally transmit the analyte data over a network to a remote target based on the current status of the connection. The remote target may be, for example, the server system 330 of FIG. 3. For example, the application 106 can enable the patient display device 107 to transmit the analyte data to the server system 330 if it is the only device currently connected to the CAM system 104, or if it is the highest priority such device according to any suitable criteria. Conversely, according to this example, the application 106 can prevent such transmission if another, higher priority device is currently connected to the CAM system 104, thus deferring to the higher priority device. Advantageously, in certain embodiments, the prevention of transmission can eliminate potential redundant transmission and improve resource utilization, particularly when multiple analyte monitoring applications on multiple patient devices execute the same or consistent conditional transmission logic. After block 406, the process 400 ends.

[0108] FIG. 5 illustrates an example of a process 500 for optimizing transmission of analyte data in multi-receiver environments based on a current connection status, in accordance with certain embodiments. In some embodiments, the process 500 can be executed, for example, by the therapy management engine 112 of FIGS. 1A-B and 2. In addition, or alternatively, the process 500 can be executed, for example, by the application 106 of FIGS. 1A-B and 2. In addition, or alternatively, the process 500 can be executed generally by any of the display devices 107 of FIGS. 1A-B and 2.

[0109] Although any number of systems, in whole or in part, can implement the process 500, to simplify discussion, the process 500 will be described as being performed by the application 106 of FIGS. 1 A-B and 2, with particular reference to the medical support system 300 of FIG. 3. With reference to the medical support system 300 of FIG. 3, in some aspects, the process 500 can be executed by each of the applications 106-1 and 106-2 before each potential transmission by the patient display devices 107a and 107c, respectively, to the server system 330. In addition, or alternatively, the process 500 can be executed by the application 106-1 and the application 106-2 at any suitable interval (e.g. every 5 minutes, every 10 minutes, every 15 minutes, every other transmission, etc.). Other variations will be apparent to one skilled in the art after a detailed review of the present disclosure.

[0110] At block 502, at the patient display device 107, the application 106 receives analyte data (e.g., analyte measurements) from the CAM system 104. The analyte data may be received, for example, via the transceiver 136 of the CAM system 104, as discussed relative to FIGS. 1A-B and 3.

[0111] At block 504, the application 106 retrieves current connection data for the CAM system 104. For example, the block 504 can include retrieving a connection list for the CAM system 104, such as the connection list discussed relative to the transceiver 136 of FIG. IB. According to this example, the connection list can be retrieved from the transceiver 136 or from another storage location where the connection list may be maintained, such as the server system 330 and / or a storage location on the patient display device 107 or another device. As discussed previously, the connection list may indicate, for example, each device currently connected to the CAM system 104. According to this example, the current connection data can include or indicate each device currently connected to the CAM system 104.

[0112] In another example, the current connection data may be received with the analyte data from the transceiver 136. For instance, the transceiver 136 may add the current connection data to the analyte data to create a single instance of data that is then sent to the patient display device 107. The current connection data may include an identification of all devices currently connected to the transceiver 136, a number of devices that are currently connected to the transceiver 136, a value indicating a current priority of the patient display device 107 with respect to all devices currently connected to the transceiver 136, a time of each device’s last connection, any errors orwarnings related to each device’s connection, any errors or warnings related to each device (e.g., low battery or low storage space), etc.

[0113] At decision block 506, the application 106 determines whether the patient display device 107 satisfies predetermined device criteria for transmitting the analyte data to a remote target, such as the server system 330 of FIG. 3. In certain aspects, the predetermined device criteria can be satisfied if the current connection data indicates that the patient display device 107 is the only device currently connected to the CAM system 104. In some of these aspects, the predetermined device criteria can otherwise be deemed to be unsatisfied (e.g., a smartwatch only transmits to the remote target if it is the only device currently connected to the CAM system 104.).

[0114] In certain aspects, the predetermined device criteria can be satisfied if the current connection data indicates that the patient display device 107 is the highest priority device among multiple devices connected to the CAM system 104. In some of these aspects, the predetermined device criteria can provide for prioritizing the multiple devices by device type (e.g., (1) smartphone; (2) smartwatch; (3) AR / VR headset; (4) tablet, etc.). In additional, or alternatively, the predetermined device criteria can provide for prioritizing the multiple devices by user preference, device capabilities (e.g., bandwidth, transmission speed, battery life, etc.), and / or the like. Other examples of predetermined device criteria will be apparent to one skilled in the art after a detailed review of the present disclosure.

[0115] In certain aspects, blocks 504 and 506 together serve as an example of determining a current status of a connection between the patient display device 107 and the CAM system 104, as discussed relative to the block 404 of FIG. 4. The current status can indicate, for example, whether the patient display device 107 is the only device currently connected to the CAM system 104, a priority of the patient display device 107 relative to one or more other devices indicated in the current connection data, whether predetermined device criteria is satisfied, and / or the like. Other examples of the current status will be apparent to one skilled in the art after a detailed review of the present disclosure.

[0116] If it is determined, at the decision block 506, that the predetermined device criteria is satisfied, at block 508, the application 106 enables the patient display device 107 to transmit the analyte data to the remote target. The block 508 can include, for example, causing the transmission to occur, allowing the transmission to occur according to a typical schedule or flow, and / or thelike. In some cases, the enablement can involve updating a network transmission setting, for example, by turning the setting to “ON.”

[0117] If it is determined, at the decision block 506, that the predetermined device criteria is not satisfied, at block 510, the application 106 prevents the patient display device 107 from transmitting the analyte data to the remote target. The block 510 can include, for example, not instructing or causing the transmission to occur, canceling or blocking a transmission that would otherwise occur according to a typical schedule or flow, and / or the like. In some cases, the prevention can involve updating a network transmission setting, for example, by turning the setting to “OFF.” In this way, application 106 can cause the patient display device 107 to defer to at least one higher priority device. In certain aspects, blocks 508 and 510 together serve as an example of conditionally transmitting as discussed relative to the block 406 of FIG. 4. After either block 508 or block 510, the process 500 ends.

