Medicine injection and disease management systems, devices, and methods

Information

  • Patent Grant
  • 11806514
  • Patent Number
    11,806,514
  • Date Filed
    Tuesday, September 10, 2019
    4 years ago
  • Date Issued
    Tuesday, November 7, 2023
    6 months ago
Abstract
One or more embodiments of the present disclosure may include an insulin delivery system that includes an insulin delivery device, a user interface that includes multiple user-selectable icons or buttons each representing different meal characteristics, memory to store one or more user-specific dosage parameter, and a processor in communication with the memory and adapted to receive blood glucose data. The processor may also be adapted to determine initial meal characteristics associated with each of the user-selectable icons or buttons based on at least one of the user-specific dosage parameters. The processor may also be adapted to update the meal characteristics associated with each of the user-selectable icons or buttons based upon the blood glucose data.
Description
TECHNICAL FIELD

The present disclosure relates to medicine injection and disease management systems, devices, and methods, particularly those related to the management of diabetes and/or the delivery of insulin. In some embodiments, systems, methods, and devices provided herein can personalize user-selectable meal sizes for a user to enter meal data for purposes of obtaining recommendations regarding one or more medication doses. In some cases, one or more buttons (e.g., user-selectable icons, physical press buttons, etc.) can be personalized to describe an amount or range of amounts of insulin to be delivered and/or carbohydrates to be consumed.


BACKGROUND

Diabetes mellitus is a chronic metabolic disorder caused by an inability of a person's pancreas to produce sufficient amounts of the hormone, insulin, such that the person's metabolism is unable to provide for the proper absorption of sugar and starch. This failure leads to hyperglycemia, i.e., the presence of an excessive amount of analyte, such as glucose, within the blood plasma. Persistent hyperglycemia has been associated with a variety of serious symptoms and life threatening long-term complications such as dehydration, ketoacidosis, diabetic coma, cardiovascular diseases, chronic renal failure, retinal damage and nerve damages with the risk of amputation of extremities. Self-monitoring of blood glucose and the self-administration of insulin is the typical method for treating diabetes. The “correct” insulin dosage is a function of the level of glucose in the blood. Insufficient insulin dosages can result in hyperglycemia, and excessive insulin dosages can result in hypoglycemia, which can result in clumsiness, trouble talking, confusion, loss of consciousness, seizures, or death. Accordingly, people with diabetes (PWDs) face a considerable cognitive burden in determining an appropriate dosage of insulin.


In order to assist with this self-treatment, many diabetes-related devices (e.g., blood glucose meters, insulin pumps, etc.) are equipped with insulin bolus calculators that have the user input a number of carbohydrates consumed (or about to be consumed) and the bolus calculator outputs a recommended size for the insulin bolus dosage. Although bolus calculators remove some of the calculations that need to be made by the user in determining an appropriate insulin bolus dosage, bolus calculators still burden the user with the mental task of determining the number of carbohydrates in their meal and often require manual entry of data. Accordingly, there is a need for methods, systems, and devices that further reduce the cognitive burden on the user while improving the accuracy of a recommended insulin bolus dosage.


BRIEF SUMMARY

Systems, devices and methods provided herein can be equipped to simplify calculation of a recommended insulin dosage by simplifying a meal announcement process and/or simplifying the collection of an estimated glucose value (EGV). A meal announcement process can be simplified by providing a user interface that includes one or more meal announcement buttons, which can be user-selectable icons on a touchscreen, physical press buttons, jog dials, voice activation commands, etc. In some cases, meal announcement buttons can be located on part of an insulin delivery device or on an accessory for an insulin delivery device. In some cases, the insulin delivery device can be an insulin pen and a dose capture pen cap including the meal announcement buttons. In some cases, an insulin delivery device or an accessory therefor can be in wireless communication with a remote user interface device (e.g., a mobile application on a smartphone) and the meal announcement buttons can be on the remote user interface device (either as physical press buttons or as user-selectable icons on a touch screen). The one or more meal announcement buttons can be personalized based on user's use of the system. Such personalization may be based on a user interacting with various buttons or features (e.g., the user selecting various meal sizes for boluses), by providing boluses and measuring the effect for the boluses over time, or any other use of devices or systems in accordance with the present disclosure.


One or more embodiments of the present disclosure may include an insulin delivery system that includes an insulin delivery device, a user interface that includes multiple user-selectable icons or buttons each representing different meal characteristics, memory to store one or more user-specific dosage parameter, and a processor in communication with the memory and adapted to receive blood glucose data. The processor may also be adapted to determine initial meal characteristics associated with each of the user-selectable icons or buttons based on at least one of the user-specific dosage parameters. The processor may also be adapted to update the meal characteristics associated with each of the user-selectable icons or buttons based upon the blood glucose data.


In accordance with one or more devices, systems, or methods of the present disclosure, a device or system may include a blood glucose monitor or sensor.


In accordance with one or more devices, systems, or methods of the present disclosure, the systems or devices may include a flash glucose monitor that includes a flash near field communication circuit, and a system near field communication circuit in communication with the processor. In these and other embodiments, the processor may be adapted to receive the blood glucose data via near field communications (NFC) when the system near field communication circuit and the flash near field communication circuit are brought within an NFC communication distance.


In accordance with one or more devices, systems, or methods of the present disclosure, the systems or devices may include a continuous glucose monitor, and the processor may be adapted to receive wireless communications from the continuous glucose monitor at predetermined time intervals.


In accordance with one or more devices, systems, or methods of the present disclosure, the systems or devices may include a continuous glucose monitor, and the processor may be adapted to receive wireless communications from the continuous glucose monitor at predetermined time intervals.


In accordance with one or more devices, systems, or methods of the present disclosure, the user-selectable icons or buttons may each initially represent an amount of carbohydrates in 5 gram or 10 gram increments.


In accordance with one or more devices, systems, or methods of the present disclosure, the amount of carbohydrates initially represented by each of the plurality of icons may be determined based on an insulin Sensitivity Factor (ISF), a Carb Ratio (CR), a body weight, an age, a total daily basal (TDB) rate, a daily dosage of Long-Acting Insulin, a weight averaged total daily dosage (TDD) of insulin and/or a combination thereof of a person with diabetes (PWD).


In accordance with one or more devices, systems, or methods of the present disclosure, the processor may be further configured to determine an insulin delivery amount based on an amount of carbohydrates associated with a selected one of the user-selectable icons or buttons and/or the blood glucose data.


In accordance with one or more devices, systems, or methods of the present disclosure, the user-selectable icons or buttons may each represent a number of units of insulin that are needed to compensate for each meal, rounded to the nearest 0.5 units.


In accordance with one or more devices, systems, or methods of the present disclosure, the updating of the meal characteristics associated with each of the plurality of user-selectable icons or buttons may be determined from postprandial blood glucose data after the user has selected a given user-selectable icon or button.


In accordance with one or more devices, systems, or methods of the present disclosure, the systems or devices may include a flash glucose monitor that includes a flash near field communication circuit, and the systems or devices may further include one or more system near field communication circuits in communication with the processor. In these and other cases, the processor may be adapted to receive the postprandial blood glucose data via near field communications (NFC) when the one or more system near field communication circuits and the flash near field communication circuit are brought within an NFC communication distance. Additionally, the processor may be adapted to send a prompt to the user to retrieve the postprandial blood glucose data by bringing one of the one or more system near field communication circuits into close proximity to the flash glucose monitor at a predetermined time after insulin is delivered or one of the user-selectable icons or buttons has been selected by the user.


In accordance with one or more devices, systems, or methods of the present disclosure, the user interface may be adapted to display a bolus recommendation based on the blood glucose data and a selection of one of the user-selectable icons or buttons.


In accordance with one or more devices, systems, or methods of the present disclosure, the processor may determine the bolus recommendation based on factors selected from the number of carbohydrates divided by the PWD's carbohydrate-to-insulin ratio, a difference between the current blood glucose level and a target blood glucose level divided by the PWD's insulin sensitivity factor, a reading from a blood glucose meter (BGM), data from a continuous glucose monitor (CGM), blood glucose trend data, Insulin on Board (IOB) data, Carbohydrates on Board (COB) data, whether the PWD is or plans to exercise, whether the PWD is sick, whether the PWD is pregnant, whether the PWD is experiencing menses, and whether the PWD has consumed certain medications.


In accordance with one or more devices, systems, or methods of the present disclosure, the processor may be further adapted to receive dosage data from the insulin delivery device, and the update the meal characteristics associated with each of the user-selectable icons or buttons may be based upon postprandial blood glucose data after the user has selected that user-selectable icon or button, the dosage data, or a combination thereof.


In accordance with one or more devices, systems, or methods of the present disclosure, the insulin delivery device may include an insulin pen, and the user interface may be part of the insulin pen, part of a pen accessory adapted to reversibly connect to an insulin pen, or part of a mobile application for a smartphone in wireless communication with an insulin pen or an accessory therefore. In these and other embodiments, the devices or systems may be adapted to detect amounts of insulin remaining in or delivered by one or more insulin pens.


In accordance with one or more devices, systems, or methods of the present disclosure, the pen accessory may be adapted to reversibly connect to an insulin pen, where the pen accessory may include a pen cap that is adapted to detect amounts of insulin remaining in an insulin pen during placement or removal from the insulin pen or when secured to the insulin pen.


In accordance with one or more devices, systems, or methods of the present disclosure, the user interface may be located on the mobile application for a smartphone, where the smartphone further includes the processor, and the insulin pen or an accessory therefor is adapted to detect insulin amount or delivery data and wirelessly communicate the insulin amount or delivery data to the processor.


One or more embodiments of the present disclosure may include a cap for an insulin pen that includes one or more sensors adapted to detect the position of a plunger within an insulin pen, and a user interface that includes one or more user-selectable icons or buttons adapted to announce a meal or an intent to have a meal.


In accordance with one or more devices, systems, or methods of the present disclosure, the cap may include a processor and memory, where the processor may be adapted to determine a time and dosage for an insulin delivery based on data from the one or more sensors and store that information in the memory.


In accordance with one or more devices, systems, or methods of the present disclosure, the user interface may include at least 2, and no more than 6, user-selectable icons or buttons adapted to announce a meal or an intent to have a meal, each representing different meal characteristics stored for each button in the memory.


In accordance with one or more devices, systems, or methods of the present disclosure, the user interface may include a display adapted to display a recommended dosage based at least in part on a selection of the one or more user-selectable icons.


In accordance with one or more devices, systems, or methods of the present disclosure, the cap may include a wireless communication device adapted to communicate with a blood glucose monitor or sensor, where the display may be adapted to display a current blood glucose level, an indication of a current rate of change, a recommended correction bolus dosage based on glucose data, or a combination thereof.


In accordance with one or more devices, systems, or methods of the present disclosure, a wireless communication device of a cap may include an NFC circuit.


In accordance with one or more devices, systems, or methods of the present disclosure, the devices or systems may include an annunciator adapted to prompt the user to obtain blood glucose data from the blood glucose monitor or sensor at a predetermined time after the selection of the one or more user-selectable icons or buttons.


In accordance with one or more devices, systems, or methods of the present disclosure, the devices or systems may include an annunciator adapted to provide an alarm when data from a blood glucose monitor or sensor indicates a need to provide therapy.


In accordance with one or more devices, systems, or methods of the present disclosure, the systems or devices may include a processor and memory, the memory storing meal characterizations for each of the one or more user-selectable icons or buttons, and the processor being adapted to receive blood glucose data and update the meal characterizations for each of the one or more user-selectable icons or buttons based on the blood glucose data.


In accordance with one or more devices, systems, or methods of the present disclosure, the systems or devices may include memory that can store multiple meal characterizations for a single user-selectable icon or button based on the time of day.


In accordance with one or more devices, systems, or methods of the present disclosure, the systems or devices may include a cap that further includes a sensor adapted to detect a characterization of an insulin pen or a type of insulin in an insulin pen, a memory to store information about different types of insulin pens or different types of insulin, and a processor to determine the type of insulin pen or the type of insulin.


In accordance with one or more devices, systems, or methods of the present disclosure, the systems or devices may include a processor adapted to change the user interface dependent on the type of insulin pen or the type of insulin, where some types of insulin or insulin pens result in a user-interface that does not include any user-selectable icons or buttons adapted to announce a meal or an intent to have a meal.





BRIEF DESCRIPTION OF THE DRAWINGS


FIG. 1A illustrates a hypothetical insulin delivery system that includes insulin pens, a glucose monitor or sensor, and a remote user interface device having a remote user interface.



FIG. 1B illustrates an exemplary meal announcement screen for a remote user interface device, which can be displayed by the remote user interface device of FIG. 1A.



FIGS. 2A and 2B depict an insulin pen with a first exemplary insulin pen cap having some of the features disclosed herein.



FIGS. 3A and 3B depict an insulin pen with a second exemplary insulin pen cap having some of the features disclosed herein.



FIG. 4 shows a schematic of internal components that may be included in the insulin pen caps of FIGS. 2A-3B.



FIGS. 5A and 5B depict an exemplary dose capture technique, which can be incorporated into the pen caps of FIGS. 2A-3B.



FIG. 6A is a flow chart of how a user may interact with an insulin pen cap provided herein.



FIG. 6B illustrates exemplary user interfaces that a user may see on a pen cap (or on an insulin delivery pen) during use of certain methods, systems, and devices provided herein.



FIG. 7 illustrates exemplary user interfaces that a user may see on a pen cap (or on an insulin delivery pen) when preparing certain methods, systems, and devices provided herein for use.



FIGS. 8A and 8B depict notices that may appear on a remote user interface device in some embodiments of methods, systems, and devices provided herein.



FIGS. 9A and 9B are charts illustrating how meal characterizations and user-specific dosage parameters can be initiated or updated.



FIGS. 10A and 10B depicts how a user might transmit data between a flash glucose monitor and an insulin pen or insulin pen cap prior to administering insulin.





DETAILED DESCRIPTION

Insulin delivery systems and devices, and methods for delivering insulin, can be designed to minimize the cognitive and active burden for people with diabetes (PWDs), or their caregivers, as they decide to administer insulin. In some embodiment's, methods, systems, and devices provided herein can passively capture diabetes-relevant data (e.g., insulin delivery data, blood glucose data, etc.) with or without providing the PWD (or a caregiver) with recommendations. In some embodiments, methods, systems, and devices provided herein can provide guidance regarding an appropriate dosage of insulin. In some embodiments, the dosage of insulin can be administered with an insulin delivery pen or syringe. In some cases, the insulin can be a long-acting insulin. In some cases, the insulin can be a quick-acting insulin. In some embodiments, an insulin delivery pen, or accessory therefor (e.g., a cap), can detect an amount of insulin delivered from the pen (or an amount of insulin that was set for delivery). In some cases, an insulin pen, or an accessory therefor, can include a user-interface, which can display data or recommendations to the user and/or permit the user to enter data into the insulin pen or accessory. The following exemplary system includes insulin delivery pens having dose capture pen caps, but alternative embodiments are also envisioned where the functionality disclosed herein is incorporated into other accessories for an insulin delivery pen or the insulin delivery pen itself.


