Intelligent Drug Delivery Controller with Multi-Axis Sensor Fusion
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Solution Overview
Problem
Conventional insulin pumps lack the ability to dynamically and proactively adjust insulin delivery rates in response to changing physiological and lifestyle events, leading to unpredictable blood glucose levels and inadequate compensation for activities like exercise or sleep patterns, resulting in suboptimal diabetes management.
Innovation Solution
A controller-based system that incorporates accelerometers, gyroscopic pitch sensors, and a data pattern matching algorithm to detect lifestyle events and adjust insulin delivery rates in real-time, using motion and orientation data to generate pump instruction signals for insulin pumps, allowing for dynamic adjustments based on user activity, sleep state, and food ingestion.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If conventional insulin pumps use rigid time-based delivery schedules, then the system is simple and reliable, but it cannot dynamically adapt to changing physiological and lifestyle events
Solution Approach 1:
The system uses accelerometers and gyroscopes to detect lifestyle events (exercise, sleep, eating) before they significantly impact blood glucose levels, allowing the insulin pump to proactively adjust delivery rates in anticipation of glucose changes rather than reacting after deviations occur
Solution Approach 2:
The system continuously monitors motion data from wearables, combines it with glucose readings, and uses this feedback loop to dynamically adjust insulin delivery rates in real-time, creating a closed-loop system that adapts to changing physiological states
2Reliability
If the system continuously monitors and adjusts insulin delivery in real-time, then blood glucose control improves, but the risk of over-correction and harmful factors increases
Solution Approach 1:
The system applies preliminary anti-action by detecting lifestyle events that will cause glucose changes (like exercise or sleep) and pre-adjusting insulin delivery to counteract these effects before they manifest, rather than reacting after glucose levels have already deviated
Solution Approach 2:
The system dynamically adjusts insulin delivery rates based on real-time motion data and glucose readings, allowing flexible, context-specific modifications to the basal rate that adapt to the user's current physiological state and activity level
3Measurement precision
If the system uses multiple sensors and real-time monitoring, then the ability to detect lifestyle events improves, but the device complexity and cost increase
Solution Approach 1:
The system uses a multi-functional approach where wearables with accelerometers and gyroscopes serve dual purposes: they track general fitness activities and simultaneously detect specific lifestyle events (sleep, exercise, eating) relevant to insulin delivery, eliminating the need for separate specialized sensors
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This system enables proactive management of blood glucose levels, reducing the risk of dangerous fluctuations and improving glucose control by aligning insulin delivery with actual insulin requirements, even during sleep or physical activity, and providing objective analysis of drug efficacy for conditions like Parkinson's disease.
Implementation Method 1
an accelerometer sensor arranged on the body and configured to output motion data based on detected motion
Implementation Method 2
a gyroscopic pitch sensor arranged on the body and configured to output orientation data based on detected orientation
Data Source
AI summary
A controller and associated multi-axis sensor system for augmenting the automatic intelligent delivery of one or more drugs is provided. The controller and associated multi-axial sensor system are based on the detection and determination of particular physical lifestyle events. As a specific example, a pump augmentation system includes a six-axis accelerometer sensor, a gyroscopic pitch sensor and a controller. The controller is configured to receive motion data from the six-axis accelerometer sensor and orientation data from the gyroscopic pitch sensor. The controller provides a pump instruction signal for changing a delivery rate of a drug to a user based on the motion data and the orientation data. The system and methods are particularly suited for treating a user with Parkinson's disease.