[0118] FIG. 6 illustrates an example of a process 600 for optimizing transmission of analyte data in multi-receiver environments based on a combination of urgency and current connection status, in accordance with certain embodiments. In some embodiments, the process 600 can be executed, for example, by the therapy management engine 112 of FIGS. 1 A-B and 2. In addition, or alternatively, the process 600 can be executed, for example, by the application 106 of FIGS. 1A-B and 2. In addition, or alternatively, the process 600 can be executed generally by any of the display devices 107 of FIGS. I A-B and 2.

[0119] Although any number of systems, in whole or in part, can implement the process 600, to simplify discussion, the process 600 will be described as being performed by the application 106 of FIGS. 1 A-B and 2, with particular reference to the medical support system 300 of FIG. 3. With reference to the medical support system 300 of FIG. 3, in some aspects, the process 600 can be executed by each of the applications 106-1 and 106-2 before each potential transmission by the patient display devices 107a and 107c, respectively, to the server system 330. In addition, or alternatively, the process 600 can be executed by the application 106-1 and the application 106-2 at any suitable interval (e.g. every 5 minutes, every 10 minutes, every 15 minutes, every other transmission, etc.). Other variations will be apparent to one skilled in the art after a detailed review of the present disclosure.

[0120] At block 602, at the patient display device 107, the application 106 receives analyte data (c.g., analyte measurements) from the CAM system 104. The analyte data may be received, for example, via the transceiver 136 of the CAM system 104, as discussed relative to FIGS. 1A-B and 3.

[0121] At decision block 604, the application 106 determines whether the analyte data satisfies predetermined urgency criteria. The predetermined urgency criteria can relate, for example, to measured analyte levels over any past period of time and / or predicted levels over any future period of time. The predetermined urgency criteria can be specified, for example, in terms of a high threshold (e.g., a threshold associated with hyperglycemia), a low threshold (e.g., a threshold associated with hypoglycemia), a failure to fall within a target range of analyte levels (e.g., a predetermined range associated with euglycemia or a user-defined range), a time period over which any of the foregoing are satisfied, a rate of change, combinations of the foregoing and / or the like.

[0122] If it is determined, at the decision block 604, that the predetermined urgency criteria is satisfied, at block 606, the application 106 enables the patient display device 107 to transmit the analyte data to the remote target. In this way, the analyte data can be transmitted to the remote target regardless of whether other devices may also transmit the same data. The block 606 can include, for example, causing the transmission to occur, thereby allowing the transmission to occur according to a typical schedule or flow, and / or the like.

[0123] If it is determined, at the decision block 604, that the predetermined urgency criteria is not satisfied, at block 608, the application 106 can conditionally transmit the analyte data to the remote target based on a current connection status, for example, as discussed relative to FIG. 5. In general, the block 608 can involve the application executing, for example, blocks 504-510 of the process 500 of FIG. 5. In some embodiments, certain devices, such as a smartwatch or a device with limited network bandwidth or battery capacity, may be configured to only transmit analyte data when the predetermined urgency criteria is satisfied. In these embodiments, in the case of the analyte data not satisfying the urgency criteria, rather than execute the block 606 as shown, the application 106 can prevent the patient display device 107 from transmitting the analyte data to the remote target, as discussed relative to the block 510 of FIG. 5. After either block 606 or 608, the process 600 ends.

[0124] In certain aspects, as described above relative to the process 500 of FIG. 1 and the process 600 of FIG. 6, the application 106 may optimize transmission of analyte data, in part, using a connection list for the CAM system 104, such as the connection list discussed relative to the transceiver 136 of FIG. IB. In some cases, however, there may be a certain amount of delay between a device disconnecting with the CAM system 104 and the CAM system 104 updating the connection list to reflect the disconnection. Therefore, in these embodiments, it is possible that a device listed in the connection list is not currently available to transmit analyte data to the remote target.

[0125] With respect to the foregoing scenario, consider an example in which the transceiver 136 of the CAM system 104 advertises every 5 minutes, 30 seconds is allowed for advertisement, and two missed connections are required for the transceiver 136 to remove a device from the connection list. In this example, a device that disconnects immediately after advertisement may not be removed from the connection list for approximately 10.5 minutes. Further, the absence of the device may not be noticed by other devices for approximately another 5 minutes, for a total delay of approximately 15 minutes. Therefore, in certain aspects, there is a possibility that the highest priority device in the connection list, for example, is no longer connected to the CAM system 104, and as such, is not available to transmit analyte data to the remote target. Additionally, in certain aspects, there is the further possibility that other devices may defer to the unavailable, highest priority device for the transmission of analyte data to the remote target, until such time that the connection list is updated and the devices become aware of that device’s unavailability. In such scenarios, the analyte data may not be transmitted to the remote target (e.g., the server system 330) in real-time. This non-transmission of analyte data can negatively impact an ability of the remote target to publish the analyte data to supporters, such as the supporter 308 of FIG. 3, thus negatively impacting the health of the user 102.

[0126] In certain aspects, the above risks can be reduced via utilization of urgency criteria as discussed relative to the process 600. According to the process 600, when the urgency criteria is satisfied, analyte data may be transmitted to the remote target regardless of whether other devices may also transmit the same data.

[0127] In addition, or alternatively, the impact of the above risks can be reduced or eliminated by taking additional action to verify current connections via inter-device communication. Anexample of verifying current connections via inter-device communication will be described relative to FIG. 7.

[0128] In addition, or alternatively, the above risks can be reduced or eliminated by determining current connection data via inter-device communication. In certain aspects, the determined current connection data can be used as a substitute for connection data received, for example, from the CAM system 104. An example of generating current connection data via interdevice communication will be described relative to FIG. 8.

[0129] FIG. 7 illustrates an example of a process 700 for optimizing transmission of analyte data in multi-receiver environments via inter-device communication, in accordance with certain embodiments. In some embodiments, the process 700 can be executed, for example, by the therapy management engine 112 of FIGS. 1A-B and 2. In addition, or alternatively, the process 700 can be executed, for example, by the application 106 of FIGS. 1A-B and 2. In addition, or alternatively, the process 700 can be executed generally by any of the display devices 107 of FIGS. 1A-B and 2.