Exemplary Insulin Delivery System



FIG. 1A illustrates a hypothetical insulin delivery system 100 that includes a quick-acting insulin (QAI) pen 160 (e.g., HUMALOG™, NOVOLOG™, APIDRA™), a long-acting insulin (LAI) pen 170 (e.g., LANTUSs™, LEVEMIR™, TOUJEO™, TRESIBA™), a glucose monitor or sensor 150, and a remote user interface device 110. As shown, each insulin pen 160 and 170 includes a dose capture cap 182 and 184, respectively, which are in wireless communication with other components of system 100. As shown, the pens can include dials 161 and 171 for a user to set a dosage to be delivered and a dose indicator window 162 and 172. In alternative systems, the insulin pens 160 and/or 170 may themselves include dose capture technology and/or be in wireless communication with other components of system 100. Additional details about possible insulin pens and/or insulin pen caps are disclosed in greater detail below.


Glucose monitor or sensor 150 can be any suitable sensor device and/or monitoring system capable of providing data that can be used to estimate one or more blood glucose values. As shown, glucose monitor or sensor 150 can be a sensor configured to transmit blood glucose data wirelessly. For example, the glucose monitor or sensor 150 can include an optical communication device, an infrared communication device, a wireless communication device (such as an antenna), and/or chipset (such as a BLUETOOTH® device (e.g., BLUETOOTH® Low Energy, Classic BLUETOOTH®, etc.), a Near-field communication (NFC) device, an 802.6 device (e.g., Metropolitan Area Network (MAN), a ZIGBEE® device, etc.), a WiFi device, a WIMAX® device, cellular communication facilities, etc.), and/or the like. The glucose monitor or sensor 150 may exchange data with a network and/or any other devices or systems described in the present disclosure. In some cases, glucose monitor or sensor 150 can be interrogated with an NFC device by the user moving one or more components of the system near the glucose monitor or sensor 150 to power and/or transmit blood glucose data from the glucose monitor or sensor 150 to other components of system 100.


As shown, remote user interface device 110 is a smartphone, but any suitable remote user interface device can be used, such as a computer tablet, a smartphone, a wearable computing device, a smartwatch, a fitness tracker, a laptop computer, a desktop computer, a smart insulin pen (e.g., the dose capture caps 182 and/or 184), and/or other appropriate computing devices. As shown in the exemplary user interface of the exemplary mobile app running on the depicted smartphone, the user interface can include a bolus calculator button 114 and optionally other buttons for the user to enter data or to request recommendations. The exemplary user interface can also include a display of blood glucose data, past, present, or predicted. As shown, the user interface includes a graph of historical data from the previous 30 minutes 123, a continuation of that graph having projected data 124, a point indicator 122 showing the current (or most recent) estimated blood glucose value, and a display of the current (or most recent) estimated blood glucose value 121. The user interface can also include text explaining the glucose data 131, text providing suggested actions 132 and 133, such as text providing insulin, carbohydrates, or other therapy suggestions 132 and/or text suggesting that the user obtain blood glucose data 133. In some cases, the user interface can permit the user to click on the glucose data or otherwise navigate in the mobile app to obtain more detailed or more complete blood glucose data.


The user interface can also depict insulin data. In some cases, the user interface can indicate an amount of Insulin-on-Board (IOB) 135, which may be only for Quick-Acting Insulin. In some cases, an IOB calculation may be for both quick-acting and long-acting insulin. In some cases, the user interface can display the time and/or amounts of the most recent doses of quick-acting and/or long-acting insulins 134. In some cases, the user interface can permit the user to click on the insulin data or otherwise navigate in the mobile app to more detailed or more complete insulin delivery data. In some cases, a user interface can overlay blood glucose data and insulin delivery data in any suitable format, such as a graphical display of the timing of blood glucose data vs. the timing of insulin delivery data.


In use, a user (e.g., the PWD and/or a caregiver) can use system 100 to get recommendations regarding an appropriate insulin dosage. In the case of an upcoming need to deliver long-acting insulin, the message of 132 may change to provide a recommended long-acting insulin dosage. In some cases, a recommended dosage may appear on pen cap 184. In the case of the user wanting to deliver a bolus of quick-acting insulin, the user may press bolus calculator button 114 to enter into a bolus calculator. Although any suitable bolus calculator could be used in systems, methods, and devices provided herein, FIG. 1B depicts a possible user interface for a user to enter a meal announcement as either a correction only 141, a small meal 142, a normal sized meal 143, or a large meal 144. Upon selecting the meal size, the user interface can provide a recommended bolus dosage based on a number of carbohydrates associated with the corresponding button and optionally based upon blood glucose data.


Additionally, or alternatively, dose capture pen caps for the quick-acting insulin pen 160 can include a user interface that permits the user to announce a small meal, medium meal, or large meal. FIGS. 2A-3B depict possible embodiments of dose capture pen caps 200 and 300 having buttons 221-223 and 321-323 that permit the user to announce a small (S), medium (M), or large (L) meal. In use, a user could announce whether the meal that they just ate or are about to eat is their normal meal size, (M), or larger (L), or smaller (S), and methods, devices, and systems provided herein can determine an appropriate bolus dosage of insulin based on the announcement and optionally based on blood glucose data, if available. Alternatively, an insulin pen can include dose capture technology and include a user interface provided herein and described as being on a dose capture pen cap. In some cases, a smart pen having dose capture capabilities can wirelessly communicate with a remote user interface (e.g., a smartphone).


Personalizing Meal Announcement Buttons


As discussed above, methods, devices, and systems provided herein can provide a user with meal announcement buttons that provide the user with a reduced number of meal size selection options, which can be based upon the user's normal meal size, which can thus reduce the cognitive burden on a user seeking to administer insulin for a meal while improving the accuracy of insulin bolus recommendations. This section describes ways that methods, systems, and devices provided herein can determine an amount of insulin and/or an amount of carbohydrates to associate with each of the meal selection buttons (e.g., 141-144, 221-223, 321-323). Optionally, additional buttons can be present, such as a button that indicates a tiny meal or an extra-large meal for the user, such that any number of buttons are within the scope of the present disclosure. Additionally or alternatively, the system may include a single button, icon, or mode for announcing a meal to systems or devices of the present disclosure.


In some cases, each of the meal announcement buttons 142-144, 221-223, 321-323 can be associated with a number of carbohydrates that is personalized for the user based on other user-specific dosage parameters entered by the user for an insulin delivery system (e.g., total daily long-acting insulin dosage (e.g., U/day), a total daily dose of insulin (e.g., total of long and quick acting), a carbohydrate-to-insulin ratio, an insulin sensitivity factor, a glucose setpoint, or a combination thereof). In some cases, the number of carbohydrates assigned to each preset icon or button can be personalized over time based on estimations of the size of each meal consumed when that icon or button is selected based on a glucose response after the consumption of each meal. In some cases, the number of carbohydrates assigned to each preset icon or button can be rounded to the nearest 5 grams of carbohydrates and displayed. In some cases, a number of carbohydrates for each button is not displayed. In some cases, a user may manually enter personalized meal sizes for a number of user-selectable icons or buttons. In some cases, a number of carbohydrates assigned to each user-selectable icon or button can be initially set at a predetermined starting point or can be determined based on entered user information, and then iteratively adjusted upward or downward based upon the glycemic response to that selected meal size and bolus over time.


Initial settings for one or more meal announcement buttons 142-144, 221-223, 321-323 included on a device or in a system provided herein can be preset with predetermined values or ranges (e.g., small=20 g or 15-25 g, medium=30 g or 30-45 g, and large=50 g or 50-75 g). Additionally or alternatively, the initial settings can be set based on entered user data or based on one or more user-specific dosage parameters entered into a device or system provided herein. In some cases, initial settings for the one or more user-selectable icons or buttons can be based on an initially entered or determined and programmed total daily long-acting insulin (TDLAI) dose (e.g., U/day). For example, the relationship between the LAI dose [U/day] and Geometric Mean Meal Size [g] as characterized by the line corresponding to the major axis of the hyperellipsoid is: μ*MS=12.1*BR0.387. The relationship between Geometric Mean Meal Size [g] and Geometric Standard Deviation Meal Size is: σ*MS=1.92−μ*MS/186 where MS may represent the meal size and BR may represent the basal rate of insulin. Accordingly, initial meal size groups may correspond to predetermined percentiles of the Meal Size distribution by combining the above equations, optionally rounding meal size groups to the nearest 1.5, or 10 grams. In some cases, the relationship between typical meal sizes and other user-specific dosage parameters can be determined according to population statistics. In some cases, the number of carbohydrates associated with each user-selectable icon or button can be displayed on and/or adjacent to the user-selectable icon or button, which can help a user understand how to use the insulin delivery device or system to avoid deskilling the user. For example, seeing the number of carbohydrates assumed for each meal size helps a user that thinks about meals in terms of carbohydrates to adjust to using buttons to indicate a size of a meal. Additionally, by starting with display numbers rounded to the nearest 5 grams, the user can perceive that precision is not required, thus also reducing the cognitive burden on the user. Additionally, as the system iterates to personalize the amount of carbohydrates for each particular user-selectable icon or button, the system can adjust these numbers by smaller units (e.g., by 1 gram) to demonstrate to the user that the system is adjusting the number of carbohydrates associated with user-selectable icon or button.


In some cases, the user interface may be configured such that a PWD may interact with the user interface to enter more detailed information regarding the bolus size outside of the default options. For example, a PWD may be presented with a series of pre-set sizes that are readily adjustable in increments of 5 g by selecting a size and scrolling up or down. By interacting further with the user device (e.g., pressing and holding on the meal size), the user may have the option to manually input a bolus size or adjust the size in increments of 1 g.


Methods, systems, and devices provided herein can update the number of carbohydrates associated with each user-selectable icon or button using any suitable method. In some cases, methods, systems, and devices can use postprandial blood glucose data (e.g., between 1 hour and 3 hours after an announced meal) to evaluate whether the PWD likely consumed significantly more or significantly less carbohydrates than programmed for the user-selectable icon or button. In some cases, one or more postprandial blood glucose thresholds can be used to evaluate the match between the amount of carbohydrates consumed and the amount of carbohydrates associated with a selected user-selectable meal icon or button. For example, methods, devices, and systems provided herein can ask a user for a postprandial blood glucose reading from a glucose sensor, glucose monitor, or blood glucose meter. In some cases, a glucose sensor can be a flash glucose monitor and methods, systems, and devices provided herein can prompt the user to interrogate the flash glucose monitor at a predetermined postprandial time period. As used herein, the term “flash glucose monitor” may refer to a device configured to provide blood glucose readings in response to a manual invocation of the device, typically by a physical signal (e.g., a button, tap, etc.) or a wireless signal (e.g., a near-field communication (NFC), BLUETOOTH® communication, etc.). Such blood glucose readings may be performed periodically and reported when the device is invoked, or may be taken when invoked. In some cases, methods, devices, and systems provided here can receive postprandial blood glucose data from a continuous glucose monitor. In some cases, methods, systems, and devices provided herein can use a single postprandial blood glucose data point and compare that to one or more upper thresholds and one or more lower thresholds for that period of time to determine whether the number of carbohydrates associated with that user-selectable meal icon or button should be adjusted upward or downward. For example, if a user selects a typical meal icon indicating a meal of 30 grams of carbohydrates, but the 2-hour postprandial blood glucose reading is above 200 mg/dL, the number of grams associated with that icon or button might be adjusted upward by 2 grams, if it is above 170 mg/dL, it might be adjusted upward by 1 gram, if it is below 130 mg/dL, it might be reduced by 1 gram, and if it is below 100 mg/dL, it might be reduced by 2 grams. Accordingly, over time the meal icons would be adjusted to more closely resemble the user's typical consumption patterns in a way that matches the user's mental model surrounding the meals that they eat. The particular thresholds can be determined based on the postprandial time, the number of grams associated with the meal icon or button, the CR, ISF, and daily dose of LAI, and setpoint of the PWD, etc.


In some cases, meal announcement buttons can be personalized based on the time of the day. For example, in some cases, a user may have a larger average dinner and smaller average morning meals, and methods, devices, and systems provided herein can estimate an amount of carbohydrates for a user based on the time of day. In some cases, the amount of carbohydrates and the meal sizes (S, M, L) can be displayed together to help a user understand that the personalization is specific to the user's daily pattern. In some cases, buttons can be personalized based on the day of the week (e.g., a user's weekend meal patterns might be significantly different than during weekdays).


Because diabetes is a highly personal disease that presents the PWD or their caregiver(s) with significant cognitive burdens surrounding the determination of appropriate dosages of insulin, some PWDs or caregivers develop their own techniques (or mental model) for estimating an appropriate dosage of insulin. Although methods, systems, and devices provided herein can be adapted to provide recommendations to a user, the user may be free to dose insulin according to the user's preferences and the user's specific knowledge of what the PWD is about to eat and/or is experiencing (e.g., exercise, sickness, etc.). In some cases, meal announcement buttons can change based on repeated patterns of a user administering doses of insulin above or below a recommended dosage of insulin so that the meal announcement buttons begin to match the user's mental model regarding a typical meal size. Adjustments to an amount of carbohydrates represented by each meal announcement button based on the actual dosage, however, may be determined based on the postprandial blood glucose readings of a PWD. For example, if the postprandial blood glucose readings indicate an appropriate dosage, it can indicate that the user's mental model is appropriate for that meal, and that the system can thus adjust the meal announcement buttons to match the user's mental model (e.g., reduce the size of the meal assumed for a (S) meal based on a repeated pattern of the user administering less insulin than recommended for an (S) meal selection if postprandial blood glucose readings are usually within a predetermined range). However, in some cases, methods, devices, and systems, provided herein can use postprandial blood glucose readings to determine if the user's mental model failed to determine the appropriate dose. In some cases, a high or low postprandial blood glucose reading can prevent methods, systems, and devices provided herein from adjusting the meal announcement buttons based on meals where one or more postprandial blood glucose readings indicate a mismatch between the dose and the meal. For example, if a user administers less insulin than recommended for a selected small meal and has one or more high postprandial blood glucose readings, methods, systems, and devices provided herein can ignore that administration for the personalization of the meal announcement buttons. In some cases, methods, systems, and devices provided herein can provide notices to a user if the user is consistently ignoring the recommended dosages in a way that causes the PWD to go high or low after a meal if the usage pattern indicates a mismatch between the user's mental model and the PWD's physiology and food consumption patterns. For example, if the user is consistently administering less insulin than recommended and consistently having high blood glucose readings after a meal, a notice may indicate to the user that the user should consider administering the recommended doses at meal times in order to achieve better glycemic control. Accordingly, in some cases, methods, systems, and devices provided herein can be designed to improve the match between the user's mental model and the PWD's physiology and food consumption patterns.


In some cases, a remote user interface device 110 can permit a user to manually enter a specific number of carbohydrates into a bolus calculator for a recommendation for a specific meal. In some cases, methods, systems, and devices can use repeated patterns of a user requesting the same meal size recommendation to update the size of a meal announcement button or to add another meal announcement button.


Dose Capture Pen Caps



FIG. 1A depicts a system that can include dose capture pen caps 182 and 184, which can transmit data to and/or from a glucose monitor or sensor 150 and/or to/from a remote user interface device 110. The pen caps in FIG. 1A may or may not include a user interface. Pen caps 182 and 184 can use any suitable technology to determine an amount of insulin that has been administered from insulin pens 160 and 170. In some cases, not shown, insulin pens 160 and 170 can include dose capture technology and can communicate wirelessly with the remote user interface device 110 and/or glucose monitor or sensor 150.



FIGS. 2A-3B depict alternative embodiments of pen caps, 200 and 300, which can be used with an insulin pen to assist a PWD or caregiver (the user) with dosing decisions.



