Dynamic Treatment Protocol Adjustment in Autonomous Medical Devices
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Solution Overview
Problem
Existing medical treatment systems require careful manual adjustment and monitoring of treatment parameters, limiting their efficiency and autonomy in delivering optimal patient outcomes.
Innovation Solution
A medical device system that dynamically adjusts treatment protocols based on real-time sensor data and patient feedback, allowing for automatic optimization of treatment parameters within safe limits, while restricting adjustments outside approved ranges.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If manual adjustment and monitoring of treatment parameters is performed, then treatment safety is maintained, but treatment efficiency and autonomy are limited
Solution Approach 1:
The system continuously monitors patient response to treatment and automatically adjusts treatment parameters based on real-time feedback. Sensors detect physiological parameters and treatment outcomes, which are fed back to the control system that modifies treatment delivery accordingly, enabling autonomous optimization while maintaining safety through continuous monitoring
Solution Approach 2:
The treatment system performs self-adjustment of treatment parameters without requiring manual intervention. The device autonomously optimizes treatment protocols by processing sensor data and making parameter modifications independently, reducing reliance on manual monitoring while maintaining treatment safety through built-in control algorithms
2Adaptability or versatility
If treatment parameters are fixed according to approved protocols, then treatment safety is ensured, but treatment optimization for individual patient needs is limited
Solution Approach 1:
The system transitions from static, fixed treatment parameters to dynamic, adaptive parameters that change in real-time based on patient response. Treatment protocols are continuously adjusted within approved ranges to optimize effectiveness for individual patient needs while maintaining compliance through boundary constraints
Solution Approach 2:
The system modifies treatment parameters such as dosage, frequency, and duration based on real-time sensor data and patient feedback. These parameter changes are automatically made within the boundaries of approved protocols, allowing customization while ensuring compliance through programmed constraints
3Productivity
If automatic incremental adjustment of treatment parameters is permitted, then treatment efficiency is improved, but risk of unsafe operation increases
Solution Approach 1:
The system pre-establishes safe operating boundaries and constraints for treatment parameters before automatic adjustment begins. Approval ranges and safety limits are defined in advance, creating a protected space within which automatic incremental adjustments can occur without risking unsafe operation
Solution Approach 2:
The system rapidly iterates through treatment parameter adjustments within safe boundaries, quickly optimizing treatment effectiveness. Multiple incremental changes are made in succession within the approved range, accelerating the optimization process while the pre-established boundaries prevent crossing into unsafe zones
Data Source
AI summary
Systems, and methods relate to a medical device receiving a treatment parameter operating point within a first operating region defined by a first set of operating points for which automatic incremental adjustment of a parameter in the current operation is permitted. In an illustrative example, incremental adjustment may use artificial intelligence based on patient feedback and sensor measurement of outcomes. Some exemplary devices may receive a request to alter the current treatment parameter operating point to a second treatment parameter operating point outside the first operating region and in a second operating region in a known safe operation zone, bounded by a known unsafe zone unavailable to the user. In the second operating region, some examples may restrict the step size of incremental adjustments requested by the user. Data may be collected for cloud-based analysis, for example, to facilitate discovery of more effective treatment protocols.