[0130] Although any number of systems, in whole or in part, can implement the process 700, to simplify discussion, the process 700 will be described as being performed by the application 106 of FIGS. 1 A-B and 2, with particular reference to the medical support system 300 of FIG. 3. With reference to the medical support system 300 of FIG. 3, in some aspects, the process 700 can be executed by each of the applications 106-1 and 106-2 before each potential transmission by the patient display devices 107a and 107c, respectively, to the server system 330. In addition, or alternatively, the process 700 can be executed by the application 106-1 and the application 106-2 at any suitable interval (e.g. every 5 minutes, every 10 minutes, every 15 minutes, every other transmission, etc.). Other variations will be apparent to one skilled in the art after a detailed review of the present disclosure.

[0131] At block 702, at the patient display device 107, the application 106 receives analyte data (e.g., analyte measurements) from the CAM system 104. The analyte data may be received, for example, via the transceiver 136 of the CAM system 104, as discussed relative to FIGS. 1A-B and 3.

[0132] At block 704, the application 106 retrieves current connection data for the CAM system 104. In general, the block 704 can include performing any of the functionality discussed relativeto the block 504 of FIG. 5. As discussed relative to the block 504 of FIG. 5, the current connection data can include or indicate each device currently connected to the CAM system 104.

[0133] At block 706, the application 106 verifies the current connection data via inter-device communication. For example, the application 106 can cause the patient display device 107 to attempt to communicate with each other device currently connected to the CAM system 104, as indicated by the current connection data, and query these other device(s) to verify each device’s current connectivity to the CAM system 104.

[0134] At block 708, the application 106 updates the current connection data to remove any unverified connections. In general, an unverified connection can result from a failure to verify that a given device is currently connected to the CAM system 104. In an example, if the application106 determines, from the attempted synchronization, that another device indicated in the current connection data is not in range of the CAM system 104 and / or is no longer connected to the CAM system 104, such other device can be removed from the current connection data. In another example, if the patient display device 107 is unable to communicate with another device indicated by the current connection data, such other device can be removed from the current connection data.

[0135] In certain aspects, blocks 704, 706, and 708 together serve as an example of determining a current status of a connection between the patient display device 107 and the CAM system 104, as discussed relative to the block 404 of FIG. 4. The current status can indicate, for example, based on the updated current connection data, whether the patient display device 107 is the only device currently connected to the CAM system 104, a priority of the patient display device107 relative to one or more other devices indicated in the updated current connection data, whether predetermined device criteria is satisfied, and / or the like. Other examples of the current status will be apparent to one skilled in the art after a detailed review of the present disclosure.

[0136] At block 710, the application 106 can conditionally transmit the analyte data to the remote target based on a current connection status, for example, as discussed relative to FIG. 5. In certain aspects, block 710 serves as an example of conditionally transmitting as discussed relative to the block 406 of FIG. 4. In general, the block 710 can involve the application executing, for example, blocks 506-510 of the process 500 of FIG. 5, with respect to the updated current connection data resulting from the block 708. After block 710, the process 700 ends.

[0137] In addition, although FIG. 7 illustrates the current connection data being verified and updated via intcr-dcvicc communication, it should be appreciated that, in certain aspects, the current connection data can be verified and updated in other ways. In an example, the application 106 can verify and update the current connection data based on an automated review of timestamps in the connection list. With reference to FIG. 3, consider an example in which the patient display device 107c is primary and the patient display device 107a is secondary, according to suitable predetermined criteria, as discussed above, where both devices are listed in the connection list. In this example, the connection list include a timestamp for each device’s most recent connection. Further, for purposes of this example, the transceiver 136 of the CAM system 104 is configured to remove a given device from the connection list after two missed connections.

[0138] According to foregoing example, if the application 106-1 on the patient display device 107a recognizes that the patient display device 107c missed its most recent connection (e.g., as indicated by the lack of a timestamp corresponding to the most recent advertisement period), the application 106- 1 can update the current connection data to remove the patient display device 107c, in similar fashion to the block 708 of FIG. 7. Accordingly, conditional transmission occurs based on the updated current connection data, as discussed relative to the block 710 of FIG. 7. According to this example, this conditional transmission would result in the application 106-1 enabling the patient display device 107a to transmit the analyte data to the remote target, even though the patient display device 107a would not otherwise perform such transmission as the secondary device. Advantageously, in certain aspects, utilization of timestamps in this fashion can decrease the amount of time it takes for a device disconnection to be noticed and acted upon by other devices, while still minimizing redundant transmissions.

[0139] FIG. 8 illustrates another example of a process 800 for optimizing transmission of analyte data in multi-receiver environments via inter-device communication, in accordance with certain embodiments. In some embodiments, the process 800 can be executed, for example, by the therapy management engine 112 of FIGS. 1A-B and 2. In addition, or alternatively, the process 700 can be executed, for example, by the application 106 of FIGS. 1A-B and 2. In addition, or alternatively, the process 700 can be executed generally by any of the display devices 107 of FIGS. 1A-B and 2.

[0140] Although any number of systems, in whole or in part, can implement the process 800, to simplify discussion, the process 800 will be described as being performed by the application 106 of FIGS. 1 A-B and 2, with particular reference to the medical support system 300 of FIG. 3. With reference to the medical support system 300 of FIG. 3, in some aspects, the process 800 can be executed by each of the applications 106-1 and 106-2 before each potential transmission by the patient display devices 107a and 107c, respectively, to the server system 330. In addition, or alternatively, the process 800 can be executed by the application 106-1 and the application 106-2 at any suitable interval (e.g. every 5 minutes, every 10 minutes, every 15 minutes, every other transmission, etc.). Other variations will be apparent to one skilled in the art after a detailed review of the present disclosure.

[0141] At block 802, at the patient display device 107, the application 106 receives analyte data (e.g., analyte measurements) from the CAM system 104. The analyte data may be received, for example, via the transceiver 136 of the CAM system 104, as discussed relative to FIGS. 1A-B and 3.

[0142] At block 804, the application 106 determines current connection data for the CAM system 104 via inter-device communication with one or more other devices that may also connected to the CAM system 104. For example, the one or more other devices can be identified in a predetermined list stored on the patient display device 107 or in a storage location accessible thereto. In another example, the one or more other devices can correspond to devices currently connected to (e.g., paired to) the patient display device 107 (e.g., a smartwatch paired to a phone). In another example, the one or more devices can be identified from a connection list previously received, for example, from the CAM system 104.