FIGS. 2A and 2B depict an embodiment of a pen cap 200 that includes a display screen 210 that can display an estimated glucose value (EGV) 212, the units for the EGV 211, and a trend indicator for the EGV 213. The display can also provide a recommended dosage 214 and an identification of the type of insulin 215. Pen cap 200 can also include meal announcement buttons 221-223. Additionally, the display may also indicate the time and amount of the previous dosage and/or an IOB value to remind a user about their most recent dosage. Although three meal announcement buttons are shown, in some cases a pen cap can include no meal announcement buttons and meals can be announced on a remote user interface device, such as device 110 as depicted in FIG. 1A. In some cases, pen cap 200 can include a single meal announcement button. In some cases, pen cap 200 can include between 2 and 6 different meal announcement buttons. In some cases, pen cap 200 can include a correction only button. Pen cap 200 can also include one or more indicator lights, such as indicator light 218, which can light up to indicate that it is transferring data, light up to indicate that the user's attention is needed, and/or light up to indicate whether a dose capture functionality is or is not working.



FIGS. 3A and 3B depict another embodiment of a pen cap 300 that includes a touch screen user interface 310 that can include meal announcement buttons 321-323 and display an estimated glucose value (EGV) 312, the units for the EGV 311, a trend indicator for the EGV 313, a recommended dosage 314 and an identification of the type of insulin 315. Additionally, the display may also indicate the time and amount of the previous dosage and/or an IOB value to remind a user about their most recent dosage. Although three meal announcement buttons are shown, the touch screen user interface 310 of pen cap 300 can be customized based on the user's preferences and/or the type of insulin to display different numbers of meal announcement buttons 321-323 and/or to not include meal announcement buttons. For example, if pen cap 300 is placed on a long-acting insulin pen, it may be capable of detecting the type of insulin and automatically updating the display to correctly identify the type of insulin at 315, but also to remove the meal announcement buttons 321-323 and replace them with other content.


Although pen caps 182, 184, 200, and 300 can use any suitable technology to estimate an insulin dosage, FIGS. 4, 5A, and 5B depict exemplary embodiments of pen cap components that may be used to detect a dosage of insulin.



FIG. 4 depicts a representation of the internal components of an exemplary pen cap 400. As shown, the pen cap 400 can include one or more displays 410, one or more buttons 420, and one or more annunciator(s) 416, each controlled by a processing system 432. Processing system 432 includes a processor 434, data storage (or memory) 436, and a communications subsystem 440. The communications subsystem 440 can enable wireless communication between the pen cap and a remote user interface device (e.g., 110 from FIG. 1A) or a glucose sensor or monitor (e.g., 150 from FIG. 1A). In some cases, the communications subsystem 440 can include a near field communications (NFC) chip. In some cases, the communications subsystem 440 can include a BLUETOOTH® Low Energy (BLE) chip. In some cases, the communications subsystem 440 can include an optical communication device, an infrared communication device, a wireless communication device (such as an antenna), and/or chipset (such as a BLUETOOTH® device (e.g., BLUETOOTH® Low Energy, Classic BLUETOOTH®, etc.), a Near-field communication (NFC) device, an 802.6 device (e.g., Metropolitan Area Network (MAN), a ZIGBEE® device, etc.), a WiFi device, a WIMAX® device, cellular communication facilities, etc.), and/or the like. In these and other cases, the communications subsystem 440 can exchange data with a network and/or any other device or system described in the present disclosure. The pen cap 400 includes a power source 450, which may be a rechargeable or non-rechargeable battery. The processing system can determine a pen type from data from a pen type detector 490. The processing system can also determine a position of a plunger within an insulin delivery pen using one or more optical or position sensors and/or micro-switches, such as micro-switch 480, optical sensor(s) 470, and position sensor(s) 460. FIGS. 5A and 5B illustrate the arrangement of a position sensor 460, micro-switch 480, and optical sensor 470 within a pen cap 400. The optical sensor 470 can include a light 471 and photoreceptor 472 positioned on opposite sides of an insulin delivery pen so that light passes through the insulin vial 163 and received by the photoreceptor 472 until the plunger 164 of the insulin pen 160 passes by the optical sensor 470. The tip of insulin pen 160 is received by a slider 462 that slides within the pen to trigger a micro-switch 480 having trigger 482 to tell the pen cap to use optical sensor 470 to identify when the plunger 164 passes the optical sensor 470. Data from position sensor 460, which includes spring 464, slider 462, and proximity sensor 466 to determine the distance that the insulin pen in inserted into the pen cap when the plunger passes the optical sensor 470 and thus determine an amount of insulin remaining in insulin vial 163. Data from prior use of the pen cap 400 can then be used to estimate an amount of insulin delivered to the patient. More detail about how this dose capture technique can be used is disclosed in PCT Publication WO 2017/009724 A1, which is hereby incorporated by reference in its entirety.


Exemplary Use of Dose Capture Device/System



FIG. 6A is a flow chart depicting how a user may decide, when eating, to dose insulin using methods, systems, and devices provided herein. As show, process 600 starts with the user deciding to eat something (or deciding to bolus for food already eaten) in step 610, followed by the user retrieving a pen injector in step 620. After retrieving a pen injector, the user may decide to announce a meal in step 640 and/or retrieve glucose data in step 630, which can occur in either order. After announcing a meal and/or retrieving glucose data, the user can view a dosage recommendation, which might appear on a pen cap or may appear on a remote user interface device, in step 650. After viewing the recommendation, the user can then decide how much insulin to deliver and deliver the insulin in step 660.



FIG. 6B depicts an exemplary user interface displays for a pen cap for the user when the user is following process 600. As shown, user screen 611 can indicate that the system is active and display data about a most recent dose 612, such as the type, amount, and time of day, and/or an IOB value 613. If a user obtains a blood glucose value in step 630 that indicates a hypoglycemic condition, user screen 631 can indicate that the user should consume carbohydrates, and may continue to display information about a recent dosage and/or an estimated IOB. If a user obtains a blood glucose value in step 630 that indicates a hyperglycemic condition, user screen 636 can indicate that the user should dose insulin and provide a recommended dosage, and may continue to display information about a recent dosage and/or an estimated IOB. In some cases, the recommended dosage may indicate an amount that a user should add to a dosage that they would otherwise take for a meal. If a user then enters a meal announcement in step 640, user screen 641 can appear and indicate a recommended insulin dosage to account for a meal and the current EGV. User screen 671, however, may appear at any time when the pen cap detects that something has gone wrong or otherwise requires the user's attention. In some cases, pressing buttons on a pen cap can cause the user screen on the pen cap to display more information and/or the user screen 671 can direct the user to troubleshoot issues with the system on a remote user interface device, such as remote user interface device 110 in FIG. 1A.


When a user administers insulin in step 660, the amount of insulin administered may differ from a recommended dosage and/or the recommendation may simply be that the user adjust their mental model of how much to administer for a meal, for example if the user does not make a meal announcement and doses insulin based on user screen 636. As shown in user screen 636, the dosage recommendation may be indicated in brackets to indicate an amount of insulin that should be used to correct for an elevated blood glucose level, and thus the user can add that to the amount of insulin that the user would ordinarily administer for a meal. Accordingly, methods, systems, and devices provided herein can infer the amount of carbohydrates eaten for a meal in the user's mental model based on an amount of insulin delivered by the user. For example, if a user retrieves an EGV from a glucose sensor or monitor in step 630 and sees a recommendation to take 3 units of Humalog in addition to what they would normally take, and then doses 10 units of Humalog, then the methods, systems, and devices provided herein can infer that the user ate a meal and estimate the size of the meal based on the bolus size. The estimated meal size can then be used by the system to further personalize meal announcement buttons (e.g., buttons 142-144, 221-223, and 321-323) and user-specific dosage parameters. Additionally, in some cases a user will announce a meal, but administer an amount of insulin that differs from the amount recommended, in which case methods, systems, and devices provided herein can either ignore the postprandial data for that administration for personalizing the meal announcement buttons (e.g., buttons 142-144, 221-223, and 321-323), but perhaps use the postprandial data for updating user-specific dosage parameters. For example, if a user is about to eat a meal that is between the user's mental model for a medium sized meal and the user's mental model for a large meal, the user might retrieve an EGV (e.g., in step 630) and look at a screen similar to user screen 636 to find out the amount for the correction dosage, and then announce a meal (e.g., in step 640) as a medium meal to see a screen similar to user screen 641 and then announce a meal again (e.g., conduct step 640 again) as a large meal to see a different recommendation, and then the user might deliver an amount of insulin between the two recommendations. Methods, systems, and devices provided herein can use data from a dose capture technique to estimate an amount of insulin actually delivered and use that insulin delivery data to determine an estimated size of each meal, regardless of whether the user announces the meal or follows the recommendation. Additionally, variations from the recommendations and postprandial glucose data can be used to determine adjustments to a number of carbohydrates represented by each meal announcement button e.g., buttons 142-144, 221-223, and 321-323) so that they match the user's mental model, as discussed above.


In many cases, a user will use their own mental model for administering boluses of insulin for meals and only use the system to determine a correction dose after obtaining an EGV (e.g., in step 630) and viewing a screen similar to user screens 631 or 636, which can in some cases indicate a correction dose only or might display two recommendations, (a) an amount to dose or suggestion to eat if they user is only seeking to correct a hyperglycemic or hypoglycemic condition and (b) a change to how much the user would typically dose if the user is eating. In some cases, the calculations can use different equations based on reducing a risk of a hypoglycemic condition. In some cases, a calculation for an amount to change the user's typical dose of insulin if the user is eating can incorporate adjustments based on detected patterns of the user over or under dosing insulin for meals in order to adjust for detected mismatches between the user's mental model and the PWD's physiology and food consumption patterns.



FIGS. 10A and 10B depict exemplary systems for how a user can retrieve blood glucose values from a glucose sensor that can communicate using near field communications by swiping a pen cap 1005 near the glucose sensor 50, optionally with swiping motion 1015. The cap can include a near field communication chip 1182. After swiping, display 1010 can appear on the pen cap 1005.


Wireless Communications and the Pairing Process


Referring back to FIG. 1A, systems provided herein can include one, two, or more pen caps 182 and 184 (or alternatively pen caps 200 and 300 in FIGS. 2A-3B), a remote user interface device 110 (e.g., a smartphone), and a glucose sensor or monitor 150 (e.g., a flash glucose monitor, a continuous glucose monitor, a blood glucose meter), which can all be in wireless communication with each other. In some cases, the glucose sensor or monitor 150 can be a flash glucose monitor adapted to communicate with the pen caps 182 or 184 via near field communication. In some cases, the glucose sensor or monitor 150 can be a continuous glucose monitor adapted to communicate with the pen caps 182 or 184 via radio signals, such as radio signals using BlUETOOTH® Low Energy protocols. Additionally or alternatively, such communication may occur over NFC, WiFi, ZIGBEE®, Classic BLUETOOTH®, or any other communication protocol, device, or technique. In some cases, a flash glucose monitor or a continuous glucose monitor can require a pairing process in order to communicate with other devices and/or can require a warm up period before it is ready to be used. For example, a broadcasting device (which may be either (1) the flash glucose monitor/continuous glucose monitor, glucose sensor or monitor 150 or (2) the pen caps 182 or 184 or other processing device in accordance with the present disclosure) may broadcast a pairing signal that is received by the other device, after which a series of data exchanges or handshakes may occur to establish a secure communication session between the two devices. In some cases, such a pairing procedure may be facilitated by invoking one or more of the buttons of the pen caps 182 or 184. Additionally or alternatively, the pairing procedure may be invoked using a user interface device paired or otherwise coupled with one or both of the glucose sensor or monitor 150 or the pen caps 182 or 184.



FIG. 7 illustrates an exemplary process 700 of starting the use of a system, such as the system depicted in FIG. 1A. In user screen 711, a pen cap can include a welcome screen including a connection indicator 712 that indicates that it has not been paired. Connection indicator 712 can include segments that indicate steps that must be completed before the system can be used. In some cases, a screen can be on a remote user interface device (e.g., remote user interface device 110 from FIG. 1A) indicating how the user should pair the pen cap to the remote user interface device. In step 720, the user can receive instructions to pair a remote user interface device (e.g., a smartphone) with the pen cap on the remote user interface device or the pen cap. After the successful pairing of the remote user interface device with the pen cap, screen 721 can appear to indicate the successful pairing with a remote user interface device. Subsequently, in step 730, instructions for connecting the pen cap and/or the remote user interface to a glucose sensor or monitor 150 can appear on the pen cap or the remote user interface. In some cases, the glucose sensor or monitor 150 can be a flash glucose monitor using near field communications, and methods devices, and systems provided here can instruct the user to create a near field communication link between the glucose sensor or monitor 150 and the remote user interface device and/or with the pen cap 182 or 184 to establish a communication link. In screen 731, the pen cap user screen can indicate that a sensor or monitor is warming up, possibly with a countdown clock. In screen 736, the pen cap user screen can indicate that the glucose sensor or monitor 150 is ready for use (after the warm up period has completed). Screen 741 can also appear at any time during the use of the system or during the pairing process to indicate that the pairing has failed, and then return the user to step 720 or 730 to fix the pairing issue. For example, glucose sensors and monitors can have a use life (e.g., 3 days, 7 days, 10 days, 14 days) and require replacement after the use life, so screen 741 may appear after the glucose sensor or monitor has expired, and the user can view instruction for replacing the sensor or monitor and connecting the system to that new glucose sensor or monitor in a step 730. Also, if there is a problem in communicating to a remote user interface device, a screen 741 can appear and bring the user back to step 720 to connect a new remote user interface device or to reconnect the remote user interface device.


Passive and Active Information Gathering


Methods, devices, and systems provided herein can be adapted to gather information about insulin usage and user eating patterns passively without requiring the user to perform extra steps, but be available to help a user determine appropriate actions when called upon by the user. As such, methods, systems, and devices provided here can use dose capture technology in or attached to insulin pens to estimate amounts of insulin delivered to the person with diabetes (PWD). Additionally, estimated blood glucose values (EGVs) can be pushed or pulled to the pen caps and/or to the remote user interface device though wireless communications as discussed above, and be available to the user to help the user make insulin delivery decisions. In some cases, the glucose sensor or monitor 150 can be a flash glucose monitor that requires user interaction to retrieve an EGV. In some cases, a system including a flash glucose monitor can receive both a current EGV and past EGVs from an interrogation of the flash glucose monitor, which can be used by methods, devices, and systems provided herein to make therapy recommendations and to update user-specific dosage parameters.


In some cases, methods, devices, and systems can include user prompts to request information from the user or to request that the user obtain an EGV, based on risks to the user and/or to obtain data. For example, as discussed above, postprandial data can be used to update the meal announcement buttons. Additionally, postprandial data can be used to update other user-specific dosage parameters. Moreover, after a meal, a user is at an elevated risk of having a hyperglycemic or hypoglycemic condition. Accordingly, in some cases, methods, systems, and devices provided herein can request a user obtain an EGV. For example, in FIG. 8A, a remote user interface device 110 can include a notice 810 displayed at 90 minutes after the administration of a bolus dose of insulin in order to encourage a user to scan a flash glucose monitor. Alternatively, notice 810 can ask the user to obtain blood glucose data from any other suitable glucose monitor or sensor (e.g., from a blood glucose meter requiring a finger stick, etc.) Alternatively, notice 810 can appear on a pen cap or a smart insulin pen. By obtaining the postprandial blood glucose data, methods, systems, and devices provided here can (a) determine whether correction doses may be prudent and/or (b) determine how to personalize meal announcement buttons.


