Surgical Planning System for Range of Motion Analysis
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current surgical planning systems lack the capability to effectively categorize patient populations anatomically and simulate range of motion for personalized orthopedic procedures, leading to suboptimal implant placement and postoperative outcomes.
Innovation Solution
A surgical planning system that categorizes patients into anatomical makeup classifications, performs range of motion simulations, and adjusts implant plans based on posture parameters, using a processor to register bone models from a local to a global reference system and generate surgical plans for improved orthopedic procedure planning.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional surgical planning methods are used, then the surgical process is simpler and faster, but the accuracy of implant placement and postoperative outcomes are suboptimal
Solution Approach 1:
The surgical planning system segments the patient population into distinct anatomical makeup classifications (e.g., narrow, average, wide categories) based on anatomical parameters. This segmentation allows the system to provide tailored implant placement recommendations for each category, improving accuracy without requiring complex individualized analysis for every patient.
Solution Approach 2:
The system performs preliminary range of motion simulations and anatomical classifications before the actual surgery. By pre-calculating the optimal implant placement for each anatomical category and simulating range of motion outcomes, the system prepares personalized surgical plans in advance, improving surgical accuracy while maintaining efficient intraoperative execution.
2Adaptability or versatility
If anatomical classification and range of motion simulation are implemented, then personalized surgical planning is achieved, but the computational requirements and processing time increase
Solution Approach 1:
By categorizing patients into discrete anatomical groups (narrow, average, wide), the system reduces the continuous complexity of individual anatomical variations into manageable segments. This allows pre-computed range of motion simulations and implant recommendations to be efficiently retrieved and applied, providing personalized care without excessive processing time.
Solution Approach 2:
The system changes the parameter representation from continuous individual measurements to discrete categorical classifications. This transformation enables the use of lookup tables and pre-computed simulation results for each category, significantly reducing real-time computational requirements while maintaining personalized surgical planning capability.
3Manufacturing precision
If detailed anatomical classification is performed, then implant placement accuracy improves, but the complexity of data processing and system requirements increase
Solution Approach 1:
The system divides complex anatomical data into segmented categories based on key parameters such as anatomical makeup classifications. This segmentation simplifies data processing by grouping similar anatomies together, allowing precise implant placement recommendations to be derived from category-level analysis rather than requiring processing of every individual anatomical detail.
Solution Approach 2:
The system creates simplified representative models (copies) for each anatomical classification category. These representative models capture the essential geometric and functional characteristics of each category, enabling accurate surgical planning through simulation on simplified copies rather than requiring complex processing of full patient-specific anatomical data.
Data Source
AI summary
Improved surgical planning systems and methods are provided for planning orthopaedic procedures, including pre-operatively, intra-operatively, and/or post-operatively to create, edit, execute, and/or review surgical plans. The surgical planning systems and methods may be utilized for planning and implementing orthopaedic procedures to restore functionality to a joint. In some embodiments, range of motion simulations may be performed on a joint associated with a plurality of anatomical makeup classifications, and range of motion data derived from the range of motion simulations may be stored within a storage system of the surgical planning system.