Abstract: Methods and apparatuses for performing an insulin infusion process are described. For example, an apparatus may include at least one memory and logic coupled to the at least one memory. The logic may operate to determine a basal parameter for a patient based on a type 2 diabetes (T2D) multiple daily injection (MDI) information of the patient, the basal parameter indicating a basal infusion rate, determine an additional insulin (Iadd) value based on a mean blood glucose difference (BGdiff) information associated with the patient, determine an insulin volume to infuse into the patient based on the basal parameter and Iadd, and administer the insulin volume to the patient. Other embodiments are described.

Abstract: Embodiments of the present disclosure relate to approaches for transitioning a drug delivery device from a low-energy sleep state to a high-energy active state. In some embodiments, a system may include a drug delivery device, the drug delivery device including a pump mechanism coupled to a reservoir for expelling a liquid drug from the reservoir; and an activation component communicatively coupled to the pump mechanism. The activation component may include at least one of a sensor and a mechanical activation device, and a wake-up circuit operable to receive an input from the sensor or the mechanical activation device, wherein the input indicates a change in a device characteristic. Based on the change in the device characteristic, the wake-up circuit may be further operable to transition the drug delivery device from a low-energy state to an active state.

Abstract: Exemplary embodiments may perform data analytics on data regarding a user of a medicament delivery device and data regarding other users of like medicament delivery devices to provide insights and guide management of the medicament delivery device for the user. The data analytics may be so called “big data” analytics that are performed on large data sets. The data analytics may be performed on various types of data to help determine what actions, if any, the remote management should take. The data analytics may be performed by the software on the remote management device or by other computational resources, such as by other servers or cloud computing resources. Exemplary embodiments may provide for remote management of a medicament delivery device. The management may be remote in that the management is performed via a remote management device, such as a computing device, that is remotely located from the medicament delivery device.

Abstract: The disclosed embodiments are directed to a wearable automatic drug delivery device configured to provide basal-only dosing of insulin. In a primary embodiment, the wearable drug delivery device is configured to provide automatic operation and provides audible alerts and visual status indicators to the patient. In other embodiments, the patient may have some degree of control over the operation of the device by providing tapping gestures on housing of the device. In yet another embodiment, the patient may provide input and receive status from the device via an application executing on a portable computing device in wireless communication with the wearable drug delivery device.

Abstract: Embodiments of the present disclosure relate to techniques, processes, devices or systems for automating fluid delivery without the use of an external interface device. In one approach, a wearable drug delivery device may include a reservoir configured to store a liquid drug, a pump mechanism coupled to the reservoir and operable to expel the liquid drug from the reservoir, and a mechanical triggering device engageable by a user. The mechanical triggering device is operable to change between a first configuration and a second configuration to control deployment of a needle to deliver the liquid drug into a patient.

Abstract: The exemplary embodiments allow a user to have more aggressive settings or less aggressive settings for an AID system after demonstrating good blood glucose level control. This allows the settings to be more quickly customized to users that demonstrate good quality blood glucose level control than conventional systems. As these users have demonstrated good quality glucose level control there is less of a need to constrain the settings and provide a high margin of safety. Conversely, users demonstrating poor quality blood glucose level control may have less aggressive settings imposed, representing a higher margin of safety.

Abstract: A drug delivery system having a drug delivery device and an associated sensor is provided. The sensor can be associated with a sensing site on user. The drug delivery device can be positioned over the sensor in any rotational position and can be associated with an infusion site on the user. The close positioning of the sensor and the drug delivery device allows data from the sensor to be relayed to the drug delivery device and then on to a remote control device. Further, the drug delivery device can be replaced at the end of its duration of use, which is shorter than the duration of use of the sensor, without disturbing the sensor. Subsequent drug delivery devices can then be used with the sensor while allowing each corresponding infusion site to be changed, thereby providing more efficient operation of the drug delivery system.

Abstract: Disclosed are techniques to establish a modified pump rate that mitigates the effects of a pump occlusion and enables a recommended dosage of insulin to be output by a pump mechanism over the course of a control cycle. In an example, the pump rate may be reduced by adding a calculated time interval between application of actuation commands to extend the amount of time over which insulin may be output by the pump mechanism.

Abstract: Disclosed are techniques and a device operable to determine a total amount of insulin delivered to the user over a predetermined time period. The total amount of insulin includes a total basal dosage delivered in basal dosages and a total bolus dosage delivered in bolus dosages over the predetermined time period. A proportion of the total amount of insulin delivered to the user provided via the total basal dosage amount over the predetermined time period is calculated. In response determining the proportion of the total amount of insulin attributed to the total basal dosage amount of insulin exceeds a threshold, an average basal dosage to be delivered within a subsequent time period that is approximately equal to the threshold may be determined. An instruction may be generated and output to deliver a modified basal dosage that substantially maintains the average basal dosage over the subsequent time period.

Abstract: Systems and methods for automatically delivering medication to a user. An automated drug delivery system may include a sensor and a wearable automated drug delivery device. The wearable automated drug delivery device may be configured to couple to the skin of a user and may include a controller and a pump. The pump may be configured to output the medication. The controller may be within the wearable automated drug delivery device. The sensor may be coupled to the user and may be configured to collect information regarding the user. The controller of the wearable automated drug delivery device may use the collected information to locally determine an amount of medication to be output from the wearable automated drug delivery device and cause delivery of the amount of medication.

