Wearable Insulin Delivery Exercise Safety Prediction From Physiology
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Solution Overview
Problem
Patients with diabetes face challenges in maintaining blood glucose levels during or after exercise, particularly due to increased insulin sensitivity and the risk of hypoglycemic events, especially when high insulin is onboard or after a bolus, leading to fear of exercising.
Innovation Solution
A wearable drug delivery device with a processor, pump mechanism, and reservoir that evaluates physiological conditions to determine exercise safety, generating signals and modifying medication treatment plans to prevent hypoglycemia, and adjusts insulin delivery based on exercise participation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If insulin delivery is increased to manage blood glucose levels, then blood glucose control is improved, but the risk of hypoglycemia during exercise increases
Solution Approach 1:
The system performs preliminary evaluation of physiological conditions (insulin onboard levels, recent bolus history, exercise parameters) before exercise begins and proactively adjusts insulin delivery settings in advance. This prevents hypoglycemia by anticipating the interaction between exercise and insulin action rather than reacting after glucose levels drop.
Solution Approach 2:
The system continuously monitors physiological parameters and uses this feedback to dynamically adjust insulin delivery recommendations during exercise. The closed-loop feedback mechanism allows real-time modification of insulin settings based on actual glucose trends and exercise intensity, balancing blood glucose control with hypoglycemia prevention.
2Ease of operation
If exercise is permitted without restrictions, then lifestyle quality is improved, but hypoglycemic events may occur
Solution Approach 1:
The system dynamically changes operational parameters (insulin delivery rates, safety thresholds, evaluation criteria) based on exercise type, intensity, and individual physiological conditions. This allows flexible exercise permissions that adapt to specific scenarios rather than applying rigid restrictions, maintaining both freedom and safety.
Solution Approach 2:
The system empowers patients to self-manage their exercise decisions by providing personalized safety evaluations and recommendations. Patients receive actionable guidance about whether their specific exercise plan is safe given their current insulin status, enabling informed self-service decisions without requiring constant medical supervision.
3Reliability
If exercise safety evaluation is performed, then hypoglycemia risk is reduced, but system complexity increases
Solution Approach 1:
The safety evaluation system is segmented into distinct functional modules: data collection from multiple sources, physiological condition assessment, exercise parameter validation, risk calculation, and recommendation generation. This modular segmentation makes the complex evaluation process more manageable and implementable within the wearable device architecture.
Data Source
AI summary
Described are techniques, processes, devices, computer-readable media that enable provision of an indication of whether it is safe for a person with diabetes to participate in exercise while using a wearable drug delivery system. A processor may receive or obtain physiological data related to a condition of a wearer of the wearable drug delivery system and by evaluating an exercise model that uses inputs related to the physiological data to make the determination of whether it is safe to exercise and output an exercise safety signal. Modifications to the wearer's medication treatment plan and other actions may be based on an outputted exercise safety signal.