AI Robotic Surgery Feedback Control for Adaptive Instrument Positioning
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Solution Overview
Problem
Current robotic surgical systems lack advanced intelligence for real-time tissue property analysis, secure data ecosystems, and autonomous positioning, which limits their precision and adaptability during surgical procedures.
Innovation Solution
An integrated AI-powered robotic surgery system with a feedback loop and AI architecture that processes input data for instrument positioning, adjusts operation parameters in real-time, and includes a secure data ecosystem for collaborative surgery.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional robotic surgical systems are used, then basic surgical procedures can be performed, but real-time tissue property analysis and adaptive positioning are not available
Solution Approach 1:
The system segments the robotic surgical system into multiple independent modules: AI engine for tissue analysis, feedback loop for real-time monitoring, control system for instrument positioning, and sensor array for data collection. Each module performs a specific function and can be developed, tested, and maintained independently, reducing overall system complexity while enabling advanced tissue property analysis capabilities.
Solution Approach 2:
An AI engine is introduced as an intermediary component that processes raw sensor data about tissue properties and translates it into actionable insights for the control system. This intermediary layer enables sophisticated tissue analysis without requiring direct complex interactions between sensors and control mechanisms, thereby improving measurement precision while managing system complexity.
2Manufacturing precision
If real-time feedback adjustment is implemented, then surgical precision is improved, but system complexity and computational requirements increase
Solution Approach 1:
The system performs preliminary actions by pre-processing sensor data and pre-calculating optimal instrument positions before actual surgical manipulation. The AI engine continuously analyzes tissue properties and pre-adjusts positioning parameters, allowing the control system to execute precise movements with reduced computational complexity during critical surgical moments.
Solution Approach 2:
A closed-loop feedback system is implemented where sensors continuously monitor tissue properties and instrument positions, the AI engine analyzes this data in real-time, and the control system automatically adjusts instrument positioning. This feedback mechanism improves positioning precision by constantly comparing actual positions with target positions and making corrective adjustments, while the modular architecture keeps control complexity manageable.
3Adaptability or versatility
If autonomous positioning with environmental modeling is added, then surgical adaptability is enhanced, but device complexity increases
Solution Approach 1:
Environmental modeling is performed as a preliminary action before surgical procedures begin. The system creates a digital representation of the surgical environment and patient anatomy based on pre-operative imaging and real-time sensor data. This pre-established model allows the autonomous positioning system to adapt to different surgical scenarios without requiring complex real-time decision-making, thereby enhancing surgical adaptability while managing system complexity.
4Reliability
If secure collaborative data ecosystem is implemented, then data security and collaboration are improved, but system complexity increases
Solution Approach 1:
The data ecosystem is segmented into distinct functional layers: data collection from sensors, data processing by AI engine, secure storage in databases, and controlled access for collaboration. Each layer has specific security protocols and access controls, allowing robust data security without requiring a monolithic complex security system. This modular data architecture enables secure collaborative access while managing data management complexity.
Data Source
AI summary
A robotic surgical system. a surgeon console operatively coupled to a patient console and one or more surgical instruments. A surgeon computer is coupled to or integrated with the surgeon console, the surgeon computer further operatively connected to the one or more surgical instruments; A surgical robot is coupled to a robotic surgery control system and a feedback loop. The robotic surgery control system includes or is coupled to an artificial intelligence (AI) system. A feedback loop is further configured to receive performance-related data from the one or more sensors, the data analyzed by the robotic surgery control system or the AI system to dynamically adjust the robotic system's operation as needed. A data extraction module retrieves, from the robotic surgery control system or the AI system. one or more programmed steps executed by the surgeon for positioning at least one of the surgical instruments during the surgical procedure.