[0143] In general, the block 804 can include, for example, the application 106 causing the patient display device 107 to attempt to communicate with each device of the one or more other devices to determine whether that device is currently connected to the CAM system 104. The communication can involve, for example, the display device 107 requesting, from each of the one or more other devices, a current communication status between that device and the CAM system 104. In certain aspects, each device that responds with an indication that the device is currently connected to the CAM system 104 can be included in the current connection data. In this way, the current connection data determined at the block 806 can include the display device 107 as well aseach other device that the application 106 determines is currently connected to the CAM system 104.

[0144] In certain aspects, the functionality described relative to the block 804 can be performed as part of the process 800 as illustrated. In addition, or alternatively, in certain aspects, the functionality described relative to the block 804 can be performed every minute, every 5 minutes, every 10 minutes, or at another periodic interval, without being a specific part of the process 800.

[0145] At decision block 806, the application 106 determines whether the patient display device 107 satisfies predetermined device criteria for transmitting the analyte data to a remote target, such as the server system 330 of FIG. 3. In certain aspects, the predetermined device criteria can be satisfied if the current connection data indicates that the patient display device 107 is the only device currently connected to the CAM system 104. In some of these aspects, the predetermined device criteria can otherwise be deemed to be unsatisfied (e.g., a smartwatch only transmits to the remote target if it is the only device currently connected to the CAM system 104.).

[0146] In certain aspects, the predetermined device criteria can be satisfied if the current connection data indicates that the patient display device 107 is the highest priority device among multiple devices connected to the CAM system 104. In some of these aspects, the predetermined device criteria can provide for prioritizing the multiple devices by device type (e.g., (1) smartphone; (2) smartwatch; (3) AR / VR headset; (4) tablet, etc.). In additional, or alternatively, the predetermined device criteria can provide for prioritizing the multiple devices by user preference, device capabilities (e.g., bandwidth, transmission speed, battery life, etc.), and / or the like. Other examples of predetermined device criteria will be apparent to one skilled in the art after a detailed review of the present disclosure.

[0147] In certain aspects, blocks 804 and 806 together serve as an example of determining a current status of a connection between the patient display device 107 and the CAM system 104, as discussed relative to the block 404 of FIG. 4. The current status can indicate, for example, whether the patient display device 107 is the only device currently connected to the CAM system 104, a priority of the patient display device 107 relative to one or more other devices indicated in the current connection data, whether predetermined device criteria is satisfied, and / or the like. Other examples of the current status will be apparent to one skilled in the art after a detailed review of the present disclosure.

[0148] If it is determined, at the decision block 806, that the predetermined device criteria is satisfied, at block 808, the application 106 enables the patient display device 107 to transmit the analyte data to the remote target. The block 808 can include, for example, causing the transmission to occur, allowing the transmission to occur according to a typical schedule or flow, and / or the like. In some cases, the enablement can involve updating a network transmission setting, for example, by turning the setting to “ON.”

[0149] If it is determined, at the decision block 806, that the predetermined device criteria is not satisfied, at block 810, the application 106 prevents the patient display device 107 from transmitting the analyte data to the remote target. The block 810 can include, for example, not instructing or causing the transmission to occur, canceling or blocking a transmission that would otherwise occur according to a typical schedule or flow, and / or the like. In some cases, the prevention can involve updating a network transmission setting, for example, by turning the setting to “OFF.” In this way, application 106 can cause the patient display device 107 to defer to at least one higher priority device. In certain aspects, blocks 808 and 810 together serve as an example of conditionally transmitting as discussed relative to the block 406 of FIG. 4. After either block 808 or block 810, the process 800 ends.

[0150] In the example of FIGS. 7 and 8, the current connection data is verified and generated, respectively, via inter-device communication. In some aspects, some devices (e.g., some smartwatches) may periodically enter a sleep mode and, furthermore, may not allow another device, such as a smartphone, to “wake” that device for communication as discussed above relative to the block 706 of FIG. 7 and the block 804 of FIG. 8. For example, with reference to the medical support system 300 of FIG. 3, in some implementations, the patient display device 107a may not allow the patient display device 107c to “wake” that device. According to this example, the application 106-1 of the patient display device 107a can cause the patient display device 107 a to periodically ping the patient display device 107c in order to prevent the patient display device 107a from entering a sleep mode, thereby maintaining communication. Advantageously, in certain implementations, this configuration of the application 106-1 can extend the foregoing ability to determine and / or update connection data via inter-device communication, as discussed relative to FIGS. 7 and 8.

[0151] FIG. 9 is a block diagram depicting a computer system 900 configured for optimizing transmission of analyte data in multi-receiver environments, for example, according to certainembodiments disclosed herein. Although depicted as a single physical device, in embodiments, the computer system 900 may be implemented using virtual dcvicc(s), and / or across a number of devices, such as in a cloud environment and / or via separate modules of portable or cloud devices. As illustrated, the computer system 900 includes a processor 905, a memory 910, a storage 915, a network interface 925, and one or more I / O interfaces 920. In the illustrated embodiment, the processor 905 retrieves and executes programming instructions stored in the memory 910, as well as stores and retrieves application data residing in the storage 915. The processor 905 is generally representative of a single CPU and / or GPU, multiple CPUs and / or GPUs, a single CPU and / or GPU having multiple processing cores, and the like.

[0152] The memory 910 is generally included to be representative of a random access memory (RAM). The storage 915 may be any combination of disk drives, flash-based storage devices, and the like, and may include fixed and / or removable storage devices, such as fixed disk drives, removable memory cards, caches, optical storage, network attached storage (NAS), or storage area networks (SAN).

