Robotic Joint Arthroscopy System with 3D Workflow Planning
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Solution Overview
Problem
Conventional surgical methods are inadequate in preventing surgical errors and adverse events during robotic joint arthroscopic surgery, due to communication breakdowns and technical errors, leading to complications such as anesthesia issues, hemorrhaging, and infections.
Innovation Solution
A robotic surgical system utilizing machine learning to analyze historical patient data, generate precise surgical workflows, and provide real-time assistance through multi-modality imaging and automated robotic movements, reducing the need for invasive procedures and enhancing diagnostic accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional communication-based methods are used to prevent surgical errors, then implementation is simple, but reliability is insufficient to prevent adverse events
Solution Approach 1:
The system performs preliminary actions by pre-planning the surgical procedure using medical images to create a three-dimensional model, pre-identifying anatomical structures and potential risks before the actual surgery begins. This advance preparation enables real-time comparison and error prevention during surgery.
Solution Approach 2:
The system implements continuous feedback by comparing real-time surgical robot position and actions against the pre-planned procedure and three-dimensional anatomical model. This real-time feedback mechanism detects deviations and prevents surgical errors immediately when they occur.
2Reliability
If traditional surgical procedures are performed, then surgical errors can occur, but the procedure is straightforward
Solution Approach 1:
The robotic surgical system integrates multiple functions including automated robot control, real-time imaging acquisition and processing, three-dimensional model generation, surgical plan creation, and intraoperative navigation within a single unified platform, reducing the need for separate systems while enhancing safety.
Solution Approach 2:
The system introduces an intermediary computational layer that acts as a mediator between the surgeon's intent and the robotic execution. This intermediary processes medical images, generates three-dimensional models, creates surgical plans, and guides robot movements, ensuring safety without requiring the surgeon to directly control every robotic action.
3Manufacturing precision
If more invasive procedures are used to ensure surgical accuracy, then precision improves, but recovery time increases and scarring worsens
Solution Approach 1:
The system replaces traditional mechanical surgical approaches with image-guided robotic automation. By substituting manual mechanical surgery with computer-controlled robotic systems guided by three-dimensional imaging and pre-planned procedures, the system achieves higher precision through automated positioning and execution while maintaining minimally invasive benefits.
Data Source
AI summary
Methods, apparatuses, and systems for performing robotic joint arthroscopic surgery are disclosed. The disclosed systems use a surgical robot network that receives medical images of a patient and generates a 3D rendering of the various medical images. A surgeon or physician is enabled to select workflow objects (such as various tools). The workflow objects can be selected in a sequence for performing actions on the 3D rendering. Data related to the workflow objects and actions in relation to the 3D rendering are stored. The surgeon or physician is enabled to select and perform various repairing techniques and input calculations of the actions performed. The user inputs, workflow objects, and actions with respect to the 3D rendering are sent to a surgical robot for performing robotic joint arthroscopic surgery.