Autonomous Imaging Rule Engine for Patient Safety and Throughput
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Solution Overview
Problem
Current autonomous imaging systems lack a well-defined methodology to manage imaging procedures, including starting, stopping, or aborting scans, and ensuring patient suitability and safety, which can lead to untoward situations due to a lack of rigorous criteria and subjective human intervention.
Innovation Solution
A rule engine apparatus is introduced that evaluates autonomous scan procedures by processing data from various sources, including sensors and machine settings, to determine readiness indices and control imaging apparatus actions such as 'start', 'stop', or 'abort', using a master rule engine unit and workflow step rule engine units to ensure patient and device readiness.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If autonomous imaging procedures are implemented without a well-defined methodology, then patient throughput increases and operational costs reduce, but safety risks increase and untoward situations may occur
Solution Approach 1:
The rule engine evaluates multiple readiness criteria (patient suitability, device readiness, workflow preparation) before initiating autonomous imaging procedures. This preliminary assessment ensures all necessary conditions are met before automation begins, preventing safety incidents while maintaining throughput.
Solution Approach 2:
The system continuously monitors workflow status and readiness indices during autonomous operation, providing real-time feedback to adjust operations. This feedback mechanism allows the system to respond to changing conditions, maintaining safety while optimizing patient throughput and operational efficiency.
2Productivity
If rigorous criteria and reduced human intervention are implemented, then operational efficiency increases and variability reduces, but system complexity increases
Solution Approach 1:
The rule engine is divided into multiple workflow step rule engine units, each responsible for specific readiness criteria (patient suitability, device status, workflow preparation). This segmentation makes the complex system more manageable and maintainable while enabling comprehensive evaluation of multiple readiness factors simultaneously.
Solution Approach 2:
The autonomous imaging system uses self-contained rule engine units that independently evaluate their specific readiness criteria and contribute to overall workflow decisions. This self-service approach reduces the need for centralized complex control, improving operational efficiency while distributing system complexity across modular units.
3Reliability
If multiple readiness criteria are evaluated before imaging, then safety improves and untoward situations are prevented, but processing time increases
Solution Approach 1:
Readiness criteria are evaluated in advance before imaging procedures begin, and the system maintains cached readiness states for ongoing workflows. This preliminary action prevents safety incidents while minimizing real-time processing delays, as most evaluation work is completed before imaging starts.
Solution Approach 2:
The rule engine continuously monitors readiness criteria during autonomous operation rather than performing discrete batch evaluations. This continuous monitoring maintains safety assurance while optimizing processing timing, allowing the system to make immediate decisions based on current workflow status without unnecessary delays.
Data Source
AI summary
The present invention relates to autonomous imaging. A system and method is proposed that automatically evaluates the readiness index of an autonomous scan procedure and continuously evaluates whether to continue, pause, or about the imaging procedure.