[0153] In some embodiments, the I / O devices 935 (such as keyboards, monitors, etc.) can be connected via the I / O interface(s) 920. Further, via the network interface 925, the computer system 900 can be communicatively coupled with one or more other devices and components, such as the user database 110. In certain embodiments, the computer system 900 is communicatively coupled with other devices via a network, which may include the Internet, local network(s), and the like. The network may include wired connections, wireless connections, or a combination of wired and wireless connections. As illustrated, the processor 905, memory 910, storage 915, network interface(s) 925, and the I / O interface(s) 920 are communicatively coupled by one or more interconnects 930. In certain embodiments, the computer system 900 is representative of the display device 107 associated with the user. In certain embodiments, as discussed above, the display device 107 can include the user’s laptop, computer, smartphone, and the like. In another embodiment, the computer system 900 is a server executing in a cloud environment.

[0154] In the illustrated embodiment, the storage 915 includes the user profile 118. The memory 910 includes the therapy management engine 112. The therapy management engine 112 can be executed by the computer system 900 to perform operations, for example, of the process400 of FTG. 4, the process 500 of FIG. 5, the process 600 of FIG. 6, and / or the process 700 of FIG. 7.Example Clauses

[0155] Implementation examples are described in the following numbered clauses:

[0156] Clause 1: A method of optimizing data transmission from a device to a remote target, the method comprising, by the device: receiving analyte measurements from a continuous analyte monitoring (CAM) system; determining a current status of a connection between the device and the CAM system; and conditionally transmitting data related to the analyte measurements over a network to the remote target based on the current status of the connection.

[0157] Clause 2: The method of Clause 1, wherein the determining the current status of the connection comprises: retrieving current connection data for the CAM system; and determining, based on the current connection data, whether the device satisfies predetermined criteria for transmission of the data related to the analyte measurements.

[0158] Clause 3: The method of Clause 2, wherein the conditionally transmitting comprises: responsive to a determination that the device satisfies the predetermined criteria, enabling the device to transmit the data related to the analyte measurements to the remote target; and responsive to a determination that the device does not satisfy the predetermined criteria, preventing the device from transmitting the data related to the analyte measurements to the remote target.

[0159] Clause 4: The method of Clause 2, wherein: the current status indicates whether the device is the only device connected to the CAM system; and the predetermined criteria is satisfied if the device is the only device connected to the CAM system.

[0160] Clause 5: The method of Clause 2, wherein: the current status indicates a priority of the device relative to one or more other devices currently connected to the CAM system; and the predetermined criteria is satisfied if the device is the highest priority device connected to the CAM system.

[0161] Clause 6: The method of Clause 2, wherein: the current status indicates a priority of the device relative to one or more other devices currently connected to the CAM system; and the predetermined criteria is not satisfied if the device is not the highest priority device currently connected to the CAM system.

[0162] Clause 7: The method of Clause 2, wherein: the connection is between the device and a transmitter associated with the CAM system; and the retrieving the current connection data comprises retrieving a connection list from the transmitter associated with the CAM system.

[0163] Clause 8: The method of Clause 1, wherein the determining the current status of the connection comprises: determining current connection data via inter-device communication with one or more other devices; and determining, based on the current connection data, whether the device satisfies predetermined criteria for transmission of the data related to the analyte measurements.

[0164] Clause 9: The method of Clause 8, wherein the determining the current connection data via inter-device communication comprises: requesting, from each device of the one or more other devices, a current communication status between the device and the CAM system; responsive to the requesting, receiving, from at least one device of the one or more other devices, an indication that the at least one device is currently connected to the CAM system; and including the at least one device in the current connection data.

[0165] Clause 10: The method of Clause 8, further comprising causing the device to periodically ping at least one device of the one or more other devices to prevent the at least one device from entering a sleep mode.

[0166] Clause 1 1 : The method of Clause 1 , wherein the determining the current status of the connection comprises: retrieving current connection data for the CAM system, the current connection data indicating a plurality of devices currently connected to the CAM system; verifying the current connection data by reviewing connection timestamps associated with the plurality of devices; and responsive to a failure to verify that at least one device of the plurality of devices is currently connected to the CAM system, updating the current connection data to remove the at least one device, wherein the current status is based on the updated current connection data.

[0167] Clause 12: A method of optimizing data transmission from a device to a remote target, the method comprising, by the device: receiving analyte measurements from a continuous analyte monitoring (CAM) system; determining whether the analyte measurements satisfy predetermined urgency criteria; and responsive to a determination that the analyte measurements satisfy the predetermined urgency criteria, enabling the device to transmit the data related to the analyte measurements to the remote target.

[0168] Clause 13: The method of Clause 12, wherein the predetermined urgency criteria comprises at least one of a high threshold or a low threshold.

[0169] Clause 14: The method of Clause 12, wherein the predetermined urgency criteria comprises a failure to fall within a target range of analyte levels.

[0170] Clause 15: The method of Clause 12, further comprising, responsive to a determination that the analyte measurements do not satisfy the predetermined urgency criteria: determining a current status of a connection between the device and the CAM system; and conditionally transmitting data related to the analyte measurements over a network to a remote target based on the current status of the connection.

[0171] Clause 16: The method of Clause 15, wherein the determining the current status of the connection comprises: retrieving current connection data for the CAM system; and determining, based on the current connection data, whether the device satisfies predetermined device criteria for transmission of the data related to the analyte measurements.

[0172] Clause 17: The method of Clause 16, wherein the conditionally transmitting comprises: responsive to a determination that the device satisfies the predetermined device criteria, enabling the device to transmit the data related to the analyte measurements to the remote target; and responsive to a determination that the device does not satisfy the predetermined device criteria, preventing the device from transmitting the data related to the analyte measurements to the remote target.

[0173] Clause 18: The method of Clause 16, wherein: the current status indicates whether the device is the only device connected to the CAM system; and the predetermined device criteria is satisfied if the device is the only device connected to the CAM system.

[0174] Clause 19: The method of Clause 16, wherein: the current status indicates a priority of the device relative to one or more other devices currently connected to the CAM system; and the predetermined device criteria is satisfied if the device is the highest priority device connected to the CAM system.

[0175] Clause 20: The method of Clause 16, wherein: the current status indicates a priority of the device relative to one or more other devices currently connected to the CAM system; and thepredetermined device criteria is not satisfied if the device is not the highest priority device currently connected to the CAM system.

[0176] Clause 21: The method of Clause 16, wherein: the connection is between the device and a transmitter associated with the CAM system; and the retrieving the current connection data comprises retrieving a connection list from the transmitter associated with the CAM system.

