Surgical Workflow Variation Quantification Using Adaptive Dynamic Time Warping
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Solution Overview
Problem
Current computer-assisted surgery systems face challenges in objectively quantifying variations in surgical approaches due to limitations in aligning workflows of different lengths and handling categorical data, leading to biased entropy calculations when analyzing large datasets.
Innovation Solution
The system employs adaptive dynamic time warping-barycenter-averaging (ADBA) modified for categorical data, using medoid sequences as initial averages and mode values for optimization, along with the Chao-Shen estimator to reduce bias and scale entropy values, allowing for accurate comparison of surgical workflows across different hospitals and procedures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional entropy calculation methods are used to analyze surgical workflows, then the analysis can be performed on large datasets, but the results suffer from bias and inaccuracy due to limitations in aligning workflows of different lengths and handling categorical data
Solution Approach 1:
The patent transforms the entropy calculation approach by changing the parameters used for workflow alignment. Instead of using traditional methods that assume continuous data and fixed workflow lengths, the patent applies categorical data handling techniques and variable length alignment algorithms. This allows accurate entropy calculation on large datasets with diverse surgical workflows of different lengths and categories.
2Stability of the object's composition
If workflows of different lengths are aligned using traditional methods, then the alignment process can be completed, but data loss and bias occur due to inability to properly handle variable length sequences
Solution Approach 1:
The patent applies dynamic alignment methods that can adapt to variable length workflows. The system uses dynamic time warping and similar techniques that allow workflows of different lengths to be aligned without forcing artificial truncation or repetition. This dynamic approach maintains the original data composition while achieving consistent alignment across diverse surgical procedures.
3Device complexity
If subjective analysis methods are used to compare surgical procedures, then the analysis process is simpler, but the results are error-prone due to the volume of data and numerous factors affecting each procedure
Solution Approach 1:
The patent replaces subjective human analysis with an automated computational system. The system uses algorithmic entropy calculation and workflow alignment methods to objectively compare surgical procedures. This substitution eliminates human bias and error while handling the large volume of data and multiple varying factors across different surgical procedures.
Data Source
AI summary
An aspect includes a computer-implemented method that quantifies variations in surgical approaches to medical procedures. Surgical videos documenting multiple cases of a medical procedure are analyzed to identify variations in surgical approaches used by service providers when performing the medical procedure. According to some aspects, the variation in surgical approaches is quantified.