Insulin Delivery and Activity Detection for Glucose Response Control
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Solution Overview
Problem
Existing insulin infusion devices lack the ability to accurately correlate physical activity with physiological responses to adjust insulin delivery effectively, particularly when blood glucose levels are above target, leading to potential fluctuations.
Innovation Solution
A system that integrates an activity detection system with an insulin infusion device, utilizing an activity correlation database to recommend physical activities to manage blood glucose levels by correlating exercise with physiological changes, thereby adjusting insulin delivery.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If insulin infusion devices continuously monitor and adjust insulin delivery based on blood glucose levels, then blood glucose control is improved, but the system cannot account for physical activity effects leading to potential fluctuations
Solution Approach 1:
The system continuously monitors blood glucose levels via sensor data and compares them against target ranges. When glucose levels deviate from the target range, the control algorithm adjusts insulin delivery rates accordingly. This closed-loop feedback mechanism enables real-time adaptation to changing physiological conditions, including physical activity effects, thereby improving both glucose control accuracy and responsiveness to activity without requiring manual user input.
2Adaptability or versatility
If the system integrates activity detection and correlates it with physiological responses, then personalized exercise recommendations can be provided, but device complexity increases
Solution Approach 1:
The system integrates multiple functions into a unified platform: continuous glucose monitoring, activity detection through wearable devices, physiological response correlation, and personalized recommendation generation. By combining these diverse functions under a single control algorithm that processes multiple data streams, the system achieves multi-functionality without proportionally increasing complexity. The activity correlation database serves as a universal reference that enables personalized recommendations across different activity types and users.
Data Source
AI summary
Systems and related operating methodologies are disclosed. An exemplary operating method obtains sensor data that indicates a physiological characteristic of the user, the sensor data provided by an analyte sensor, and determines that a current level of the physiological characteristic differs from a user-specific target level by a quantifiable amount. The method continues by searching an activity correlation database to locate one or more physical activity events correlated with the quantifiable amount of the physiological characteristic. The activity correlation database is populated with event-correlated physiological responses that associate physical activity events with corresponding changes in the physiological characteristic. A recommendation is provided for the user. The recommendation specifies the one or more physical activity events.