[0177] Clause 22: A method of optimizing data transmission from a device to a remote target, the method comprising, by the device: receiving analyte measurements from a continuous analyte monitoring (CAM) system; retrieving current connection data for the CAM system, the current connection data indicating a plurality of devices currently connected to the CAM system; verifying the current connection data via inter-device communication with one or more of the plurality of devices; responsive to a failure to verify that at least one device of the plurality of devices is currently connected to the CAM system, updating the current connection data to remove the at least one device; determining, based on the updated current connection data, whether the device satisfies predetermined criteria for transmission of data related to the analyte measurements; and conditionally transmitting data related to the analyte measurements over a network to the remote target based on the determination of whether the device satisfies the predetermined criteria for transmission.

[0178] Clause 23: The method of Clause 22, wherein the conditionally transmitting comprises: responsive to a determination that the device satisfies the predetermined criteria for transmission, enabling the device to transmit the data related to the analyte measurements to the remote target; and responsive to a determination that the device does not satisfy the predetermined criteria for transmission, preventing the device from transmitting the data related to the analyte measurements to the remote target.

[0179] Clause 24: The method of Clause 22, wherein the predetermined criteria is satisfied if the updated current connection data indicates that the device is the only device connected to the CAM system.

[0180] Clause 25: The method of Clause 22, wherein the predetermined criteria is satisfied if the updated current connection data indicates that the device is the highest priority device connected to the CAM system.

[0181] Clause 26: The method of Clause 22, wherein the predetermined criteria is not satisfied if the updated current connection data indicates that the device is not the highest priority device currently connected to the CAM system.

[0182] Clause 27: A method of optimizing data transmission from a device to a remote target, the method comprising, by the device: receiving analyte measurements from a continuous analyte monitoring (CAM) system; retrieving current connection data for the CAM system, the current connection data indicating a plurality of devices currently connected to the CAM system; verifying the current connection data by reviewing connection timestamps associated with the plurality of devices; responsive to a failure to verify that at least one device of the plurality of devices is currently connected to the CAM system, updating the current connection data to remove the at least one device; and determining, based on the updated current connection data, whether the device satisfies predetermined criteria for transmission of data related to the analyte measurements; and conditionally transmitting data related to the analyte measurements over a network to the remote target based on the determination of whether the device satisfies the predetermined criteria for transmission.

[0183] Clause 28: A method of optimizing data transmission from a device to a remote target, the method comprising, by the device: receiving analyte measurements from a continuous analyte monitoring (CAM) system; determining whether the analyte measurements fall within a predetermined target range; and responsive to a determination that the analyte measurements do not fall within the predetermined target range, enabling the device to transmit the data related to the analyte measurements to the remote target.

[0184] Clause 29: The method of Clause 28, further comprising, responsive to a determination that the analyte measurements fall within the predetermined target range: determining a current status of a connection between the device and the CAM system; and conditionally transmitting data related to the analyte measurements over a network to a remote target based on the current status of the connection.

[0185] Clause 30: The method of Clause 29, wherein the determining the current status of the connection comprises: retrieving current connection data for the CAM system; and determining, based on the current connection data, whether the device satisfies predetermined device criteria for transmission of the data related to the analyte measurements.

[0186] Clause 31 : The method of Clause 30, wherein the conditionally transmitting comprises: responsive to a determination that the device satisfies the predetermined device criteria, enabling the device to transmit the data related to the analyte measurements to the remote target; and responsive to a determination that the device does not satisfy the predetermined device criteria, preventing the device from transmitting the data related to the analyte measurements to the remote target.

[0187] Clause 32: The method of Clause 30, wherein: the current status indicates whether the device is the only device connected to the CAM system; and the predetermined device criteria is satisfied if the device is the only device connected to the CAM system.

[0188] Clause 33: The method of Clause 30, wherein: the current status indicates a priority of the device relative to one or more other devices currently connected to the CAM system; and the predetermined device criteria is satisfied if the device is the highest priority device connected to the CAM system.

[0189] Clause 34: The method of Clause 30, wherein: the current status indicates a priority of the device relative to one or more other devices currently connected to the CAM system; and the predetermined device criteria is not satisfied if the device is not the highest priority device currently connected to the CAM system.

[0190] Clause 35: The method of Clause 30, wherein: the connection is between the device and a transmitter associated with the CAM system; and the retrieving the current connection data comprises retrieving a connection list from the transmitter associated with the CAM system.

[0191] Clause 36: The method of Clause 30, wherein: the CAM system comprises a continuous glucose monitoring system; and the analyte measurements comprise glucose measurements.

[0192] Clause 37: A method of optimizing data transmission from a device to a remote target, the method comprising, by the device: receiving analyte measurements from a continuous analyte monitoring (CAM) system; communicating with one or more other devices to determine current connection data for the CAM system; determining, based on the current connection data, whether the device satisfies predetermined criteria for transmission of the data related to the analyte measurements; and conditionally transmitting data related to the analyte measurements over anetwork to the remote target based on the determination of whether the device satisfies the predetermined criteria for transmission.

[0193] Clause 38: The method of Clause 37, wherein the communicating comprises: requesting, from each device of the one or more other devices, a current communication status between the device and the CAM system; responsive to the requesting, receiving, from at least one device of the one or more other devices, an indication that the at least one device is currently connected to the CAM system; and including the at least one device in the current connection data.

[0194] Clause 39: The method of Clause 38, wherein the communicating is performed at a periodic interval.

[0195] Clause 40: The method of Clause 37, wherein the conditionally transmitting comprises: responsive to a determination that the device satisfies the predetermined criteria for transmission, enabling the device to transmit the data related to the analyte measurements to the remote target; and responsive to a determination that the device does not satisfy the predetermined criteria for transmission, preventing the device from transmitting the data related to the analyte measurements to the remote target.

[0196] Clause 41: The method of Clause 37, further comprising causing the device to periodically ping at least one device of the one or more other devices to prevent the at least one device from entering a sleep mode.

[0197] Clause 42: The method of Clause 37, wherein the predetermined criteria is satisfied if the current connection data indicates that the device is the only device connected to the CAM system.