Methods, devices, and systems provided herein can also seek feedback from a user regarding the user's mental model, especially if a user fails to announce a meal size. For example, in some cases, a user determining a dosage of quick-acting insulin may follow the steps shown in FIG. 6B, but stop short of announcing a meal, but instead just bolus for a meal after seeing a suggested correction dose in user screen 636. As discussed above, methods, systems, and devices provided herein can estimate a number of carbohydrates for a meal based on a difference between a recommended correction dosage and an actual dosage. In some cases, methods, devices, and systems provided herein can seek confirmation about an estimated number of carbohydrates from the user when the user accesses a remote user interface. For example, FIG. 8B depicts a message 820 that might appear on a remote user interface device 110 asking the user to confirm by selecting YES 821 or deny by selecting NO 822 whether the PWD ate a particularly sized meal. In some cases, message 820 can appear after blood glucose data is retrieved. In some cases, message 820 can use multiple blood glucose values to determine the likely timing of the meal and the likely size of the meal, which can differ from an amount of carbohydrates inferred based on the insulin size. Additionally or alternatively, methods, systems, and devices of the present disclosure may continue with analysis and/or data collection with an estimated meal size of the PWD even without input from the PWD regarding the size of the meal or even whether or not the PWD consumed a meal. In some cases, a difference between an estimated meal size based on postprandial blood glucose values and insulin delivery data and an estimated meal size based on insulin delivery data alone can indicate a mismatch between the user's mental model and the PWD's physiology and food consumption. In some cases, message 820 can be passive (i.e., without an audible alert), but be available for a user to answer when the user looks at the remote user interface device or opens a mobile app for the system on the remote user interface device. In some cases, message 820 can provide insights showing the user that the methods, systems, and devices understand the user's usage patterns in order to build the user's trust in the devices and systems. In some cases, a user may select button 823 to provide additional details about the bolus. Data received from the user after a meal can then be used to make updates to the meal announcement buttons 142-144, 221-223, 321-323.


Calculating and Updating Recommendations, User-Specific Dosage Parameters, and Active Insulin


Methods, devices, and systems provided herein can use any suitable technique for making recommendations, for updating user-specific dosage parameters (e.g., the person's ISF, CR, Total Daily LAI dosage, etc.), and for estimating amounts of unacted insulin (e.g., for calculating IOB). In some cases, the user-specific dosage parameters can vary depending on the time of day. In some cases, the user-specific dosage parameters can be determined using a fixed relationship between the user-specific dosage parameters. For example, in some cases such as a user having Type 1 Diabetes, a fixed relationship between Total Daily LAI and the PWD's carbohydrate-to-insulin ratio and the PWD's Insulin Sensitivity Factor can be based on fixed mathematical relationships. In some cases, the relationships may be determined by one of the plotted lines 915, 925, 935, 945, 955, 965, 975, or 985 shown in FIGS. 9A and 9B, or any plotted line between lines 915 and 945 and between lines 955 and 985. By having a fixed mathematical relationship between Total Daily LAI and ISF and CR, methods, systems, and devices provided herein can update CR and ISF as a PWD's response to insulin changes over time.


Methods, systems, and devices, can, in some cases, make recommendations to the user to adjust dosages of LAI based on fasting blood glucose readings (e.g., blood glucose readings taken in the morning before the PWD has eaten). In some cases, methods, devices, and systems provided herein can increase by a set number of units (e.g., 0.5 units) based on fasting blood glucose readings being above a threshold and decrease the recommended dosage of LAI based on fasting blood glucose readings being below a different lower threshold. In some cases, methods, devices, and systems can provide recommendations regarding a dosage of LAI and quick-acting insulin (QAI) for if the user fails to deliver the LAI at an appropriate time.


Methods, devices, and systems provided herein can calculate a recommended correction bolus by subtracting a target blood glucose value from the EGV and dividing that number by the Insulin Sensitivity Factor (ISF) and then subtracting the IOB. Methods, devices, and systems provided herein can also calculate a recommended bolus for food consumption by dividing a number of carbohydrates associated with a food announcement button by a carbohydrate-to-insulin ratio (CR) stored for the PWD. Conversely, if a PWD delivers a bolus of insulin after calculating a correction bolus without entering a meal and that bolus differs from the recommended correction bolus, methods, systems, and devices provided herein can calculate an amount of inferred carbohydrates for the meal by subtracting the recommended correction bolus from the amount of insulin delivered and multiplying that number by a CR stored for the user. In other words, Inferred Carbs=(Bolus of Insulin delivered−Recommended Correction Bolus)*CR. Methods, systems, and devices provided herein can then use the calculated inferred carbs in calculating predicted blood glucose levels, which may be used to issue alarms or alerts (e.g., predictive hypoglycemic or predictive hyperglycemic alarms or alerts) to the PWD. In some cases, a Recommended Correction Bolus may be negative. In some cases, devices, systems, and methods provided herein can calculate an amount of inferred carbs by multiplying the bolus by the CR when the user does not input or retrieve an EGV and/or does not have the system calculate a recommended correction bolus. By having methods, systems, and devices infer a number of carbohydrates, methods, devices, and systems provided herein can match the user's mental model without requiring the user to enter data.


Systems for the Treatment of Type 2 Diabetes


In some cases, methods, systems, and devices provided herein can be used to treat a person with type 2 diabetes (PWT2D) and to personalize insulin therapy for the treatment of Type 2 Diabetes (T2D). For example, the system shown in FIG. 1A can be used for the treatment of a PWT2D.


Type 2 Diabetes is often treated by slowly adding treatments. Initially, a PWT2D may be advised to control their diet and to exercise in order to prevent high blood glucose levels, which could be reviewed by logging blood glucose readings taken with a BGM. If diet and exercise is insufficient to achieve glycemic control, which may be defined by an HBA1C value of less than 7% and fasting/pre-meal blood glucose readings of less than 110 mg/dL (but may be personalized based on a number of factors), then the PWT2D may begin treatment of various drugs like GLP-1 RA or SGLT-2i or DPP-4i, which are designed to lower blood glucose levels. If those drugs do not achieve appropriate glycemic control, then the PWT2D may start insulin therapy using one or two injections of LAI, which or without the use of other drugs. Systems, devices, and methods provided herein can be used to assist PWT2Ds with the creating of a data log of blood glucose readings, documenting meals, and reminders of when to take post-meal blood glucose readings even if the PWT2D is not on insulin therapy.


If the PWT2D is taking LAI but not QAI for meals, methods and systems provided herein can be used to make adjustments to the LAI injections in addition to documenting BGM data and meals and issuing reminders. When starting systems and methods provided herein, the user and/or provider of healthcare services may set the initial amounts of LAI based on the PWT2D's previous LAI therapy. If the PWT2D is starting LAI therapy for the first time, the total units of LAI per day may be set at about 0.2 U/kg, or any amount between 0.1 and 0.3 U/kg, when the PWT2D starts the system. For example, if a PWT2D has an A1C of less than 8%, a provider of healthcare may typically set the total LAI therapy at somewhere between 0.1 and 0.2 U/kg. If a PWT2D has an A1C of greater than 8%, a provider of healthcare may typically set the total LAI therapy at somewhere between 0.2 and 0.3 U/kg. For example, a PWT2D weighing 100 kg and having an A1C of 8% might have a provider of healthcare set a total daily dose of LAI at 20 Units (e.g., 10 Units at 8 AM and 10 Units at 8 PM). In some cases, mobile application 10 can include an interface for the PWT2D or their provider of healthcare to enter an initial LAI therapy, which could be updated or adjusted later (both by the algorithm provided below or manually). In some cases, LAI therapy could be initially set and/or updated by a provider of healthcare in a remote web interface that connects to the mobile application through the cloud. In some cases, methods and systems provided herein may require that a qualified healthcare professional enter or confirm the initial LAI therapy.


Methods, devices, and systems provided herein can use and adjust the LAI therapy by tracking blood glucose data and LAI injections. In some cases, the LAI can be upwardly adjusted if an average fasting blood glucose reading for a period of time (e.g., 1 day, 2 days, 3 days, 5 days, 7 days, or more) exceeds a threshold. In some cases, the amount of the adjustment can depend on how much the average fasting blood glucose value exceeds a threshold. For example, in some cases a 3 day average fasting blood glucose value of between 110 and 140 mg/dL would result in an increase of 1 unit LAI per day, a 3 day average fasting blood glucose value of between 140 and 180 mg/dL would result in an increase of LAI by 10%, and a 3 day average fasting blood glucose value of at least 180 mg/dL would result in an increase of LAI by 20%. In some cases, the increase in percentage of LAI can be linearly proportional to the 2 or 3 day average over 110 mg/dL.


In some cases, the LAI can be downwardly adjusted if any blood glucose reading is below a threshold value, which could be hypoglycemia or indicate a risk for hypoglycemia. The decrease can be proportional to the low blood glucose reading. In some cases, if a blood glucose reading is between 40 and 70 mg/dL, the LAI would be decreased by between 10-20%, and a blood glucose reading of less than 40 mg/dL would result in a decrease of between 20-40%. In some cases, methods and systems provided here would decrease LAI 10% for a reading of about 70 mg/dL, decrease it by 20% for a reading of about 40 mg/dL, and decrease it by 40% for a reading of about 30 mg/dL or less.


Typically, if LAI therapy is achieving glycemic control, the system should not produce contradictory upward and downward adjustments. Moreover, glycemic control should result in the absence of hypoglycemia, prevent fasting and pre-meal blood glucose readings of greater than 110 mg/dL, and an A1C of less than 7%. If methods and systems fail to achieve glycemic control after a sufficient period of time (e.g., 1 month, 2 months, etc.), which can be preset or set by a provider of healthcare, the system can send a message to the provider of healthcare to indicate that additional therapy might be considered, which may include drugs like GLP-1 RA or SGLT-2i or DPP-4i or the use of both LAI and QAI therapy. If additional drugs other that QAI are added to the therapy, the system may continue to adjust LAI as described above and determine if glycemic control is achieved after a sufficient period of time (e.g., 1 month, 2 months, etc.).


If a PWT2D switches from LAI therapy alone to therapy using both LAI and QAI, a provider of healthcare can either switch to QAI for only some meals or for all meals. For example, in some cases a provider of healthcare may reduce LAI by 10% or 5 units and set a prandial QAI bolus for the largest meal at that 10% value or the value of 5 units, potentially adding prandial QAI boluses for additional meals if that fails to achieve glycemic control. In some cases, a provider of healthcare may decide to reduce LAI by 50% and set prandial QAI boluses at values to equal the reduction in LAI, perhaps estimating different amounts for different meals. Regardless of the amounts of LAI and prandial QAI boluses and times set by the provider of healthcare, methods and systems provided herein can make adjustments to both LAI and QAI injections based on blood glucose readings. The LAI total units per day could be decreased or increased using the same criteria discussed above for any fasting blood glucose reading. Each prandial QAI bolus can be adjusted by increasing it if a running average blood glucose reading after that meal is above a high threshold and decreasing if a post-meal blood glucose reading is below a low threshold. For example, if a post-meal blood glucose reading 2 hours after a meal is between 70 and 40 mg/dL, the prandial QAI bolus for that meal would be reduced by between 10 and 20%, and it would be reduced by between 20 and 40% if it is below 40 mg/dL. Post-meal blood glucose readings above 140 mg/dL could, for example, result in the system increasing the prandial QAI bolus for that meal by 10% or between 1-2 units of QAI for that meal. Accordingly, the systems and methods presented herein can personalize the size of prandial QAI meal boluses, which may be due to a PWT2D's typical meal size or variations in insulin sensitivity and carbohydrate-to-insulin ratios during the day. Systems provided herein could also issue notices to users if the prandial QAI boluses are producing highly variable post-meal blood glucose readings, indicating to the PWT2D that the meal sizes should remain approximately constant.


Systems, devices, and methods provided herein can also flag unusual circumstances for the user or the provider of healthcare and suggest additional tasks. For example, in some cases, a user may have a post-dinner blood glucose reading of 130 mg/dL, but wake up with a fasting blood glucose reading of greater than 160 mg/dL, which may indicate that the PWT2D may be experience a nighttime low followed by a rebound in blood glucose levels due to a biological response (e.g., the release of glucagon from the liver), thus the system may suggest an occasional additional blood glucose reading at night. A nighttime low may indicate a need to adjust the dinner QAI bolus or the units of LAI. In some cases, methods and systems provided herein may have data regarding a next appointment with a provider of healthcare and ask the PWT2D to take additional blood glucose measurements for a few days leading up to the appointment.


System-Based Inferences


In some cases, methods, devices or systems of the present disclosure may infer certain information by observing and/or analyzing data gathered in accordance with the present disclosure. For example, inferences may be made regarding whether or not a meal was consumed, a size of a meal consumed, whether or not a bolus of insulin was received, and/or a size of a bolus of insulin received.


In some cases, methods, devices or systems of the present disclosure may analyze historic blood glucose readings and note points when blood glucose levels rise, particularly around meal times. By observing rising blood glucose levels, an inference may be made regarding the consumption of a meal. Additionally or alternatively, using user-specific parameters (e.g., carbohydrate-to-insulin ratio (CR), insulin sensitivity factor (ISF), insulin-on-board (IOB), etc.) and/or historic data, a size of a meal may be inferred based on the amount of change in blood glucose levels and data gathered regarding meal sizes for the PWD. For example, if a known amount of insulin is repeatedly given for a PWD as a bolus for a meal and a known response is expected for an expected meal size, variations in that response may convey variations in the size of the meal.


In some cases, methods, devices or systems of the present disclosure may analyze historic blood glucose readings and note points when blood glucose levels decrease. For example, an inference may be made whether or not a user has received a bolus of insulin based on a decrease in blood glucose level based on an expected bolus associated with a meal. For example, an initial increase in blood glucose level around a meal time followed by a decrease in blood glucose level may indicate that a user did, in fact, receive a bolus for a meal. Additionally or alternatively, using user-specific parameters and/or historical data, a size of a bolus may be estimated. For example, if a meal size is known (or estimated) and a typical response is known (or expected) for a PWD, a decrease in blood glucose level may permit methods, devices or systems of the present disclosure to infer a bolus size. In some cases, methods, devices or systems of the present disclosure may use inferences to act as a security check to verify that a PWD received a bolus in association with a meal. For example, a PWD may use an insulin pen for boluses that is not in communication with other components of a system or device of the present disclosure, and such approaches may verify that a bolus was given for a meal.


In some cases, expected variations in blood glucose levels may incorporate the overlap of expected blood glucose levels due to LAI, QAI, and consumed carbohydrates. Such data may be inferred, read from one or more sensors or devices, or input by a user or PWD.


The embodiments described herein may include the use of a special-purpose or general-purpose computer including various computer hardware or software modules, as discussed in greater detail below.


Embodiments described herein may be implemented using computer-readable media for carrying or having computer-executable instructions or data structures stored thereon. Such computer-readable media may be any available media that may be accessed by a general-purpose or special-purpose computer. By way of example, and not limitation, such computer-readable media may include non-transitory computer-readable storage media including Random Access Memory (RAM), Read-Only Memory (ROM), Electrically Erasable Programmable Read-Only Memory (EEPROM), Compact Disc Read-Only Memory (CD-ROM) or other optical disk storage, magnetic disk storage or other magnetic storage devices, flash memory devices (e.g., solid state memory devices), or any other storage medium which may be used to carry or store desired program code in the form of computer-executable instructions or data structures and which may be accessed by a general-purpose or special-purpose computer. Combinations of the above may also be included within the scope of computer-readable media.


