Enhanced Automatic Detection of Un-Bolused Meals

An advanced system and method for automatic detection of un-bolused meals, leveraging continuous glucose monitoring data and user input to provide timely reminders and personalized meal bolus recommendations, thereby improving diabetes therapy outcomes.

The original patent addressed the challenge of accurately detecting un-bolused meals in diabetes therapy. However, it had limitations in providing timely reminders and personalized meal bolus recommendations. The new inventive concept builds upon the original patent by incorporating advanced analytics and machine learning algorithms to enhance the detection of un-bolused meals and provide more effective reminders and recommendations.

The new inventive concept comprises a portable infusion pump, a continuous glucose monitoring system, and a mobile communication device. The system receives continuous glucose monitoring data and user input relating to an expected meal, analyzes the data to detect an un-bolused meal, and automatically generates a reminder to deliver a meal bolus or a personalized meal bolus recommendation in response to the detection. The system utilizes advanced analytics and machine learning algorithms to improve the accuracy of un-bolused meal detection and provide more effective reminders and recommendations.

The new claims introduce the concept of personalized meal bolus recommendations, which is not present in the original patent. Additionally, the use of advanced analytics and machine learning algorithms to enhance the detection of un-bolused meals and provide more effective reminders and recommendations is a novel and non-obvious improvement over the original patent.

Alternative embodiments of the inventive concept could include integrating the system with other diabetes management tools, such as blood glucose meters or insulin dosing calculators. Variations of the system could include using different types of continuous glucose monitoring systems or incorporating additional data sources, such as physical activity or nutrition data, to improve the accuracy of un-bolused meal detection.

The new inventive concept has significant commercial potential in the diabetes management market, particularly among patients with type 1 and type 2 diabetes who require insulin therapy. The system's ability to provide timely reminders and personalized meal bolus recommendations could improve diabetes therapy outcomes and reduce the risk of hypoglycemic events.