Embedded Drug Dosing Optimization for Low-Power Wearables
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Solution Overview
Problem
Conventional wearable drug delivery devices face challenges in implementing complex medication delivery algorithms due to limited processing capability and power consumption, making it difficult to execute optimization algorithms onboard, especially in disposable, small-scale electronics.
Innovation Solution
A simplified computational model is employed to approximate the optimization algorithm, allowing for reduced computational cost and power consumption by performing a stepwise exploration across search spaces, enabling the algorithm to be executed on wearable devices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a complex optimization algorithm is used to determine medication delivery, then the accuracy and precision of drug dosing is improved, but the computational cost and power consumption increase significantly
Solution Approach 1:
The patent applies partial action by implementing a simplified optimization algorithm that performs only the necessary computational steps required for drug dosing decisions. Instead of executing complex full optimization routines, the system uses reduced-order models and selective calculation approaches that provide sufficient dosing accuracy while dramatically reducing power consumption for embedded wearable devices
Solution Approach 2:
The patent changes computational parameters by adjusting the complexity level of optimization algorithms based on available processing resources. The system dynamically selects between simplified and comprehensive optimization approaches depending on device capabilities, transforming the fixed high-complexity algorithm into an adaptive parameter-based solution that balances precision and power consumption
2Measurement precision
If a complex optimization algorithm is used to determine medication delivery, then the accuracy and precision of drug dosing is improved, but the processing capability requirements increase
Solution Approach 1:
The patent implements partial action by executing only the essential computational operations needed for safe and effective drug delivery. The simplified optimization algorithm performs targeted calculations focusing on critical dosing parameters while omitting unnecessary computational steps, thereby reducing processing capability requirements while maintaining clinical accuracy
Solution Approach 2:
The patent applies segmentation by dividing the complex optimization algorithm into discrete, manageable computational modules. Each module performs a specific function in the dosing calculation process, allowing the system to execute only the necessary segments based on available processing power while maintaining overall dosing precision through coordinated operation of key computational blocks
3Speed
If the optimization algorithm is executed more frequently to maintain accurate dosing, then the responsiveness of the system is improved, but the computational burden and power consumption increase
Solution Approach 1:
The patent implements periodic action by executing the optimization algorithm at strategically determined intervals rather than continuously. The system calculates dosing recommendations at specific time points when clinical decisions are most needed, while using lighter computational tasks during intermediate periods, thereby maintaining responsive dosing control while reducing overall computational burden and power consumption
Data Source
AI summary
Disclosed herein is a method for execution by a drug delivery device for determining an optimal dose of a liquid drug for current cycle of a medication delivery algorithm, the method utilizing a stepwise evaluation of a model and a cost function across a coarse search space consisting of coarse discrete quantities of the drug and a refined search space consisting of refined discrete quantities of the drug.