Computer-executable instructions comprise, for example, instructions and data which cause a general-purpose computer, special-purpose computer, or special-purpose processing device (e.g., one or more processors) to perform a certain function or group of functions. Although the subject matter has been described in language specific to structural features and/or methodological acts, it is to be understood that the subject matter defined in the appended claims is not necessarily limited to the specific features or acts described above. Rather, the specific features and acts described above are disclosed as example forms of implementing the claims.


Any ranges expressed herein (including in the claims) are considered to be given their broadest possible interpretation. For example, unless explicitly mentioned otherwise, ranges are to include their end points (e.g., a range of “between X and Y” would include X and Y). Additionally, ranges described using the terms “approximately” or “about” are to be understood to be given their broadest meaning consistent with the understanding of those skilled in the art. Additionally, the term approximately includes anything within 10%, or 5%, or within manufacturing or typical tolerances.


All examples and conditional language recited herein are intended for pedagogical objects to aid the reader in understanding the disclosure and the concepts contributed by the inventor to furthering the art, and are to be construed as being without limitation to such specifically recited examples and conditions. Although embodiments of the present disclosure have been described in detail, it should be understood that the various changes, substitutions, and alterations could be made hereto without departing from the spirit and scope of the disclosure.

Claims
  • 1. An insulin delivery system comprising: an insulin delivery pen;a glucose monitor or sensor;a cap for the insulin delivery pen, the cap comprising: a memory to store one or more user-specific dosage parameters;a user interface comprises a plurality of user-selectable icons, each user-selectable icon representing multiple meal characteristics, each meal characteristic of the multiple meal characteristics of a single user-selectable icon being associated with a time of day; anda processor in communication with the memory and adapted to receive blood glucose data from the glucose monitor or sensor, the processor being adapted to: responsive to the received blood glucose data, present a dosage recommendation with the plurality of user-selectable icons;responsive to a selection of a user-selectable icon of the plurality of user-selectable icons, update the presented dosage recommendation to account for the meal characteristics associated with the selected user-selectable icon; andresponsive to a determination that a dosage was administered above or below the updated dosage recommendation, adjust the meal characteristic associated with the current time of day of the selected user-selectable icon.
  • 2. The insulin delivery system of claim 1, wherein the glucose monitor or sensor is a flash glucose monitor comprising a flash near field communication circuit, wherein the cap further comprises a system near field communication circuit in communication with the processor, wherein the processor is adapted to receive the blood glucose data via near field communications (NFC) when the system near field communication circuit and the flash near field communication circuit are brought within an NFC communication distance.
  • 3. The insulin delivery system of claim 1, wherein the multiple meal characteristics each initially represent an amount of carbohydrates in 5 gram or 10 gram increments.
  • 4. The insulin delivery system of claim 3, wherein the amount of carbohydrates initially represented by each user-selectable icon of the plurality of user-selectable icons is determined based on an insulin Sensitivity Factor (ISF), a Carb Ratio (CR), a body weight, an age, a total daily basal (TDB) rate, a daily dosage of Long-Acting Insulin, a weight averaged total daily dosage (TDD) of insulin and/or a combination thereof of a person with diabetes (PWD).
  • 5. The insulin delivery system of claim 1, wherein the system is further adapted to update each of the multiple meal characteristics based on postprandial blood glucose data.
  • 6. The insulin delivery system of claim 5, wherein the system comprises a flash glucose monitor comprising a flash near field communication circuit, wherein the system further comprises one or more system near field communication circuits in communication with the processor, wherein the processor is adapted to receive the postprandial blood glucose data via near field communications (NFC) when the one or more system near field communication circuits and the flash near field communication circuit are brought within an NFC communication distance, wherein the processor is adapted to send a prompt to a user to retrieve the postprandial blood glucose data by bringing one of the one or more system near field communication circuits into close proximity to the flash glucose monitor at a predetermined time after insulin is delivered to the user.
  • 7. The insulin delivery system of claim 1, wherein the system is adapted to determine an initial setting for each of the multiple meal characteristics of each user-selectable icon based on a user-entered total daily basal dose.
  • 8. The insulin delivery system of claim 1, wherein the system further comprises a mobile application in wireless communication with the cap.
  • 9. A cap for an insulin delivery pen, the cap comprising: a memory to store one or more user-specific dosage parameters;a user interface comprises a plurality of user-selectable icons, each user-selectable icon representing multiple meal characteristics, each meal characteristic of the multiple meal characteristics of a single user-selectable icon being associated with a time of day; anda processor in communication with the memory and adapted to receive blood glucose data from a glucose monitor or sensor, the processor being adapted to: responsive to the received blood glucose data, present a dosage recommendation with the plurality of user-selectable icons;responsive to a selection of a user-selectable icon of the plurality of user-selectable icons, update the presented dosage recommendation to account for the meal characteristics associated with the selected user-selectable icon; andresponsive to a determination that a dosage was administered above or below the updated dosage recommendation, adjust the meal characteristic associated with the current time of day of the selected user-selectable icon.
  • 10. The cap of claim 9, further comprising a flash near field communication circuit for receiving the blood glucose data from the glucose monitor or sensor.
  • 11. The cap of claim 9, wherein the user interface is adapted to display a blood glucose value received from a glucose monitor or sensor.
  • 12. The cap of claim 11, wherein the cap further comprises one or more system near field communication circuits in communication with the processor, wherein the processor is adapted to receive blood glucose data via near field communications (NFC) with the glucose monitor or sensor when the one or more system near field communication circuits is brought within an NFC communication distance of the glucose monitor or sensor.
  • 13. The cap of claim 9, wherein the cap is adapted to determine an initial setting for each of the multiple meal characteristics of each user-selectable icon based on a user-entered total daily basal dose.
  • 14. The cap of claim 9, wherein the cap is in wireless communication with a mobile application.
  • 15. An insulin delivery system comprising: an insulin delivery pen;a blood glucose monitor or sensor;a cap for the insulin delivery pen, the cap comprising: a user interface comprising a plurality of user-selectable icons or buttons, each user-selectable icon or button representing multiple meal characteristics, each meal characteristic of the multiple meal characteristics of a single user-selectable icon or button being associated with a time of day;a memory to store one or more user-specific dosage parameters; anda processor in communication with the memory and adapted to receive blood glucose data from the blood glucose monitor or sensor, the processor being adapted to: responsive to the received blood glucose data, present with the plurality of user-selectable icons or buttons a dosage recommendation;responsive to a selection of a user-selectable icon or button of the plurality of user-selectable icons or buttons, update the presented dosage recommendation to account for the meal characteristics associated with the selected user-selectable icon; andresponsive to a determination that a dosage was administered above or below the updated dosage recommendation, adjust the meal characteristic associated with the current time of day of the selected user-selectable icon or button.
  • 16. The insulin delivery system of claim 15, wherein the blood glucose monitor or sensor is a flash glucose monitor comprising a flash near field communication circuit, wherein the cap further comprises a system near field communication circuit in communication with the processor, wherein the processor is adapted to receive the blood glucose data via near field communications (NFC) when the system near field communication circuit and the flash near field communication circuit are brought within an NFC communication distance.
  • 17. The insulin delivery system of claim 15, wherein the processor is adapted to update each of the multiple meal characteristics of each user-selectable icon or button based on the blood glucose data comprising postprandial blood glucose data.
  • 18. The insulin delivery system of claim 15, wherein the processor is adapted to update each of the multiple meal characteristics of each user-selectable icon or button based on the blood glucose data after a user has selected one of the plurality of user-selectable icons or buttons.
  • 19. The insulin delivery system of claim 15, wherein the processor is adapted to determine an initial setting for each of the multiple meal characteristics of each user-selectable icon or button based on a user-entered total daily basal dose.
  • 20. The insulin delivery system of claim 15, wherein the user interface comprises a display of a pen cap for use with an insulin pen.
CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. patent application Ser. No. 15/717,805, filed Sep. 27, 2017, now U.S. Pat. No. 10,426,896, issued Oct. 1, 2019, which claims the benefit of U.S. Patent Provisional Application No. 62/400,366, filed Sep. 27, 2016, the disclosure of each of which is hereby incorporated herein in its entirety by this reference.

