Surgical Skill Quantification via Motion Data Segmentation
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Solution Overview
Problem
Current virtual training systems for surgical skills lack an objective method to quantify clinical technical skill, leading to inadequate training and increased mistakes, as they struggle to distinguish between skilled and unskilled operators based on motion data variability.
Innovation Solution
A method and system for quantifying clinical skill using data collected from surgical robots, comparing skilled and unskilled user performances to determine expertise levels, and providing objective feedback for training improvement, employing a computer program with modules for data segmentation, comparison, and teaching to enhance proficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If motion data is collected from multiple task performances to assess skill, then more data is available for analysis, but the data becomes more variable and harder to interpret due to natural motion variations
Solution Approach 1:
The patent segments motion data into discrete events with specific phases (approach, contact, manipulation, release) and parameters (position, velocity, acceleration, force). This segmentation transforms continuous variable motion data into structured, comparable event units, allowing precise skill assessment despite natural variations in repeated tasks.
Solution Approach 2:
The patent transforms motion data from raw positional information into derived parameters including velocity, acceleration, force, and timing metrics. This parameter transformation enables more precise skill assessment by capturing dynamic characteristics that are not apparent in position data alone, resolving the precision problem while utilizing large quantities of motion data.
2Adaptability or versatility
If traditional subjective assessment methods are used for surgical skill, then flexibility in evaluation is maintained, but objectivity and consistency in skill quantification are lost
Solution Approach 1:
The patent implements automated feedback systems that provide objective, consistent skill assessments based on quantified motion parameters. The system compares measured parameters against predefined criteria and provides standardized feedback, maintaining objectivity while allowing adaptability through configurable assessment protocols and customizable parameter thresholds for different surgical tasks.
Solution Approach 2:
The patent creates a universal assessment framework that can evaluate multiple surgical skills across different tasks using the same objective measurement principles. The system handles various motion types (positioning, cutting, suturing) and task complexities through a unified parameter-based approach, providing both objectivity and versatility simultaneously.
3Measurement precision
If detailed motion parameters are measured to improve skill assessment accuracy, then more information is obtained about operator performance, but system complexity and data processing requirements increase
Solution Approach 1:
The patent extracts only the most relevant motion parameters needed for skill assessment from the complete set of available data. By identifying and extracting key parameters (position, velocity, acceleration, force, timing) associated with critical event phases, the system achieves high assessment accuracy without requiring complex processing of all possible motion variables, thus reducing system complexity while maintaining precision.
4Adaptability or versatility
If multiple parameters are monitored simultaneously to capture comprehensive skill performance, then more aspects of performance are evaluated, but data analysis and interpretation become more difficult
Solution Approach 1:
The patent segments multi-parameter data into discrete event phases (approach, contact, manipulation, release) with specific parameters relevant to each phase. This segmentation organizes comprehensive performance data into structured, phase-specific information, making analysis more manageable while maintaining comprehensive evaluation of all performance aspects through the segmented framework.
Data Source
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AI summary
A system and method for quantifying clinical skill of a user, comprising: collecting data relating to a surgical task done by a user using a surgical device; comparing the data for the surgical task to other data for another similar surgical task; quantifying the clinical skill of the user based on the comparing of the data for the surgical task to the other data for the other similar surgical task; outputting the clinical skill of the user.