[0198] Clause 43: The method of Clause 37, wherein the predetermined criteria is satisfied if the current connection data indicates that the device is the highest priority device connected to the CAM system.

[0199] Clause 44: The method of Clause 37, wherein the predetermined criteria is not satisfied if the current connection data indicates that the device is not the highest priority device currently connected to the CAM system.

[0200] Clause 45: A system for optimizing data transmissions to a remote target, comprising: a continuous analyte monitoring system configured to generate measurements associated with ananalyte level of a patient; a device in data communication with the continuous analyte monitoring system and configured to perform one or more operations comprising: receiving analyte measurements from a continuous analyte monitoring (CAM) system; determining a current status of a connection between the device and the CAM system; and conditionally transmitting data related to the analyte measurements over a network to the remote target based on the current status of the connection.

[0201] Clause 46: A system for optimizing data transmissions to a remote target, comprising: a continuous analyte monitoring system configured to generate measurements associated with an analyte level of a patient; a device in data communication with the continuous analyte monitoring system and configured to perform one or more operations comprising: receiving analyte measurements from a continuous analyte monitoring (CAM) system; determining whether the analyte measurements satisfy predetermined urgency criteria; and responsive to a determination that the analyte measurements satisfy the predetermined urgency criteria, enabling the device to transmit the data related to the analyte measurements to the remote target.

[0202] Clause 47: A system for optimizing data transmissions to a remote target, comprising: a continuous analyte monitoring system configured to generate measurements associated with an analyte level of a patient; a device in data communication with the continuous analyte monitoring system and configured to perform one or more operations comprising: receiving analyte measurements from a continuous analyte monitoring (CAM) system; retrieving current connection data for the CAM system, the current connection data indicating a plurality of devices currently connected to the CAM system; verifying the current connection data via inter-device communication with one or more of the plurality of devices; responsive to a failure to verify that at least one device of the plurality of devices is currently connected to the CAM system, updating the current connection data to remove the at least one device; determining, based on the updated current connection data, whether the device satisfies predetermined criteria for transmission of data related to the analyte measurements; and conditionally transmitting data related to the analyte measurements over a network to the remote target based on the determination of whether the device satisfies the predetermined criteria for transmission.

[0203] Clause 48: A system for optimizing data transmissions to a remote target, comprising: a continuous analyte monitoring system configured to generate measurements associated with ananalyte level of a patient; a device in data communication with the continuous analyte monitoring system and configured to perform one or more operations comprising: receiving analyte measurements from a continuous analyte monitoring (CAM) system; retrieving current connection data for the CAM system, the current connection data indicating a plurality of devices currently connected to the CAM system; verifying the current connection data by reviewing connection timestamps associated with the plurality of devices; responsive to a failure to verify that at least one device of the plurality of devices is currently connected to the CAM system, updating the current connection data to remove the at least one device; and determining, based on the updated current connection data, whether the device satisfies predetermined criteria for transmission of data related to the analyte measurements; and conditionally transmitting data related to the analyte measurements over a network to the remote target based on the determination of whether the device satisfies the predetermined criteria for transmission.

[0204] Clause 49: A system for optimizing data transmissions to a remote target, comprising: a continuous analyte monitoring system configured to generate measurements associated with an analyte level of a patient; a device in data communication with the continuous analyte monitoring system and configured to perform one or more operations comprising: receiving analyte measurements from a continuous analyte monitoring (CAM) system; determining whether the analyte measurements fall within a predetermined target range; and responsive to a determination that the analyte measurements do not fall within the predetermined target range, enabling the device to transmit the data related to the analyte measurements to the remote target.

[0205] Clause 50: A system for optimizing data transmissions to a remote target, comprising: a continuous analyte monitoring system configured to generate measurements associated with an analyte level of a patient; a device in data communication with the continuous analyte monitoring system and configured to perform one or more operations comprising: receiving analyte measurements from a continuous analyte monitoring (CAM) system; communicating with one or more other devices to determine current connection data for the CAM system; determining, based on the current connection data, whether the device satisfies predetermined criteria for transmission of the data related to the analyte measurements; and conditionally transmitting data related to the analyte measurements over a network to the remote target based on the determination of whether the device satisfies the predetermined criteria for transmission.

[0206] Clause 51 : An apparatus, comprising: at least one memory comprising executable instructions; and at least one processor configured to execute the executable instructions and cause the apparatus to perform a method in accordance with any combination of Clauses 1-44.

[0207] Clause 52: An apparatus, comprising means for performing a method in accordance with any combination of Clauses 1-44.

[0208] Clause 53: A non-transitory computer-readable medium comprising executable instructions that, when executed by at least one processor of an apparatus, cause the apparatus to perform a method in accordance with any combination of Clauses 1-44.

[0209] Clause 54: A computer program product embodied on a computer-readable storage medium comprising code for performing a method in accordance with any combination of Clauses 1-44.Additional Considerations

[0210] Each of these non-limiting examples can stand on its own or can be combined in various permutations or combinations with one or more of the other examples.

[0211] The above detailed description includes references to the accompanying drawings, which form a part of the detailed description. The drawings show, by way of illustration, specific embodiments in which the invention can be practiced. These embodiments are also referred to herein as “examples.” Such examples can include elements in addition to those shown or described. However, the present inventors also contemplate examples in which only those elements shown or described are provided. Moreover, the present inventors also contemplate examples using any combination or permutation of those elements shown or described (or one or more aspects thereof), either with respect to a particular example (or one or more aspects thereof), or with respect to other examples (or one or more aspects thereof) shown or described herein.

[0212] In the event of inconsistent usages between this document and any documents so incorporated by reference, the usage in this document controls.

[0213] In this document, the terms “a” or “an” are used, as is common in patent documents, to include one or more than one, independent of any other instances or usages of “at least one” or “one or more.” In this document, the term “or” is used to refer to a nonexclusive or, such that “A or B” includes “A but not B,” “B but not A,” and “A and B,” unless otherwise indicated. In thisdocument, the terms “including” and “in which” are used as the plain-English equivalents of the respective terms “comprising” and “wherein.” Also, in the following claims, the terms “including” and “comprising” are open-ended, that is, a system, device, article, composition, formulation, or process that includes elements in addition to those listed after such a term in a claim are still deemed to fall within the scope of that claim. Moreover, in the following claims, the terms “first,” “second,” and “third,” etc. are used merely as labels, and are not intended to impose numerical requirements on their objects.