Abstract: Disclosed are techniques to establish initial settings for an automatic insulin delivery device. An adjusted total daily insulin (TDI) factor usable to calculate a TDI dosage may be determined. The adjusted TDI factor may be a TDI per unit of a physical characteristic of the user (e.g., weight) times a reduction factor. The adjusted TDI factor may be compared to a maximum algorithm delivery threshold. Based on the comparison result, the application or algorithm may set a TDI dosage and output a control signal. Blood glucose measurement values may be collected from a sensor over a period of time. A level of glycated hemoglobin of the blood may be determined based on the obtained blood glucose measurement values. In response to the level of glycated hemoglobin, the set TDI dosage may be modified. A subsequent control signal including the modified TDI dosage may be output to actuate delivery of insulin.

Abstract: A system, techniques, and computer-readable media includes examples that provide an indication of an early exercise detection are described. An example of an early exercise detection application executed by a processor may cause the processor to perform functions and be operable to obtain image data including metadata from a camera of a mobile device during, for example, an unlock procedure of a mobile device. The processor may determine whether the obtained image data includes location or timestamp information in metadata or has image data that may be recognized as exercise-related objects. Based on the determinations, the processor may output an indication of early exercise detection to an artificial pancreas application, which is operable to adjust an amount of insulin to be delivered to a user.

Abstract: Exemplary embodiments may address the problem of missing blood glucose concentration readings from a glucose monitor that transmits blood glucose concentration readings over a wireless connection due to problems with the wireless connection. In the exemplary embodiments, an automated insulin delivery (AID) device uses an estimate in place of a missing blood glucose concentration reading in determining a predicted future blood glucose concentration reading for a user. Thus, the AID device is able to operate normally in generating insulin delivery settings despite not receiving a current blood glucose concentration reading for a current cycle. There is no need to suspend delivery of insulin to the user due to the missing blood glucose concentration reading.

Abstract: Systems and methods for automatically delivering medication to a user. An automated drug delivery system may include a sensor and a wearable automated drug delivery device. The wearable automated drug delivery device may be configured to couple to the skin of a user and may include a controller and a pump. The pump may be configured to output the medication. The controller may be within the wearable automated drug delivery device. The sensor may be coupled to the user and may be configured to collect information regarding the user. The controller of the wearable automated drug delivery device may use the collected information to locally determine an amount of medication to be output from the wearable automated drug delivery device and cause delivery of the amount of medication.

Abstract: The exemplary embodiments attempt to identify impending hypoglycemia and/or hyperglycemia and take measures to prevent the hypoglycemia or hyperglycemia. Exemplary embodiments may provide a drug delivery system for delivering insulin and glucagon as needed by a user of the drug delivery system. The drug delivery system may deploy a control system that controls the automated delivery of insulin and glucagon to a patient by the drug delivery system. The control system seeks among other goals to avoid the user experiencing hypoglycemia or hyperglycemia. The control system may employ a clinical decision support algorithm as is described below to control delivery of insulin and glucagon to reduce the risk of hypoglycemia or hyperglycemia and to provide alerts to the user when needed. The control system assesses whether the drug delivery system can respond enough to avoid hypoglycemia or hyperglycemia and generates alerts when manual action is needed to avoid hypoglycemia or hyperglycemia.

Abstract: Exemplary embodiments described herein relate to a closed loop artificial pancreas system. The artificial pancreas system seeks to automatically and continuously control the blood glucose level of a user by emulating the endocrine functionality of a healthy pancreas. The artificial pancreas system uses a closed loop control system with a cost function. The penalty function helps to bound the infusion rate of insulin to attempt to avoid hypoglycemia and hyperglycemia. However, unlike conventional systems that use a generic or baseline parameter for a user's insulin needs in a cost function, the exemplary embodiments may use a customized parameter in the cost function that reflects the individualized insulin needs of the user. The use of the customized parameter causes the cost function to result in insulin dosages over time better suited to the individualized insulin needs of the user. This helps to better avoid hypoglycemia and hyperglycemia.

Abstract: Disclosed are examples of a device, a system, methods and computer-readable medium products operable to implement functionality to determine and respond to a purpose of a meal. An algorithm or application may receive data that may include data related to a meal purpose from data sources and determine whether any of the data received from the plurality of data sources was received from a direct data source or an indirect data source. The data may be evaluated to determine a purpose of the meal. Based on the results of the evaluation, instructions may be generated to provide an appropriate response based on the determined purpose of the meal. The generated instructions to provide the appropriate response based on the determined purpose of the meal may be output.

Abstract: Exemplary embodiments may provide an improved approach to automated insulin delivery by more accurately estimating the total daily insulin (TDI) of a user. As a result, less insulin is wasted by the delivery system, and the estimate of TDI more closely matches a user's actual daily insulin needs. Hence, the user need not refill the insulin reservoir excessively or need not fret unnecessarily about running out of insulin prematurely. The estimate relies on the history of actual automated insulin deliveries and thus reflects the actual insulin delivered to the user more accurately than conventional approaches.

Abstract: In an automated insulin delivery device, fuzzy logic may be applied to the responding to the possibility of a user taking additional action that may affect the blood glucose concentration. Fuzzy sets may be defined for empirically derived different likelihoods of the user taking such additional action based on correlated factors. A membership function may be provided for each fuzzy set. The membership function may provide a probability of membership in the set based on a parameter. Each fuzzy set may have a response that is reflective of the likelihood of additional user action associated with the fuzzy set. The responses by the AID device to each of these cases may reflect the probability of each such case occurring as evidenced by empirical data.

Abstract: Disclosed are a device, system, methods and computer-readable medium products that provide techniques to implement functionality to receive information related to a meal and delivery of a meal bolus. The received information may be stored and utilized in the generation of insulin delivery profiles. An estimate a mealtime insulin need based on the generated insulin delivery profiles may be generated. A dose of insulin may be determined that satisfies an estimated mealtime insulin need based on the generated insulin delivery profiles. The determined dose of insulin may be output at a time corresponding to a mealtime.