Parameterizing Medical Procedure Records for Robot-Assisted Surgery
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Solution Overview
Problem
Current medical procedures lack effective systems for parameterizing and analyzing the characteristic actions and parameters of minimally invasive medical procedures, which hinders the optimization of clinical practices and training methods.
Innovation Solution
A method and system for receiving and analyzing medical procedure records to identify common characteristic actions and determine associated parameters, using a robot-assisted medical system with a control system that captures and processes data from various sensors and recording systems to generate parameterized medical procedure records.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If medical procedure records are aggregated and analyzed to identify characteristic actions and parameters, then procedure efficiency and training quality are improved, but system complexity and data processing requirements increase
Solution Approach 1:
The system segments medical procedure records into discrete characteristic actions (e.g., cutting, grasping, suturing) and associates parameters with each action type. This segmentation allows for targeted analysis of specific procedural elements rather than treating entire procedures as monolithic units, improving efficiency while managing complexity through modular data organization.
Solution Approach 2:
The system transforms unstructured medical procedure records into structured data by extracting and parameterizing characteristic actions. Each action is represented with specific parameters (duration, force, position, etc.), converting qualitative procedural data into quantitative metrics that can be efficiently analyzed and compared across multiple procedures.
2Measurement precision
If detailed parameters are extracted and analyzed from medical procedure records, then training and assessment accuracy are improved, but data processing time and computational resources increase
Solution Approach 1:
The system extracts only the most relevant characteristic actions and their associated parameters from complete medical procedure records. By identifying and isolating key procedural elements (such as critical surgical steps) rather than analyzing every detail of the procedure, the system achieves high assessment accuracy for training purposes while minimizing unnecessary data processing time.
3Reliability
If robot-assisted medical systems implement comprehensive data collection and parameterization, then clinical outcomes are improved, but device complexity and operational overhead increase
Solution Approach 1:
The system is designed to handle multiple types of medical procedures and characteristic actions through a unified parameterization framework. The same data collection and analysis infrastructure supports various surgical disciplines and procedure types, improving clinical outcomes through consistent measurement standards while avoiding the need for separate specialized systems for each procedure type.
Data Source
AI summary
A robot-assisted medical system comprises a manipulator arm, an operator console, a medical instrument coupled to the manipulator arm, and a control system in communication with the operator console and the manipulator arm. The control system comprises a processor and a memory comprising machine readable instructions. When executed by the processor, the machine readable instructions may cause the control system to receive a plurality of medical procedure records, identify a set of characteristic actions common among the plurality of medical procedure records, and determine at least one parameter for each characteristic action in the set of characteristic actions.