[0214] Method examples described herein can be machine or computer-implemented at least in part. Some examples can include a computer-readable medium or machine-readable medium encoded with instructions operable to configure an electronic device to perform methods as described in the above examples. An implementation of such methods can include code, such as microcode, assembly language code, a higher-level language code, or the like. Such code can include computer readable instructions for performing various methods. The code may form portions of computer program products. Further, in an example, the code can be tangibly stored on one or more volatile, non-transitory, or non-volatile tangible computer-readable media, such as during execution or at other times. Examples of these tangible computer-readable media can include, but are not limited to, hard disks, removable magnetic disks, removable optical disks (e.g., compact disks and digital video disks), magnetic cassettes, memory cards or sticks, random access memories (RAMs), read only memories (ROMs), and the like.

[0215] The above description is intended to be illustrative, and not restrictive. For example, the above-described examples (or one or more aspects thereof) may be used in combination with each other. Other embodiments can be used, such as by one of ordinary skill in the art upon reviewing the above description. The Abstract is provided to comply with 37 C.F.R. § 1.72(b), to allow the reader to quickly ascertain the nature of the technical disclosure. It is submitted with the understanding that it will not be used to interpret or limit the scope or meaning of the claims. Also, in the above Detailed Description, various features may be grouped together to streamline the disclosure. This should not be interpreted as intending that an unclaimed disclosed feature is essential to any claim. Rather, inventive subject matter may lie in less than all features of a particular disclosed embodiment. Thus, the following claims are hereby incorporated into the Detailed Description as examples or embodiments, with each claim standing on its own as a separate embodiment, and it is contemplated that such embodiments can be combined with eachother in various combinations or permutations. The scope of the invention should be determined with reference to the appended claims, along with the full scope of equivalents to which such claims are entitled.

Claims

CLAIMS1. A method of optimizing data transmission from a device to a remote target, the method comprising: receiving analyte measurements from a continuous analyte monitoring (CAM) system; determining a current status of a connection between the device and the CAM system; and conditionally transmitting data related to the analyte measurements over a network to a remote target based on the current status of the connection.

2. The method of claim 1, wherein the determining the current status of the connection comprises: retrieving current connection data for the CAM system; and determining, based on the current connection data, whether the device satisfies predetermined criteria for transmission of the data related to the analyte measurements.

3. The method of claim 2, wherein the conditionally transmitting comprises: responsive to a determination that the device satisfies the predetermined criteria, enabling the device to transmit the data related to the analyte measurements to the remote target; and responsive to a determination that the device does not satisfy the predetermined criteria, preventing the device from transmitting the data related to the analyte measurements to the remote target.

4. The method of claim 3, wherein: the current status indicates whether the device is the only device connected to the CAM system; and the predetermined criteria is satisfied if the device is the only device connected to the CAM system.

5. The method of claim 3, wherein: the current status indicates a priority of the device relative to one more other devices currently connected to the CAM system; and the predetermined criteria is satisfied if the device is the highest priority device connected to the CAM system.

6. The method of claim 3, wherein: the current status indicates a priority of the device relative to one or more other devices currently connected to the CAM system; and the predetermined criteria is not satisfied if the device is not the highest priority device currently connected to the CAM system.

7. The method of claim 3, wherein: the connection is between the device and a transmitter associated with the CAM system; and the retrieving the current connection data comprises retrieving a connection list from the transmitter associated with the CAM system.

8. The method of claim 1, wherein the determining the current status of the connection comprises: determining current connection data via inter-device communication with one or more other devices; and determining, based on the current connection data, whether the device satisfies predetermined criteria for transmission of the data related to the analyte measurements.

9. The method of claim 8, wherein the determining the current connection data via intcr-dcvicc communication comprises: requesting, from each device of the one or more other devices, a current communication status between the device and the CAM system; responsive to the requesting, receiving, from at least one device of the one or more other devices, an indication that the at least one device is currently connected to the CAM system; and including the at least one device in the current connection data.

10. The method of claim 8, further comprising causing the device to periodically ping at least one device of the one or more other devices to prevent the at least one device from entering a sleep mode.

11. The method of claim 1 , wherein the determining the current status of the connection comprises: retrieving current connection data for the CAM system, the current connection data indicating a plurality of devices currently connected to the CAM system; verifying the current connection data by reviewing connection timestamps associated with the plurality of devices; and responsive to a failure to verify that at least one device of the plurality of devices is currently connected to the CAM system, updating the current connection data to remove the at least one device, wherein the current status is based on the updated current connection data.

12. A system for optimizing data transmissions from a device to a remote target, comprising: a continuous analyte monitoring (CAM) system configured to generate measurements associated with an analyte level of a patient; a device in data communication with the CAM system and configured to perform one or more operations comprising: receiving analyte measurements from the CAM system; determining a current status of a connection between the device and the CAM system; and conditionally transmitting data related to the analyte measurements over a network to a remote target based on the current status of the connection.

13. The system of claim 12, wherein the determining the current status of the connection comprises: retrieving current connection data for the CAM system; and determining, based on the current connection data, whether the device satisfies predetermined criteria for transmission of the data related to the analyte measurements.

14. The system of claim 13, wherein the conditionally transmitting comprises: responsive to a determination that the device satisfies the predetermined criteria, enabling the device to transmit the data related to the analyte measurements to the remote target; and responsive to a determination that the device does not satisfy the predetermined criteria, preventing the device from transmitting the data related to the analyte measurements to the remote target.

15. A computer-program product comprising a non-transitory computer-usable medium having computer-readable program code embodied therein, the computer-readable program code adapted to be executed to implement a method of optimizing data transmission from a device to a remote target, the method comprising: receiving analyte measurements from a continuous analyte monitoring (CAM) system; determining a current status of a connection between the device and the CAM system; and conditionally transmitting data related to the analyte measurements over a network to a remote target based on the current status of the connection.

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