Surgical Hub for Device Integration and Data Management
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Solution Overview
Problem
Existing surgical systems face challenges in efficiently managing and integrating various surgical devices and data systems, leading to inefficiencies and a lack of connectivity between medical facilities.
Innovation Solution
A computer-implemented interactive surgical system that includes a surgical hub connected to a cloud-based system, enabling communication and coordination between various surgical devices, visualization systems, and robotic systems, as well as providing a platform for data management and analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If surgical systems integrate multiple devices and data systems, then system functionality and data availability improve, but device complexity and integration difficulty increase
Solution Approach 1:
A central hub device serves as an intermediary component that receives data from multiple surgical devices (energy generators, robotic systems, visualization systems) and provides centralized control. This hub architecture simplifies integration by providing standardized communication interfaces and centralized data management, reducing the complexity of direct peer-to-peer connections between diverse surgical devices.
Solution Approach 2:
The surgical system employs universal communication protocols and standardized data formats that enable different surgical devices to interoperate through a common interface. The hub device performs multiple functions including data aggregation, processing, storage, and distribution, eliminating the need for device-specific integration solutions and reducing overall system complexity.
2Productivity
If real-time data communication between surgical devices is implemented, then surgical efficiency and decision-making improve, but system complexity and communication overhead increase
Solution Approach 1:
The central hub acts as a communication intermediary that consolidates data transmission from multiple surgical devices. Instead of requiring direct real-time communication channels between all device pairs, the hub centralizes the communication infrastructure, reducing the number of communication channels needed and simplifying the network architecture while maintaining real-time data availability.
Solution Approach 2:
The system merges multiple data streams from different surgical devices into a unified data structure at the hub. This consolidation approach reduces communication overhead by transmitting aggregated data rather than separate data streams for each device interaction, improving surgical efficiency while reducing system complexity.
3Loss of information
If cloud-based data management and analytics are implemented, then data analysis capability and decision-making improve, but data transmission requirements and system dependency increase
Solution Approach 1:
The system extracts and separates heavy computational analytics functions from the local surgical environment and relocates them to cloud-based processing resources. This allows the local surgical system to maintain minimal data processing capabilities while leveraging powerful cloud-based analytics engines for complex data analysis, reducing local hardware requirements and data transmission bandwidth needs.
Solution Approach 2:
The hub device performs preliminary data processing, filtering, and preprocessing of surgical data before transmitting information to the cloud. By preparing and optimizing data locally beforehand, the system reduces the quantity and complexity of data that needs to be transmitted to cloud-based analytics platforms, minimizing network bandwidth requirements while maintaining comprehensive data analysis capabilities.
Data Source
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AI summary
A surgical feedback system includes a surgical instrument, a data source, and a surgical hub configured to communicably couple to the data source and the surgical instrument. The surgical hub has a control circuit, wherein the control circuit is configured to receive an input from the data source, analyze the received data against a stored set of data to optimize an outcome of a surgical procedure, and communicate a recommendation based on the analyzed data.