Abstract: Embodiments described herein relate to systems, devices, and methods for use in the implementation of a brain-computer interface that integrates real-time eye-movement tracking with brain activity tracking to present and update a user interface that is strategically designed for high speed and accuracy of human-machine interaction. Embodiments described herein also relate to the implementation of a hardware agnostic brain-computer interface that uses real-time eye tracking and online analysis of neural signals to mediate user manipulation of machines.

Abstract: Embodiments described herein relate to systems, devices, and methods for use in the implementation of a human-computer interface using high-speed, and efficient tracking of user interactions with a User Interface/User Experience that is strategically presented to the user. Embodiments described herein also relate to the implementation of a hardware agnostic human-computer interface that uses neural, oculomotor, and/or electromyography signals to mediate user manipulation of machines and devices.

Abstract: Embodiments described herein relate to systems, devices, and methods for use in the implementation of a brain-computer interface that integrates real-time eye-movement tracking with brain activity tracking to present and update a user interface that is strategically designed for high speed and accuracy of human-machine interaction. Embodiments described herein also relate to the implementation of a hardware agnostic brain-computer interface that uses real-time eye tracking and online analysis of neural signals to mediate user manipulation of machines.

Abstract: The disclosed embodiments are directed to systems and methods for providing optimized, individualized bolus dosing of insulin based on a macronutrient profile of meals ingested by the patient. Optimized bolus dosing may be provided by varying the overall quantity of insulin delivered in the post-prandial window, as well as the split between a portion of the insulin delivered immediately after the meal and a portion of the insulin delivered later in the post-prandial window, based on an analysis of the macronutrient profile of the meal and the behavior of the blood glucose trace of the patient from past meals.

Abstract: The disclosed embodiments are directed to an automatic drug delivery (ADD) system device configured to provide bolus dosing of insulin. The embodiments include a system and method for providing an improved meal input interface for the user as well as methods for the use of the information provided by the user to both improve the post-prandial bolus dosing of insulin and to advise the user on meals that will lead to improved blood glucose control for the user.

Abstract: The provided examples of systems, devices and techniques improve systems and methods for keeping users of automatic drug delivery systems engaged and assisting with the optimal use of the drug delivery system. The automatic drug delivery system may include a drug delivery device and a controller. Through the use of an attrition prevention engine in a cloud-based services system that cooperates with an attrition prevention application executing on the controller of the drug delivery device, notifications that include instructions for adjusting operation of the drug delivery device as well as offer assistance to the patient to optimize performance of the drug delivery system for the patient may be provided. Optimizing the performance of the drug delivery system has been shown to prevent attrition of patients from using the drug delivery system.

Abstract: Embodiments described herein relate to systems, devices, and methods for use in the implementation of a human-computer interface using high-speed, and efficient tracking of user interactions with a User Interface/User Experience that is strategically presented to the user. Embodiments described herein also relate to the implementation of a hardware agnostic human-computer interface that uses neural, oculomotor, and/or electromyography signals to mediate user manipulation of machines and devices.

Abstract: Embodiments described herein relate to systems, devices, and methods for use in the implementation of a brain-computer interface that integrates real-time eye-movement tracking with brain activity tracking to present and update a user interface that is strategically designed for high speed and accuracy of human-machine interaction. Embodiments described herein also relate to the implementation of a hardware agnostic brain-computer interface that uses real-time eye tracking and online analysis of neural signals to mediate user manipulation of machines.

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: Embodiments described herein relate to systems, devices, and methods for use in the implementation of a human-computer interface using high-speed, and efficient tracking of user interactions with a User Interface/User Experience that is strategically presented to the user. Embodiments described herein also relate to the implementation of a hardware agnostic human-computer interface that uses neural, oculomotor, and/or electromyography signals to mediate user manipulation of machines and devices.

Abstract: Embodiments described herein relate to systems, devices, and methods for use in the implementation of a brain-computer interface that tracks brain activity, with or without additional sensors providing additional sources of information, while presenting and updating a User Interface/User Experience that is strategically designed for high speed and accuracy of human-machine interaction. Embodiments described herein also relate to the implementation of a hardware agnostic brain-computer interface that uses neural signals to mediate user manipulation of machines and devices.

Abstract: Embodiments described herein relate to systems, devices, and methods for use in the implementation of a brain-computer interface that integrates real-time eye-movement tracking with brain activity tracking to present and update a user interface that is strategically designed for high speed and accuracy of human-machine interaction. Embodiments described herein also relate to the implementation of a hardware agnostic brain-computer interface with specific user interface adaptations to enable high-speed, intuitive, and accurate user manipulation of applications and/or machines.

Abstract: Embodiments described herein relate to systems, devices, and methods for use in the implementation of a brain-computer interface that integrates real-time eye-movement tracking with brain activity tracking to present and update a user interface that is strategically designed for high speed and accuracy of human-machine interaction. Embodiments described herein also relate to the implementation of a hardware agnostic brain-computer interface that uses real-time eye tracking and online analysis of neural signals to mediate user manipulation of machines.

Abstract: Embodiments described herein relate to systems, devices, and methods for use in the implementation of a human-computer interface using high-speed, and efficient tracking of user interactions with a User Interface/User Experience that is strategically presented to the user. Embodiments described herein also relate to the implementation of a hardware agnostic human-computer interface that uses neural, oculomotor, and/or electromyography signals to mediate user manipulation of machines and devices.

Abstract: Embodiments described herein relate to systems, devices, and methods for use in the implementation of a human-computer interface using high-speed, and efficient tracking of user interactions with a User Interface/User Experience that is strategically presented to the user. Embodiments described herein also relate to the implementation of a hardware agnostic human-computer interface that uses neural, oculomotor, and/or electromyography signals to mediate user manipulation of machines and devices.