US Referenced Citations (753)
Number Name Date Kind
2605765 Kollsman Aug 1952 A
3886938 Szabo et al. Jun 1975 A
4077405 Haerten et al. Mar 1978 A
4231368 Becker Nov 1980 A
4265241 Portner et al. May 1981 A
4300554 Hessberg et al. Nov 1981 A
4313439 Babb et al. Feb 1982 A
4398908 Siposs Aug 1983 A
4435173 Siposs et al. Mar 1984 A
4443218 Decant et al. Apr 1984 A
4493704 Beard et al. Jan 1985 A
4529401 Leslie et al. Jul 1985 A
4681569 Coble et al. Jul 1987 A
4749109 Kamen Jun 1988 A
4838857 Strowe et al. Jun 1989 A
4850817 Nason et al. Jul 1989 A
5045064 Idriss Sep 1991 A
5088981 Howson et al. Feb 1992 A
5088990 Hivale et al. Feb 1992 A
D325781 Moller-Jensen Apr 1992 S
5190522 Wojcicki et al. Mar 1993 A
5225763 Krohn et al. Jul 1993 A
5250027 Lewis et al. Oct 1993 A
5261882 Sealfon Nov 1993 A
5314412 Rex May 1994 A
5335994 Weynant Aug 1994 A
5338157 Blomquist Aug 1994 A
5342180 Daoud Aug 1994 A
D351469 Okamoto Oct 1994 S
5389078 Zalesky et al. Feb 1995 A
5395340 Lee Mar 1995 A
5411487 Castagna May 1995 A
5545143 Fischell et al. Aug 1996 A
5551850 Williamson et al. Sep 1996 A
5554123 Herskowitz Sep 1996 A
5569186 Lord et al. Oct 1996 A
5626566 Petersen et al. May 1997 A
5637095 Nason et al. Jun 1997 A
5640954 Pfeiffer et al. Jun 1997 A
5665065 Colman et al. Sep 1997 A
5678571 Brown Oct 1997 A
5718562 Lawless et al. Feb 1998 A
D393264 Leung Apr 1998 S
5741216 Hemmingsen et al. Apr 1998 A
5766155 Hyman et al. Jun 1998 A
5772635 Dastur et al. Jun 1998 A
5816306 Giacomel Oct 1998 A
5852803 Ashby et al. Dec 1998 A
5858001 Tsals et al. Jan 1999 A
5918603 Brown Jul 1999 A
5919167 Mulhauser et al. Jul 1999 A
5925018 Ungerstedt Jul 1999 A
5928201 Poulsen et al. Jul 1999 A
5947934 Hansen et al. Sep 1999 A
5951530 Steengaard et al. Sep 1999 A
5957889 Poulsen et al. Sep 1999 A
5984894 Poulsen et al. Nov 1999 A
5984897 Petersen et al. Nov 1999 A
5997475 Bortz Dec 1999 A
6003736 Ljunggren Dec 1999 A
6010485 Buch-Rasmussen et al. Jan 2000 A
6032119 Brown et al. Feb 2000 A
6033377 Rasmussen et al. Mar 2000 A
6045537 Klitmose Apr 2000 A
D424036 Arora et al. May 2000 S
6056728 Von Schuckmann May 2000 A
6074372 Hansen Jun 2000 A
6110149 Klitgaard et al. Aug 2000 A
6156014 Petersen et al. Dec 2000 A
6171276 Lippe et al. Jan 2001 B1
6231540 Smedegaard May 2001 B1
6248067 Causey et al. Jun 2001 B1
6248090 Jensen et al. Jun 2001 B1
6248093 Moberg Jun 2001 B1
6277098 Klitmose et al. Aug 2001 B1
6302855 Lav et al. Oct 2001 B1
6302869 Klitgaard Oct 2001 B1
6354996 Drinan et al. Mar 2002 B1
6368314 Kipfer et al. Apr 2002 B1
6375638 Nason et al. Apr 2002 B2
6379339 Klitgaard et al. Apr 2002 B1
6381496 Meadows et al. Apr 2002 B1
6404098 Kayama et al. Jun 2002 B1
D460053 Choi Jul 2002 S
6427088 Bowman et al. Jul 2002 B1
D461241 Moberg et al. Aug 2002 S
D461891 Moberg Aug 2002 S
6436072 Kullas et al. Aug 2002 B1
6461331 Van Antwerp Oct 2002 B1
6474219 Klitmose et al. Nov 2002 B2
6485461 Mason et al. Nov 2002 B1
6508788 Preuthun Jan 2003 B2
6524280 Hansen et al. Feb 2003 B2
6533183 Aasmul et al. Mar 2003 B2
6537251 Klitmose Mar 2003 B2
6540672 Simonsen et al. Apr 2003 B1
6544229 Danby et al. Apr 2003 B1
6547764 Larsen et al. Apr 2003 B2
6551276 Mann et al. Apr 2003 B1
6554798 Mann et al. Apr 2003 B1
6554800 Nezhadian et al. Apr 2003 B1
6558320 Causey et al. May 2003 B1
6558351 Steil et al. May 2003 B1
6562001 Lebel et al. May 2003 B2
6562011 Buch-Rasmussen et al. May 2003 B1
6564105 Starkweather et al. May 2003 B2
6569126 Poulsen et al. May 2003 B1
6571128 Lebel et al. May 2003 B2
6577899 Lebel et al. Jun 2003 B2
6582404 Klitgaard et al. Jun 2003 B1
6585644 Lebel et al. Jul 2003 B2
6585699 Ljunggreen et al. Jul 2003 B2
6589229 Connelly et al. Jul 2003 B1
6605067 Larsen Aug 2003 B1
6613019 Munk Sep 2003 B2
6641533 Causey et al. Nov 2003 B2
6648821 Lebel et al. Nov 2003 B2
6650951 Jones et al. Nov 2003 B1
6656158 Mahoney et al. Dec 2003 B2
6656159 Flaherty Dec 2003 B2
6659948 Lebel et al. Dec 2003 B2
6659978 Kasuga et al. Dec 2003 B1
6659980 Moberg et al. Dec 2003 B2
6663602 Schmidt Dec 2003 B2
6668196 Villegas et al. Dec 2003 B1
6669669 Flaherty et al. Dec 2003 B2
6687546 Lebel et al. Feb 2004 B2
6690192 Wing Feb 2004 B1
6691043 Ribeiro, Jr. Feb 2004 B2
6692457 Flaherty Feb 2004 B2
6692472 Hansen et al. Feb 2004 B2
6694191 Starkweather et al. Feb 2004 B2
6699218 Flaherty et al. Mar 2004 B2
6702779 Connelly et al. Mar 2004 B2
6715516 Ohms et al. Apr 2004 B2
6716198 Larsen Apr 2004 B2
6723072 Flaherty et al. Apr 2004 B2
6733446 Lebel et al. May 2004 B2
6736796 Shekalim May 2004 B2
6740059 Flaherty May 2004 B2
6740072 Starkweather et al. May 2004 B2
6740075 Lebel et al. May 2004 B2
6744350 Blomquist Jun 2004 B2
6749587 Flaherty Jun 2004 B2
6752787 Causey et al. Jun 2004 B1
6758810 Lebel et al. Jul 2004 B2
6768425 Flaherty et al. Jul 2004 B2
6780156 Haueter et al. Aug 2004 B2
6786246 Ohms et al. Sep 2004 B2
6786890 Preuthun et al. Sep 2004 B2
6796970 Klitmose et al. Sep 2004 B1
6799149 Hartlaub Sep 2004 B2
6809653 Mann et al. Oct 2004 B1
6810290 Lebel et al. Oct 2004 B2
6811533 Lebel et al. Nov 2004 B2
6811534 Bowman et al. Nov 2004 B2
6813519 Lebel et al. Nov 2004 B2
6827702 Lebel et al. Dec 2004 B2
6830558 Flaherty et al. Dec 2004 B2
6852104 Blomquist Feb 2005 B2
6854620 Ramey Feb 2005 B2
6854653 Eilersen Feb 2005 B2
6855129 Jensen et al. Feb 2005 B2
6872200 Mann et al. Mar 2005 B2
6873268 Lebel et al. Mar 2005 B2
6878132 Kipfer Apr 2005 B2
6893415 Madsen et al. May 2005 B2
6899695 Herrera May 2005 B2
6899699 Enggaard May 2005 B2
6922590 Whitehurst Jul 2005 B1
6936006 Sabra Aug 2005 B2
6936029 Mann et al. Aug 2005 B2
6945961 Miller et al. Sep 2005 B2
6948918 Hansen Sep 2005 B2
6950708 Bowman et al. Sep 2005 B2
6956572 Zaleski Oct 2005 B2
6960192 Flaherty et al. Nov 2005 B1
6979326 Mann et al. Dec 2005 B2
6997911 Klitmose Feb 2006 B2
6997920 Mann et al. Feb 2006 B2
7005078 Van et al. Feb 2006 B2
7008399 Larsen et al. Mar 2006 B2
7014625 Bengtsson Mar 2006 B2
7018360 Flaherty et al. Mar 2006 B2
7025743 Mann et al. Apr 2006 B2
7029455 Flaherty Apr 2006 B2
7054836 Christensen et al. May 2006 B2
7096431 Tambata et al. Aug 2006 B2
7104972 Moller et al. Sep 2006 B2
7109878 Mann et al. Sep 2006 B2
7128727 Flaherty et al. Oct 2006 B2
7133329 Skyggebjerg et al. Nov 2006 B2
7232423 Mernoee Jun 2007 B2
D545837 Haldimann et al. Jul 2007 S
7241265 Cummings et al. Jul 2007 B2
D550227 Sato et al. Sep 2007 S
D553625 Burns et al. Oct 2007 S
D554140 Armendariz Oct 2007 S
7291107 Hellwig et al. Nov 2007 B2
7343197 Shusterman Mar 2008 B2
7454359 Rosenfeld et al. Nov 2008 B2
7479949 Jobs et al. Jan 2009 B2
D592223 Neuhaus May 2009 S
7534226 Mernoe et al. May 2009 B2
7553281 Hellwig et al. Jun 2009 B2
7555727 Hawkins et al. Jun 2009 B2
7570980 Ginsberg Aug 2009 B2
D600341 Loerwald Sep 2009 S
D603421 Ebeling et al. Nov 2009 S
D607099 Loerwald Dec 2009 S
7647237 Malave et al. Jan 2010 B2
D614587 Yodfat et al. Apr 2010 S
7695434 Malecha Apr 2010 B2
7708717 Estes et al. May 2010 B2
7717903 Estes et al. May 2010 B2
7751907 Blomquist Jul 2010 B2
D623753 Saffer et al. Sep 2010 S
7789859 Estes et al. Sep 2010 B2
D628107 Lee Nov 2010 S
7828528 Estes et al. Nov 2010 B2
7837647 Estes et al. Nov 2010 B2
7850641 Lebel et al. Dec 2010 B2
7871376 Brown Jan 2011 B2
D632699 Judy et al. Feb 2011 S
7878975 Liljeryd et al. Feb 2011 B2
7887512 Estes et al. Feb 2011 B2
7931613 Haueter et al. Apr 2011 B2
7938797 Estes May 2011 B2
D640269 Chen Jun 2011 S
7956845 Lee Jun 2011 B2
D642191 Barnett et al. Jul 2011 S
D644242 Matas Aug 2011 S
D644243 Matas Aug 2011 S
8012119 Estes et al. Sep 2011 B2
D648804 Coulter Nov 2011 S
D652426 Anzures Jan 2012 S
8132101 Buck et al. Mar 2012 B2
D656950 Shallcross et al. Apr 2012 S
8156070 Buck et al. Apr 2012 B2
D660315 Anzures May 2012 S
D661701 Brown et al. Jun 2012 S
8202249 Iio et al. Jun 2012 B2
8217946 Halpern et al. Jul 2012 B2
8219222 Blomquist Jul 2012 B2
8221345 Blomquist Jul 2012 B2
8221359 Kristensen et al. Jul 2012 B2
8231562 Buck et al. Jul 2012 B2
D665409 Gupta et al. Aug 2012 S
8237715 Buck et al. Aug 2012 B2
8250483 Blomquist Aug 2012 B2
8257652 Drucker et al. Sep 2012 B2
8257653 Drucker et al. Sep 2012 B2
8262616 Grant et al. Sep 2012 B2
8273296 Drucker et al. Sep 2012 B2
D669165 Estes et al. Oct 2012 S
D669166 Estes et al. Oct 2012 S
D669167 Estes et al. Oct 2012 S
8279226 Krieftewirth Oct 2012 B2
8310415 Mclaughlin et al. Nov 2012 B2
8337469 Eberhart et al. Dec 2012 B2
D674405 Guastella et al. Jan 2013 S
8357091 Say et al. Jan 2013 B2
8365065 Gejdos et al. Jan 2013 B2
8372005 Say et al. Feb 2013 B2
D682289 Dijulio et al. May 2013 S
D682304 Mierau et al. May 2013 S
D682305 Mierau et al. May 2013 S
8439834 Schmelzeisen-Redeker et al. May 2013 B2
D683738 Wujcik et al. Jun 2013 S
D687062 Gardner et al. Jul 2013 S
D687541 Estes et al. Aug 2013 S
8514086 Harper et al. Aug 2013 B2
D689087 Fymat Sep 2013 S
D689090 Impas et al. Sep 2013 S
D689523 Galbraith et al. Sep 2013 S
D689874 Brinda et al. Sep 2013 S
8529838 Drucker et al. Sep 2013 B2
8529839 Drucker et al. Sep 2013 B2
8529841 Drucker et al. Sep 2013 B2
D690717 Thomsen et al. Oct 2013 S
D690718 Thomsen et al. Oct 2013 S
D691258 Estes et al. Oct 2013 S
D691259 Estes et al. Oct 2013 S
D693114 Lemanski, Sr. Nov 2013 S
D693365 Gardner et al. Nov 2013 S
D694262 Jang et al. Nov 2013 S
8579815 Galley et al. Nov 2013 B2
8601005 Bousamra et al. Dec 2013 B2
8615366 Galley et al. Dec 2013 B2
D697204 Maier et al. Jan 2014 S
D697519 Thomsen et al. Jan 2014 S
8622906 Say et al. Jan 2014 B2
D698808 Funabashi et al. Feb 2014 S
D699741 Wantland et al. Feb 2014 S
8657779 Blomquist Feb 2014 B2
D701879 Foit et al. Apr 2014 S
D702258 Wantland et al. Apr 2014 S
D705261 Holz et al. May 2014 S
8719945 Birtwhistle et al. May 2014 B2
8756074 Brzustowicz Jun 2014 B2
8761940 Long et al. Jun 2014 B2
D709080 Kim Jul 2014 S
D709183 Kemlein Jul 2014 S
D709917 Faulkner et al. Jul 2014 S
8774887 Say et al. Jul 2014 B2
8816862 Harper et al. Aug 2014 B2
8839106 Lee et al. Sep 2014 B2
D714816 Varon Oct 2014 S
D715835 Montgomery et al. Oct 2014 S
D716340 Bresin et al. Oct 2014 S
D717822 Brotman et al. Nov 2014 S
D717823 Brotman et al. Nov 2014 S
D717830 Brinda et al. Nov 2014 S
D718438 Davis et al. Nov 2014 S
8895315 Batman et al. Nov 2014 B2
D719186 Kim Dec 2014 S
8929823 Mears et al. Jan 2015 B2
8961465 Blomquist Feb 2015 B2
D724616 Jou Mar 2015 S
8992464 Bashan et al. Mar 2015 B2
D727336 Allison et al. Apr 2015 S
9008803 Blomquist Apr 2015 B2
9022996 Eberhart et al. May 2015 B2
9033877 Werner et al. May 2015 B2
9041730 Johnson et al. May 2015 B2
D730929 Yu et al. Jun 2015 S
D731525 Myers Jun 2015 S
D733175 Bae Jun 2015 S
D733179 Kwon Jun 2015 S
9050409 Haueter et al. Jun 2015 B2
9056165 Steil et al. Jun 2015 B2
9072477 Say et al. Jul 2015 B2
9076107 Cameron et al. Jul 2015 B2
D736792 Brinda et al. Aug 2015 S
D737278 Shin et al. Aug 2015 S
D738907 Cabrera-Cordon et al. Sep 2015 S
D738913 Cabrera-Cordon et al. Sep 2015 S
D738914 Torres et al. Sep 2015 S
D739878 Baxley Sep 2015 S
9134823 Grant et al. Sep 2015 B2
9136939 Galley et al. Sep 2015 B2
9144204 Redmond et al. Sep 2015 B2
D741891 Gardner et al. Oct 2015 S
9159148 Boyer et al. Oct 2015 B2
9171343 Fischell Oct 2015 B1
D743435 Herold et al. Nov 2015 S
9186113 Harper et al. Nov 2015 B2
D744505 Wilberding et al. Dec 2015 S
D745050 Kwon Dec 2015 S
D745543 Kim et al. Dec 2015 S
D746314 Jung et al. Dec 2015 S
9198623 Fern et al. Dec 2015 B2
D746848 Bovet et al. Jan 2016 S
D748646 Kim et al. Feb 2016 S
D749097 Zou et al. Feb 2016 S
D750663 Mariet et al. Mar 2016 S
D751081 Kim et al. Mar 2016 S
D751090 Hu et al. Mar 2016 S
D751585 Kaufthal et al. Mar 2016 S
D751586 Kaufthal et al. Mar 2016 S
D752604 Zhang Mar 2016 S
D752736 Chandrasenan et al. Mar 2016 S
D753139 Bovet Apr 2016 S
D753177 Mierau et al. Apr 2016 S
D753685 Zimmerman et al. Apr 2016 S
D754150 Oh et al. Apr 2016 S
D754670 Park Apr 2016 S
D754685 Carlton et al. Apr 2016 S
D754689 Lee Apr 2016 S
D754713 Zhang et al. Apr 2016 S
D754714 Zhang et al. Apr 2016 S
D755206 Lee et al. May 2016 S
D755830 Chaudhri et al. May 2016 S
D757026 Lim et al. May 2016 S
D757047 Cornwell et al. May 2016 S
D758433 Lee et al. Jun 2016 S
D760752 Anzures et al. Jul 2016 S
D761843 Kim Jul 2016 S
D762234 Li et al. Jul 2016 S
D762675 Lim et al. Aug 2016 S
D763285 Chan et al. Aug 2016 S
D763860 Sunshine et al. Aug 2016 S
D763921 Dharwada et al. Aug 2016 S
D765092 Chaudhri et al. Aug 2016 S
D765710 Anzures et al. Sep 2016 S
D766257 Zhang et al. Sep 2016 S
D766424 Anderson et al. Sep 2016 S
D768144 Kim et al. Oct 2016 S
D768687 Bae et al. Oct 2016 S
D769314 Piroddi et al. Oct 2016 S
D769322 Rajeswaran et al. Oct 2016 S
D769325 Casalegno et al. Oct 2016 S
D771672 Tanabe et al. Nov 2016 S
D772241 Capano Nov 2016 S
D772924 Begin et al. Nov 2016 S
