Computer-Vision Surgical Tool Control for Field-of-View Safety
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Solution Overview
Problem
Surgical tools can cause patient injury due to erroneous handling during surgical procedures, necessitating improved safety and reliability in surgical tool control.
Innovation Solution
Utilizing computer-vision processing systems to train machine-learning models that recognize surgical tools and anatomical structures, enabling controlled operation of surgical tools based on their presence within the camera's field of view, and adjusting tool functionality accordingly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If surgical tools are used during surgical procedures, then surgical operations can be performed, but patient injury can occur due to erroneous handling
Solution Approach 1:
The system continuously monitors the surgical field using computer vision and provides real-time feedback to the control system. When the surgical tool is detected outside the field of view or in unsafe positions, the system automatically adjusts tool operation or disables functionality to prevent patient injury
Solution Approach 2:
The patent introduces an intermediary computer vision system between the surgical tool and the patient. This intermediary monitors tool position and operation continuously, acting as a safety layer that can intervene to prevent harmful actions before they occur
2Reliability
If computer-vision processing is implemented to monitor surgical tools, then patient safety is improved, but system complexity increases
Solution Approach 1:
The computer vision system serves multiple functions simultaneously: it monitors tool position, verifies surgical steps completion, provides safety oversight, and enables automated control decisions. This multi-functionality reduces the need for separate dedicated systems for each function
Solution Approach 2:
The surgical system performs self-monitoring and self-regulation through the integrated computer vision system. The system automatically detects tool positions, identifies anatomical structures, and adjusts operation parameters without requiring external monitoring equipment or manual verification
3Reliability
If surgical tool operation is automatically controlled based on field of view detection, then erroneous handling is prevented, but operational flexibility is reduced
Solution Approach 1:
The control system dynamically adjusts tool operation based on real-time detection of tool position and surgical context. When the tool is within the field of view and proper surgical steps are confirmed, full functionality is restored, providing dynamic adaptability rather than static restriction
Data Source
AI summary
The present disclosure relates to systems and methods that use computer-vision processing systems to improve patient safety during surgical procedures. Computer-vision processing systems may train machine-learning models using machine-learning techniques. The machine-learning techniques can be executed to train the machine-learning models to recognize, classify, and interpret objects within a live video feed. Certain embodiments of the present disclosure can control (or facilitate control of) surgical tools during surgical procedures using the trained machine-learning models.