Surgical Robot Navigation with Image-Based Patient Movement Tracking
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Solution Overview
Problem
Current surgical robot navigation systems face challenges in accurately tracking patient movement and adjusting surgical robot positions in real-time, leading to potential inaccuracies and safety issues during invasive and non-invasive procedures.
Innovation Solution
The implementation of image-based tracking techniques and torque sensing methods to detect patient movement, allowing for real-time adjustment of surgical robot positions and manual control initiation based on detected conditions, ensuring precise alignment with predetermined pathways and targets within the surgical environment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If real-time image-based tracking is implemented to detect patient movement, then surgical precision and safety are improved, but device complexity and computational requirements increase
Solution Approach 1:
The system continuously captures images of the patient, processes them to detect movement, and feeds this information back to adjust the surgical robot's position in real-time. This closed-loop feedback mechanism ensures the robot remains accurately positioned despite patient movement, directly improving surgical safety through real-time adaptation.
Solution Approach 2:
An image processing system acts as an intermediary between the patient and the surgical robot control. This intermediary component processes visual information and translates it into movement compensation commands, reducing the direct complexity burden on the robot control system while maintaining real-time tracking capability.
2Productivity
If automated robotic control is used for surgical procedures, then productivity and precision are improved, but adaptability to unexpected conditions deteriorates
Solution Approach 1:
The robotic system dynamically adjusts its control mode based on real-time surgical conditions. When automated control is needed for precision tasks, the system operates autonomously within predefined pathways. When unexpected conditions arise, the system can transition to manual control mode, providing adaptability while maintaining high productivity during routine procedures.
Solution Approach 2:
The system changes operational parameters such as control mode (automated vs. manual), robot speed, and positioning precision based on detected surgical conditions. This parameter adaptation allows the system to optimize productivity for routine tasks while maintaining flexibility when conditions require human intervention.
3Adaptability or versatility
If manual control is implemented during surgical procedures, then adaptability to unexpected conditions is improved, but precision and productivity deteriorate
Solution Approach 1:
Even during manual control mode, the system provides continuous feedback by displaying real-time patient position and robot status information to the operator. This feedback mechanism helps the manual operator maintain precision by being aware of the current state, bridging the gap between manual flexibility and automated precision.
Solution Approach 2:
The image processing and display system serves as an intermediary that enhances the operator's situational awareness during manual control. By visualizing real-time patient movement and robot position, the intermediary system enables more precise manual operations while maintaining adaptability to unexpected conditions.
4Measurement precision
If continuous real-time tracking is performed, then measurement precision of patient movement is improved, but use of energy and computational resources increase
Solution Approach 1:
The system performs image capture and processing at periodic intervals rather than continuously, analyzing patient movement at key moments during the surgical procedure. This periodic approach maintains sufficient measurement precision for safety while significantly reducing computational energy consumption compared to continuous real-time processing.
Solution Approach 2:
The system maintains continuous monitoring capability through efficient image processing algorithms that can quickly analyze and interpret patient movement data. This allows the system to process images at high speeds with minimal computational delay, maintaining the appearance of continuous action while managing energy resources efficiently.
Data Source
AI summary
Systems and methods for controlling and navigating robots in a surgical environment are disclosed. The systems and methods described herein provide techniques to adjust the location of a robot, such as a surgical robot, in response to detecting movement of a patient using image-based tracking techniques. Techniques are provided that enables a robot control system to adjust a position of a surgical robot in real-time or near real-time in response to measurements from sensors coupled to the robot or a patient in a surgical environment. Techniques for initiating a collaborative control status of a surgical robot in response to detecting image alignment errors, sensor measurements, or other conditions are disclosed.