D773510 Foss et al. Dec 2016 S
D776137 Chaudhri et al. Jan 2017 S
D776253 Li Jan 2017 S
D776702 Huang et al. Jan 2017 S
D777200 Luo et al. Jan 2017 S
D777204 Lee et al. Jan 2017 S
D777735 Kim et al. Jan 2017 S
D777906 Anderson et al. Jan 2017 S
D781305 Lau Mar 2017 S
D781908 Bhandari et al. Mar 2017 S
D783652 Guan et al. Apr 2017 S
D784372 Kovchiy Apr 2017 S
D786266 Van et al. May 2017 S
D786270 Barry et al. May 2017 S
D788138 Lee et al. May 2017 S
D788140 Hemsley et al. May 2017 S
D788145 Sullivan et al. May 2017 S
D788808 Chaudhri et al. Jun 2017 S
D789419 Chaudhri et al. Jun 2017 S
D790562 Nageli et al. Jun 2017 S
D790583 Kay et al. Jun 2017 S
D791806 Brewington et al. Jul 2017 S
9707336 Dang et al. Jul 2017 B2
D794649 Niijima et al. Aug 2017 S
D795284 Miller et al. Aug 2017 S
D795294 Faulkner et al. Aug 2017 S
9717849 Mhatre et al. Aug 2017 B2
D797123 Lee et al. Sep 2017 S
D797771 Caporal et al. Sep 2017 S
D797772 Mizono et al. Sep 2017 S
D797788 Havranek, Jr. Sep 2017 S
D798318 Ferguson et al. Sep 2017 S
D798895 Kim et al. Oct 2017 S
D799536 Eder Oct 2017 S
D800757 Mullen et al. Oct 2017 S
D801519 Sabin et al. Oct 2017 S
D801990 Reissner et al. Nov 2017 S
D802607 Apodaca et al. Nov 2017 S
D803850 Chang et al. Nov 2017 S
D804505 Hoffman et al. Dec 2017 S
D804516 Dye et al. Dec 2017 S
D805541 Juliano Dec 2017 S
D806117 Springer Dec 2017 S
D806748 Van et al. Jan 2018 S
D806749 Van et al. Jan 2018 S
D806750 Van et al. Jan 2018 S
D808417 Mander et al. Jan 2018 S
D808974 Chiappone et al. Jan 2018 S
D809134 Crothall Jan 2018 S
9878097 Estes Jan 2018 B2
D809535 Park et al. Feb 2018 S
D810095 Vali et al. Feb 2018 S
D812072 Hoffman Mar 2018 S
D815665 Li et al. Apr 2018 S
D816093 Mazur et al. Apr 2018 S
9931454 Lo et al. Apr 2018 B2
D816708 Riedel et al. May 2018 S
D816709 Riedel et al. May 2018 S
D816713 Kang May 2018 S
D819065 Xie et al. May 2018 S
D819067 Behzadi et al. May 2018 S
D819646 Jow et al. Jun 2018 S
D820304 Coffman et al. Jun 2018 S
D821437 Chaudhri et al. Jun 2018 S
D822708 Ghosh Jul 2018 S
D823859 Boyd Jul 2018 S
D826969 Goyette et al. Aug 2018 S
D828375 Mok et al. Sep 2018 S
D828377 Dhide Sep 2018 S
D830385 Lepine et al. Oct 2018 S
D835658 Chan et al. Dec 2018 S
D835659 Anzures et al. Dec 2018 S
D837809 Kagatsume et al. Jan 2019 S
D839287 Hersh et al. Jan 2019 S
D839294 Mazlish et al. Jan 2019 S
10263802 Burns et al. Apr 2019 B2
D852816 Baekelandt et al. Jul 2019 S
D852817 Aoshima Jul 2019 S
D852837 Mazlish et al. Jul 2019 S
D853441 Khandelwal Jul 2019 S
D857724 Clediere et al. Aug 2019 S
D858566 Bacchus Sep 2019 S
D858567 Bacchus Sep 2019 S
10410538 Simpson Sep 2019 B2
D863343 Mazlish et al. Oct 2019 S
D864239 Hisada et al. Oct 2019 S
10426896 Desborough et al. Oct 2019 B2
D865813 Lee et al. Nov 2019 S
D866584 Burroughs et al. Nov 2019 S
D867601 Henry et al. Nov 2019 S
D870767 Villafane Dec 2019 S
D875111 Clediere Feb 2020 S
D875124 Yan Feb 2020 S
10572107 Beebe et al. Feb 2020 B1
D879118 Chen et al. Mar 2020 S
D880497 Boyd Apr 2020 S
D883319 Caro et al. May 2020 S
D884007 Uppala et al. May 2020 S
D884716 Tan et al. May 2020 S
D886850 Kim et al. Jun 2020 S
D888748 Valladares et al. Jun 2020 S
D890206 Felkins et al. Jul 2020 S
D910063 Brooks Feb 2021 S
D910654 Eder Feb 2021 S
D910669 Wuqiang Feb 2021 S
D920349 Clements et al. May 2021 S
D927527 Bragdon et al. Aug 2021 S
D931898 Demar Sep 2021 S
D937312 Ding et al. Nov 2021 S
D939570 Dye et al. Dec 2021 S
D940156 Butcher et al. Jan 2022 S
D944772 Kim Mar 2022 S
D944824 Wang et al. Mar 2022 S
20010041869 Causey et al. Nov 2001 A1
20010056262 Cabiri et al. Dec 2001 A1
20020004651 Ljunggreen et al. Jan 2002 A1
20020007154 Hansen et al. Jan 2002 A1
20020040208 Flaherty et al. Apr 2002 A1
20020091358 Klitmose Jul 2002 A1
20020126036 Flaherty et al. Sep 2002 A1
20020175931 Holtz et al. Nov 2002 A1
20020177810 Reilly et al. Nov 2002 A1
20030028089 Galley Feb 2003 A1
20030055380 Flaherty Mar 2003 A1
20030065308 Lebel et al. Apr 2003 A1
20030088238 Poulsen et al. May 2003 A1
20030167035 Flaherty et al. Sep 2003 A1
20030198558 Nason et al. Oct 2003 A1
20030199825 Flaherty Oct 2003 A1
20030216683 Shekalim Nov 2003 A1
20040010207 Flaherty et al. Jan 2004 A1
20040019325 Shekalim Jan 2004 A1
20040064088 Gorman et al. Apr 2004 A1
20040064096 Flaherty et al. Apr 2004 A1
20040078028 Flaherty et al. Apr 2004 A1
20040087894 Flaherty May 2004 A1
20040092865 Flaherty et al. May 2004 A1
20040092878 Flaherty May 2004 A1
20040093331 Garner et al. May 2004 A1
20040116866 Gorman et al. Jun 2004 A1
20040127844 Flaherty Jul 2004 A1
20040153032 Garribotto et al. Aug 2004 A1
20040153257 Munk Aug 2004 A1
20040171983 Sparks et al. Sep 2004 A1
20040176727 Shekalim Sep 2004 A1
20040204673 Flaherty Oct 2004 A1
20040220551 Flaherty et al. Nov 2004 A1
20040235446 Flaherty et al. Nov 2004 A1
20040260233 Garibotto et al. Dec 2004 A1
20050021005 Flaherty et al. Jan 2005 A1
20050022274 Campbell et al. Jan 2005 A1
20050038674 Braig et al. Feb 2005 A1
20050044500 Orimoto et al. Feb 2005 A1
20050065760 Murtfeldt et al. Mar 2005 A1
20050090808 Malave et al. Apr 2005 A1
20050090851 Devlin Apr 2005 A1
20050095063 Fathallah et al. May 2005 A1
20050114374 Juszkiewicz et al. May 2005 A1
20050160858 Mernoe Jul 2005 A1
20050171512 Flaherty Aug 2005 A1
20050182366 Vogt et al. Aug 2005 A1
20050192494 Ginsberg Sep 2005 A1
20050192561 Mernoe Sep 2005 A1
20050203461 Flaherty et al. Sep 2005 A1
20050215982 Malave et al. Sep 2005 A1
20050222645 Malave et al. Oct 2005 A1
20050234404 Vilks et al. Oct 2005 A1
20050238507 Diianni et al. Oct 2005 A1
20050245878 Mernoe et al. Nov 2005 A1
20050251097 Mernoe Nov 2005 A1
20050267402 Stewart et al. Dec 2005 A1
20050273059 Mernoe et al. Dec 2005 A1
20060041229 Garibotto et al. Feb 2006 A1
20060069382 Pedersen Mar 2006 A1
20060074381 Malave et al. Apr 2006 A1
20060095014 Ethelfeld May 2006 A1
20060135913 Ethelfeld Jun 2006 A1
20060142698 Ethelfeld Jun 2006 A1
20060151545 Imhof et al. Jul 2006 A1
20060178633 Garibotto et al. Aug 2006 A1
20060184119 Remde et al. Aug 2006 A1
20060200073 Radmer et al. Sep 2006 A1
20060206054 Shekalim Sep 2006 A1
20060247581 Pedersen et al. Nov 2006 A1
20060276771 Galley et al. Dec 2006 A1
20070073228 Mernoe et al. Mar 2007 A1
20070073235 Estes et al. Mar 2007 A1
20070073236 Mernoe et al. Mar 2007 A1
20070088271 Richards Apr 2007 A1
20070106218 Yodfat et al. May 2007 A1
20070124002 Estes et al. May 2007 A1
20070156092 Estes et al. Jul 2007 A1
20070167905 Estes et al. Jul 2007 A1
20070167912 Causey et al. Jul 2007 A1
20070171087 Shimazu et al. Jul 2007 A1
20070179444 Causey et al. Aug 2007 A1
20070213657 Jennewine et al. Sep 2007 A1
20070239116 Follman et al. Oct 2007 A1
20080051716 Stutz Feb 2008 A1
20080059158 Matsuo et al. Mar 2008 A1
20080097381 Moberg et al. Apr 2008 A1
20080119705 Patel et al. May 2008 A1
20080172026 Blomquist Jul 2008 A1
20080201325 Doniger et al. Aug 2008 A1
20080208627 Skyggebjerg Aug 2008 A1
20080220752 Forstall et al. Sep 2008 A1
20080262469 Brister et al. Oct 2008 A1
20080287755 Sass et al. Nov 2008 A1
20080287922 Panduro Nov 2008 A1
20080294094 Mhatre et al. Nov 2008 A1
20080294108 Briones et al. Nov 2008 A1
20080294109 Estes et al. Nov 2008 A1
20080294142 Patel et al. Nov 2008 A1
20080300534 Blomquist Dec 2008 A1
20080306434 Dobbles et al. Dec 2008 A1
20080319383 Byland et al. Dec 2008 A1
20090054750 Jennewine Feb 2009 A1
20090058823 Kocienda Mar 2009 A1
20090067989 Estes et al. Mar 2009 A1
20090069745 Estes et al. Mar 2009 A1
20090069746 Miller et al. Mar 2009 A1
20090069749 Miller et al. Mar 2009 A1
20090069784 Estes et al. Mar 2009 A1
20090069785 Miller et al. Mar 2009 A1
20090069787 Estes et al. Mar 2009 A1
20090089710 Wood et al. Apr 2009 A1
20090099523 Grant et al. Apr 2009 A1
20090156990 Wenger et al. Jun 2009 A1
20090164239 Hayter et al. Jun 2009 A1
20090197635 Kim et al. Aug 2009 A1
20090204421 Guimaraes Aug 2009 A1
20090253970 Bashan Oct 2009 A1
20090292247 Basso et al. Nov 2009 A1
20100016700 Sieh et al. Jan 2010 A1
20100048358 Tchao et al. Feb 2010 A1
20100118037 Sheikh et al. May 2010 A1
20100174266 Estes Jul 2010 A1
20100273610 Johnson Oct 2010 A1
20100280329 Randloev et al. Nov 2010 A1
20100286601 Yodfat et al. Nov 2010 A1
20100298765 Budiman et al. Nov 2010 A1
20100305965 Benjamin et al. Dec 2010 A1
20100315359 Seong et al. Dec 2010 A1
20110009846 Istoc et al. Jan 2011 A1
20110040247 Mandro et al. Feb 2011 A1
20110092788 Long et al. Apr 2011 A1
20110152657 Bielawa et al. Jun 2011 A1
20110160555 Reifman et al. Jun 2011 A1
20110201911 Johnson et al. Aug 2011 A1
20110238520 Selley Sep 2011 A1
20110273388 Joo et al. Nov 2011 A1
20110313349 Krulevitch et al. Dec 2011 A1
20110319322 Bashan et al. Dec 2011 A1
20120022496 Causey et al. Jan 2012 A1
20120053560 Kawamura Mar 2012 A1
20120159328 Millington et al. Jun 2012 A1
20120215201 Brauker et al. Aug 2012 A1
20120226124 Blomquist Sep 2012 A1
20120232520 Sloan et al. Sep 2012 A1
20120238999 Estes et al. Sep 2012 A1
20120330270 Colton Dec 2012 A1
20130165901 Ruchti et al. Jun 2013 A1
20130172710 Mears et al. Jul 2013 A1
20130184547 Taub Jul 2013 A1
20130245545 Arnold et al. Sep 2013 A1
20130318439 Landis et al. Nov 2013 A1
20130324941 Mann et al. Dec 2013 A1
20130331659 Koski et al. Dec 2013 A1
20130332952 Anandpura et al. Dec 2013 A1
20130338453 Duke et al. Dec 2013 A1
20140012117 Mensinger et al. Jan 2014 A1
20140025400 Galley et al. Jan 2014 A1
20140031786 Kircher, Jr. et al. Jan 2014 A1
20140039383 Dobbles et al. Feb 2014 A1
20140058749 Galley et al. Feb 2014 A1
20140068487 Steiger et al. Mar 2014 A1
20140073892 Randloev et al. Mar 2014 A1
20140154987 Lee et al. Jun 2014 A1
20140160078 Seo et al. Jun 2014 A1
20140309615 Mazlish Oct 2014 A1
20140317546 Jacobson et al. Oct 2014 A1
20140344280 Wei et al. Nov 2014 A1
20140358082 Ohzawa Dec 2014 A1
20140380218 Johnnie Dec 2014 A1
20150025498 Estes Jan 2015 A1
20150067527 Gardner et al. Mar 2015 A1
20150073337 Saint et al. Mar 2015 A1
20150073754 Okkonen Mar 2015 A1
20150080842 Mathys Mar 2015 A1
20150112264 Kamen et al. Apr 2015 A1
20150141912 Estes May 2015 A1
20150173674 Hayes et al. Jun 2015 A1
20150277722 Masterson et al. Oct 2015 A1
20160000998 Estes Jan 2016 A1
20160038675 Estes et al. Feb 2016 A1
20160058939 Brewer et al. Mar 2016 A1
20160072841 Caporal et al. Mar 2016 A1
20160089491 Smith Mar 2016 A1
20160110064 Shapira Apr 2016 A1
20160139671 Jun et al. May 2016 A1
20160235913 Smith et al. Aug 2016 A1
20160250422 Koch et al. Sep 2016 A1
20160317743 Estes Nov 2016 A1
20160357371 Lee Dec 2016 A1
20160361494 Jurg et al. Dec 2016 A1
20170003848 Wakayanagi et al. Jan 2017 A1
20170017374 Herz Jan 2017 A1
20170049957 Michaud Feb 2017 A1
20170056591 Breton et al. Mar 2017 A1
20170100538 Mhatre et al. Apr 2017 A1
20170165416 Saint Jun 2017 A1
20170173262 Veltz Jun 2017 A1
20170176952 Misaki et al. Jun 2017 A1
20170189614 Mazlish et al. Jul 2017 A1
20170193184 Hayter et al. Jul 2017 A1
20170199985 Mazlish et al. Jul 2017 A1
20170203030 Brewer et al. Jul 2017 A1
20170203036 Mazlish et al. Jul 2017 A1
20170203037 Desborough et al. Jul 2017 A1
20170203038 Desborough et al. Jul 2017 A1
20170203039 Desborough et al. Jul 2017 A1
20170216524 Haider et al. Aug 2017 A1
20170224910 Yodfat et al. Aug 2017 A1
20170232195 Desborough et al. Aug 2017 A1
20170242975 Kahlbaugh Aug 2017 A1
20170255771 Miyakawa Sep 2017 A1
20170316592 Kamath et al. Nov 2017 A1
20170332952 Desborough et al. Nov 2017 A1
20170348484 Duke Dec 2017 A1
20170351842 Booth et al. Dec 2017 A1
20180001006 Schade et al. Jan 2018 A1
20180036495 Searle et al. Feb 2018 A1
20180089395 Desborough et al. Mar 2018 A1
20180101297 Yang et al. Apr 2018 A1
20180133397 Estes May 2018 A1
20180147362 Arenas et al. May 2018 A1
20180150614 Sokolovskyy et al. May 2018 A1
20180161499 Al-Ali et al. Jun 2018 A1
20180200435 Mazlish et al. Jul 2018 A1
20180200436 Mazlish et al. Jul 2018 A1
20180200437 Mazlish et al. Jul 2018 A1
20180200438 Mazlish et al. Jul 2018 A1
20180200439 Mazlish et al. Jul 2018 A1
20180200441 Desborough et al. Jul 2018 A1
20180207380 Lantz et al. Jul 2018 A1
20180361060 Rosinko Dec 2018 A9
20190001067 Berey et al. Jan 2019 A1
20190015024 Desborough et al. Jan 2019 A1
20190175841 Sjolund Jun 2019 A1
20190183434 Sjolund et al. Jun 2019 A1
20190184111 Sjolund et al. Jun 2019 A1
20190265871 Eim et al. Aug 2019 A1
20190274624 Mazlish et al. Sep 2019 A1
20190348166 Booth et al. Nov 2019 A1
20200042166 Burns et al. Feb 2020 A1
20200097131 Bowden et al. Mar 2020 A1
20200201494 Allington et al. Jun 2020 A1
20200236212 Vinna et al. Jul 2020 A1
Foreign Referenced Citations (73)
Number Date Country
2543545 May 2005 CA
104620244 May 2015 CN
19627619 Jan 1998 DE
10236669 Feb 2004 DE
000627617-0002 Jan 2007 EM
000627617-0003 Jan 2007 EM
