Surgical Data Pipeline Remapping Under Bandwidth Constraints
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Solution Overview
Problem
Existing surgical systems lack dynamic and real-time adaptability in managing data pipelines during procedures, leading to inefficiencies and potential disruptions due to varying patient parameters, system status changes, and data integrity issues.
Innovation Solution
A surgical data management system that dynamically changes data pipeline mappings in response to trigger events during procedures, including altering destinations, sources, flow rates, transformation points, and communication protocols to ensure seamless data transmission and integrity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a static data pipeline mapping is used in surgical systems, then system stability is maintained, but data transmission efficiency and responsiveness deteriorate during dynamic surgical procedures
Solution Approach 1:
The patent implements dynamic data pipeline mapping by allowing the surgical hub to modify data pipeline configurations in real-time based on trigger events during surgical procedures. The system transitions from static to dynamic mapping, enabling adaptive data routing that responds to changing surgical conditions while maintaining manageable complexity through automated adjustment mechanisms.
2Loss of time
If real-time dynamic data pipeline adjustments are implemented, then data transmission responsiveness improves, but system stability and reliability may deteriorate
Solution Approach 1:
The system incorporates feedback mechanisms where trigger events from surgical procedures dynamically adjust data pipeline mappings. The surgical hub monitors surgical conditions and automatically modifies data routing based on real-time feedback, reducing transmission delays while maintaining stability through condition-based automated adjustments rather than arbitrary changes.
Solution Approach 2:
The patent implements preliminary configuration of data pipelines with predefined mapping rules and trigger conditions. When trigger events occur, the system executes pre-planned adjustments rather than creating new mappings on-the-fly, which reduces instability while achieving real-time responsiveness. The automated nature of these pre-defined actions ensures consistent and reliable execution.
3Adaptability or versatility
If multiple data pipelines are added to handle diverse surgical data types, then data processing capability improves, but system complexity and difficulty of management increase
Solution Approach 1:
The surgical hub serves as a universal data management platform that handles multiple data types (patient data, surgical procedure data, surgical instrument data) through a single integrated system. Rather than requiring separate specialized systems for each data type, the hub provides unified data pipeline management that adapts to different data processing needs through configurable mappings and trigger-based automation.
Data Source
AI summary
Surgical systems and related computer-implemented methods are provided, including during performance of a surgical procedure on a patient, receiving, at a first surgical system, a first dataflow from a second surgical system, the first dataflow including first data regarding a measured patient parameter that the first surgical system is configured to use in performing a function during the performance of the surgical procedure. The computer-implemented methods including determining that a trigger event occurred during the performance of the surgical procedure such that a sum of a first bandwidth of the first dataflow and a second bandwidth of a second dataflow exceeds an available bandwidth, and in response to determining that the trigger event occurred, and during the performance of the surgical procedure, adjusting at least one of the first and second dataflows such that the sum of the first and second bandwidths does not exceed the available bandwidth.