Medical System Network Graph Automated Configuration
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Solution Overview
Problem
Medical systems, particularly medical imaging systems, require significant training and experience to operate, and telemedicine advancements have not adequately addressed the challenge of automating the configuration and control of these devices for remote operation.
Innovation Solution
A medical system with a network graph comprising nodes and edges, where nodes have subject-specific metadata and edges have configuration metadata, allowing for automated configuration and control through a computational system that replicates network edges and establishes communication channels for remote control.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual configuration and operation of medical systems is used, then operational control and customization are maintained, but extensive training and experience are required and operational efficiency is reduced
Solution Approach 1:
The system creates a digital twin (virtual replica) of the physical medical device, including its configuration, state, and operational parameters. This digital twin can be manipulated and configured remotely without requiring the operator to physically interact with the device or have extensive training on its manual operation procedures.
Solution Approach 2:
The patent introduces a communication system with a gateway and network as an intermediary between the operator and the medical device. This intermediary layer handles the complex configuration and control protocols, translating high-level commands into device-specific operations, thereby shielding the operator from operational complexity.
2Productivity
If telemedicine and remote control of medical devices are implemented, then accessibility and operational efficiency are improved, but automated configuration and control capabilities are insufficient
Solution Approach 1:
By maintaining a digital twin that mirrors the physical device's state, the system enables automated configuration and control through the virtual replica. Commands can be issued to the digital twin, which automatically translates them to the physical device, reducing the need for manual intervention and enhancing automation capabilities in telemedicine scenarios.
Solution Approach 2:
The system pre-configures the digital twin with device specifications, operational parameters, and control logic before remote operation begins. This preliminary setup enables automated configuration during remote operation, as the system already has the necessary information structured and ready for automated processing.
3Adaptability or versatility
If comprehensive device configuration and control is provided, then operational capability and customization are enhanced, but system complexity and configuration difficulty increase
Solution Approach 1:
The patent segments the device configuration and control into distinct modular components within the digital twin architecture. Each functional aspect of the device can be independently configured and managed, allowing comprehensive adaptability without overwhelming system complexity. Operators can access and modify only the specific segments relevant to their needs.
Solution Approach 2:
The digital twin serves as a universal interface that can represent and control multiple different medical devices through a common platform. This multi-functionality allows the system to handle diverse device types with varying levels of complexity through a unified configuration approach, reducing the perceived complexity for operators.
Data Source
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AI summary
Disclosed here is a medical system (100, 400) comprising a memory (110) storing machine executable instructions (112) and a network graph (114, 114'). The network graph comprises network nodes (300) and network edges (302). At least a portion of the network nodes comprise node specific subject metadata. The network edges comprise configuration metadata comprises routing data for establishing a communication channel for communicating data between two network nodes of the network graph using a communication device. The execution of the machine executable instructions causes a computational system (104) to: create (200) a new node (116) comprising new subject metadata (118) in the network graph; search (202) for a closest matching network node (122) selected from the network nodes, and construct (204) new network edges (126) for the new node in the network graph by replicating of at least a portion of the network edges of the closest matching network node.