000627617-0091 Jan 2007 EM
0006276170001 Jan 2007 EM
0006276170002 Jan 2007 EM
0006276170003 Jan 2007 EM
000732649-0001 Jun 2007 EM
000732649-0002 Jun 2007 EM
0007326490001 Jun 2007 EM
0007326490002 Jun 2007 EM
003126705-0091 Jul 2016 EM
003126795-9992 Jul 2016 EM
003126795-9993 Jul 2016 EM
003126795-9994 Jul 2016 EM
0031267050001 Jul 2016 EM
0031267050002 Jul 2016 EM
0031267050003 Jul 2016 EM
0031267050004 Jul 2016 EM
0062974 Oct 1982 EP
0275213 Jul 1988 EP
0496141 Jul 1992 EP
0580723 Feb 1994 EP
0612004 Aug 1994 EP
0721358 Jul 1996 EP
1045146 Oct 2000 EP
1136698 Sep 2001 EP
1177802 Feb 2002 EP
1495775 Jan 2005 EP
1527792 May 2005 EP
1754498 Feb 2007 EP
1818664 Aug 2007 EP
2585252 May 2013 EP
2585252 Jan 1987 FR
0747701 Apr 1956 GB
2218831 Nov 1989 GB
9015928 Dec 1990 WO
9509021 Apr 1995 WO
9721457 Jun 1997 WO
9804301 Feb 1998 WO
9811927 Mar 1998 WO
9857683 Dec 1998 WO
9921596 May 1999 WO
9939118 Aug 1999 WO
9948546 Sep 1999 WO
0172360 Oct 2001 WO
0191822 Dec 2001 WO
0191833 Dec 2001 WO
0240083 May 2002 WO
0257627 Jul 2002 WO
0268015 Sep 2002 WO
0284336 Oct 2002 WO
2002100469 Dec 2002 WO
0326726 Apr 2003 WO
2003103763 Dec 2003 WO
2004056412 Jul 2004 WO
2004110526 Dec 2004 WO
2005002652 Jan 2005 WO
2005039673 May 2005 WO
2005072794 Aug 2005 WO
2005072795 Aug 2005 WO
2006067217 Jun 2006 WO
2006097453 Sep 2006 WO
2006105792 Oct 2006 WO
2006105793 Oct 2006 WO
2006105794 Oct 2006 WO
2007141786 Dec 2007 WO
2011163450 Dec 2011 WO
2016019192 Feb 2016 WO
2017009724 Jan 2017 WO
Non-Patent Literature Citations (66)
Entry
Owens et al., Run-to-Run Control of Blood Glucose Concentrations for People with Type 1 Diabetes Mellitus, IEEE 2006, pp. 996-1005. (Year: 2006).
Eren-Oruklu et al., Adaptive Control Strategy for Regulation of Blood Glucose Levels in Patients with Type 1 Diabetes, ScienceDirect 2009, pp. 1333-1346. (Year: 2009).
“Clean Toggle Button Navigation Menu PSD” Jan. 24, 2014, WeLoveSoLo, site visited Oct. 19, 2018: https://www.welovesolo.com/clean-toggle-button-navigation-menu-psd/.
“Omnipod Horizon: Automated Glucose Control” Jun. 2017, 2 pages.
Accu-Chek Spirit, “Pump Therapy Made for You,” Roche, 2006, 6 pages.
Arrow Repeat. By Flaticon. Freepik.com. Date: 2014. Retrieved from Internet: <https://www.freepik com/free-icon/arrow-repeat_ 694329.htm#term=arrows&page=47&position=67> (Year: 2014).
Arrows Curves Forming an Oval Shape. By Flaticon. Freepik.com. Date: 2015. Retrieved from Internet: <https://www.freepik.com/free-icon/arrows-curves-forming-an-oval-shape_746143.htm> (Year: 2015).
Arrows, Couple, IOS 7 Interface Symbol. By Flaticon. Freepik.com. Date: 2015. Retrieved from Internet: <https://www.freepik.com/free-icon/arrows-couple-ios-7-interface-symbo_751266.htm#tterm=arrows&page=68&position=43> (Year: 2015).
Baruah, Insulin Pens: The Modern Delivery Devices, Google Scholar 2011, pp. 38-40. (Year: 2011).
Bhalla, Raveesh, Understanding Material Design Part II, Sep. 28, 2014, Medium.com [online], [site visited Apr. 11, 2018], Available from Internet: https://medium.eom/@raveeshbhalla/understanding-material-design-cf2d60a16de3 (Year: 2014).
Bigfoot Biomedical Reveals its Automated Insulin Delivery System. diaTribe. Date published: Jan. 25, 2016 <https://diatribe.org/bigfoot-biomedical-reveals-its-automated-insulin-delivery-system>.
Bode et al., Diabetes Management in the New Millennium Using Insulin Pump Therapy, Wiley Inter Science 2002, pp. 514-520. (Year: 2002).
Collins and Lee, “Microfluidic flow transducer based on the measurement of electrical admittance,” Lab Chip, 2004,4:7-10.
Curved Arrow to the Right. By Flaticon. Freepik.com. Date: 2015. Retrieved from Internet: 21 https://www.freepik.com/free-icon/curved-arrow-to-the-right 735735.htm#term=arrows&page=59&position=69> (Year: 2015).
Dassau and Associates, 12-Week 24/7 Ambulatory Artificial Pancreas With Weekly Adaptation of Insulin Delivery Settings: Effect on Hemoglobin A1C and Hypoglycemia, Diabetes Care, Oct. 13, 2017.
David A. Copp, Ravi Gondhalekar, and Joao P. Hespanha, Simultaneous Model Predictive Control and Moving Horizon Estimation for Blood Glucose Regulation in Type 1 Diabetes, Optimal Control Applications and Methods, Wiley InterScience, DOI: 10.1002/oca, pp. 1-15, Oct. 2016.
Delaney, Chelsey, “4 apps for tracking your fertility” Jun. 6, 2016, Bedsider, site visited Oct. 19, 2018: https://www.bedsider.org/features/647-4-apps-for-tracking-your-fertility.
Dreyfuss, Henry. Symbol Sourcebook. Van Nostrand Reinhold Company. Date published: 1984. Page 28. (Year: 1984).
E. Salzsieder, G. Albrecht, E. Jutzi, and U. Fischer, Estimation of Individually Adapted Control Parameten for an Artificial Beta Cell, Biomedica Biochimica Acta. 43(5) pp. 585-596, May 1984.
Fischer et al.. In Vivo Comparison of Different Algorithms for the Artificial Beta-Cell, Artificial Organs, 9(2), International Society for Artificial Organs, May 1985, New York.
Guy A. Dumont, Feedback Control for Clinicians, Springer Science+Media, Apr. 12, 2013, New York.
Hoskins, Mike, NEWS: Bigfoot Closed Loop, Jul. 17, 2017, Healthline.com [online], [visited Jan. 22, 2019]. Internet: https://web.archive.org/web/20170810052840/https://www.diabetesdaily.com/blog/bigfoot-biomedical-aims-to-take-multiple-daily-injections-to-the-next-level-with-timesulin-acquisition (Year: 2017).
International Search Report for PCT Application No. PCT/US2017/053814, dated Jan. 4, 2018, 4 pages.
Kuwayama, Yasaburo. Trademarks & Symbols. vol. 2: Symbolical Designs. Van Nostrand Reinhold Company. Date published: 1973. p. 136 (Year: 1973).
Michele Schiavon, Chiara Dalla Man, Yogish C. Kudva, Ananda Basu, and Claudio Cobelli, Quantitative Estimation of Insulin Sensitivity in Type 1 Diabetic Subjects Wearing a Sensor-Augmented Insulin Pump, Diabetes Care, vol. 37, pp. 1216-1223, May 2014.
OmniPod Insulin Management System—Investor Relations—Press Release, Feb. 1, 2005, http://investors.insulel.com/phoenix.zhlml?c=209336&p=irol-newsArticle&ID=988708&highlight= 1 page.
OmniPod Quick Start Guide, 2007, 2 pages.
Patent Abstracts of Japan, vol. 1999, No. 04, and JP 11 010036, Apr. 30, 1999 and Jan. 19, 1999, Toray Ind. Inc.
Pearson, Practical Aspect of Insulin Pen Devices, Journal of Diabetes Science and Technology 2010, pp. 522-531. (Year: 2010).
Refresh Arrow Loop. By Flaticon. Freepik.com. Date:2014. Retrieved from Internet: <https://www.freepik.com/free-icon/refresh-arrow-loop_705291 .htm#term=arrows&page=49&position=43> (Year: 2014).
Refreshing. By Flaticon. Freepik.com. Date: 2016. Retrieved from Internet: <https://www.freepik.com/free-icon/refreshing_807573. htm#term=arrows&page=26&position=26> (Year: 2016).
Sara Krugman, Bionic Pancreas User Interface (3/4): Interface Details, Tidepool.org, Jul. 20, 2015.
Sindaco et al., Use of the Short-acting Insulin Analogue Lispro in Intensive Treatment of Type 1 Diabetes Mellitus: Importance of Appropriate Replacement of Basal Insulin and Time-interval Injection-meal, Diabetic Medicine 1998, pp. 592-600. (Year: 1998).
Smart et al., “Can children with type 1 diabetes and their caregivers estimate the carbohydrate content of meals and snacks?” Diabetic Medicine, 27, No. 3 (2010) pp. 38-353.
Synchronise, IOS 7 Interface Symbol. By Flaticon. Freepik.com. Date: 2015. Retrieved from Internet: <https://www.freepik.com/free-icon/synchronise-ios-7-interface-symbol_751804.htm#term=arrows&page=69&position=14> (Year: 2015).
T:slimx2 Insulin Pump User Guide, Tandem Diabetes Care, Jul. 22, 2016.
The Medtronic Diabetes Connection, 2006, 6 pages.
Written Opinion of the International Searching Authority for PCT Application No. PCT/US2017/053814, dated Jan. 4, 2018, 8 pages.
Xilas Temp Touch, “The latest in high-tech and convenient devices,” DOCNews, vol. 2, No. 7, Jul. 1, 2005, http://docnews.diabetesjoumals.ordlcgi/contenl/foll/2/7i 13, 3 pages.
Zhang et al., Second Insulin Pump Safety Meeting: Summary Report, Journal of Diabetes Science and Technology 2010, pp. 488-493. (Year: 2010).
“Medical Set.” iconfinder.com. Added Apr. 7, 2017. Accessed Jan. 27, 2020. Available online at URL: https://www.iconfinder.com/iconsets/medical-set-5 (Year: 2017).
“Three icons—Ready, Set and Go” Nov. 29, 2015, depositphotos, site visited Apr. 21, 2020: https://depositphotos.com/91436542/stock-illustration-countdown-ready-set-go-colorful.html (Year: 2015).
Ansyari, Nazurrudin. “Circle Badge Set.” iconfinder.com. Added Aug. 15, 2016. Accessed Jan. 27, 2020. Available online at URL: https://www.iconfinder.com/iconsets/ciicle-badge-set (Year: 2016).
Bhalla, Reveesh, Understading Material Design Part II, Sep. 28, 2014, Medium.com [online], [site visited Apr. 11, 2018], Available from Internet: https://medium.com/@raveeshbhalla/understanding-material-design-cf2d60a16de3 (Year: 2014).
Bigfoot Biomedical Reveals its Automated Insulin Delivery System. diaTribe. Date published: Jan. 25, 2016 <https://diatrive.org/bigfoot-biomedical-reveals-its-automated-insulin-delivery-system>.
Centers for Disease Control and Prevention, Number (in Millions) of Adults with Diabetes by Diabetes Medication Status, United States, 1997-2011, http://www.cdc.gov/diabetes/statislics/meduse/fig1.him, 2013.
Debiotech News Release, “Debiotech reveals its new miniaturized Disposable Insulin Nanopump™ for Diabetes therapy,” available at http://www.debiotech.com/news/nw 159.html Apr. 24, 2006, 3 pages.
European Search Report and Opinion for European Application No. 17857364.8, dated Apr. 21, 2020, 8 pages.
Grill et al., Exercise and Postprandial Lipid Metabolism: an Update on Potential Mechanisms and Interactions with High-Carbohydrate Diets/(Review), Elsevier 2003, pp. 122-132. (Year: 2003).
Harvey et al., Quest for the Artificial Pancreas, IEEE 2010, pp. 53-62. (Year: 2010).
Hurley, Dan. Artificial Pancreas Makers Race to Markel. Discover. Date published: Apr. 12, 2016. <http://discovermagazine.com/2016/may/13-priming-the-pump>.
JDRF, Statistics: JDRF and Diabetes, http://jdrf.org/aboul-jdrf/facl-sheels/jdrf-anddiabeles- statistics/, 2014.
Karnes, Chris. “Kids Mental Health App.” dribbble.com. Feb. 1, 2020. Accessed May 7, 2020. Available online at URL: https://dribbble.com/shots/9841070-Kids-Mental-Health-App (Year: 2020).
Kumar, Rohit. “Health App.” dribbble.com. May 14, 2015. Accessed May 7, 2020. Available online at URL: https://dribbble.com/shots/2062723-Health-App (Year: 2015).
Medtronic News Release, “Medtronic Receives FDA Approval for World's First Insulin Pump with Real-time Continuous Glucose Monitoring,” Apr. 13, 2006, 3 pages.
Samuel Vozeh and Jean-Louis Steimer, Feedback Control Methods for Drug Dosage Optimisation, Concepts, Classification and Clinical Application, Clinical Pharmacokinetics, 10(6), pp. 457-476, Nov.-Dec. 1985.
Shishir, Shahidl Islam. “Med-i App | Splash Home and Logo.” dribbble.com. Jul. 28, 2019. Accessed May 7, 2020. Available online at URL: https://dribbble.com/shots/6852974-Med-i-App-I-Splash-Home-and-Logo (Year: 2019).
Simmons, Cory, “How to Make Your Own Button UI Kil with Super-Clean Syntax” Dec. 23, 2014, envato tuts+, site visited Sep. 19, 2019: https://webdesign.lutsplus.com/lutorials/how-lo-make-your--0wn-button-ui-kil-wilh-super-clean-syntax-cms-22946.
Australian Examination Report from Australian Application No. 2017335762, dated Oct. 29, 2021, 3 pages.
Dreyfuss, Henry. Symbol Sourcebook: An Authoritative Guide to International Graphic Symbols. Van Nostrand Reinhold, 1984. p. 52. (Year: 1984).
U.S. Trademark Serial No. 85698749 to Mmillenniumm Group Ing. Filed Aug. 8, 2012. Retrieved Mar. 7, 2022 online via Trademark Electronic Search System (TESS). (Year: 2012).
U.S. Trademark Serial No. 86854669 to DynoSense Corp. Filed Dec. 19, 2015. Retrieved Mar. 7, 2022 online via Trademark Electronic Search System (TESS). (Year: 2015).
Chinese First Office Action for Chinese Application No. 201910969068.3 dated Nov. 21, 2022, 13 pages with translation.
European Communication pursuant to Article 94(3) EPC for European Application No. 17857362.2, dated Mar. 20, 2023, 5 pages.
“LifeScan Receives FDA Clearance for One Touch VerioSync Bluetooth Blood Glucose Meter” Mar. 7, 2013, posted at medgadget.com, [site visited May 30, 2023]. https://www.medgadget.com/2013/03/lifescan-receives-fda-clearance-for-onetouch-veriosync-bluetooth-blood-glucose-meter.html (Year: 2013).
“SeebeckCell Technologies” Jul. 7, 2022, posted at greentownlabs.com, [site visited May 30, 2023]. https://web.archive.org/web/20220707134432/https://greentownlabs.com/members/seebeckcell-technologies (Year: 2022).
Related Publications (1)
Number Date Country
20200001018 A1 Jan 2020 US
Provisional Applications (1)
Number Date Country
62400366 Sep 2016 US
Continuations (1)
Number Date Country
Parent 15717805 Sep 2017 US
Child 16566544 US