Mandibular Relocation Feature Location Optimization
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Solution Overview
Problem
Conventional methods for selecting locations of mandibular relocation features (MRFs) on oral appliances result in significant changes between stages, leading to discomfort and reduced effectiveness of mandibular relocation treatment due to the selection of the first available candidate location without considering optimal distance minimization between stages.
Innovation Solution
The described systems and methods determine candidate locations for MRFs on oral appliances to minimize the distance between selected locations across successive stages, using a computing device to compare and select locations that decrease the distance change, thereby improving patient comfort and treatment effectiveness.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the first available candidate location is selected for MRF placement at each stage, then the selection process is simple and quick, but the distance between MRF locations changes significantly between successive stages, causing patient discomfort and reduced treatment effectiveness
Solution Approach 1:
The system performs preliminary identification of all candidate MRF locations for multiple successive stages before final selection. By pre-calculating and storing candidate locations with their coordinates for each stage, the system enables subsequent distance-based optimization without requiring complex real-time computations during the selection phase.
Solution Approach 2:
The system calculates the distance between MRF locations of successive stages and uses this distance metric as feedback to evaluate and compare different candidate location combinations. This feedback mechanism guides the selection process to choose location pairs that minimize distance changes, thereby improving patient comfort while maintaining treatment effectiveness.
2Loss of time
If MRF locations are selected without optimizing distance between stages, then the treatment planning process is faster and less resource-intensive, but the patient experiences discomfort and treatment effectiveness is reduced
Solution Approach 1:
The system replaces manual or conventional trial-and-error MRF location selection with an automated computing device that performs distance calculations and optimization. This substitution of mechanical/manual processes with computational algorithms enables efficient evaluation of multiple candidate locations and their inter-stage distance metrics, achieving both speed and reliability.
Solution Approach 2:
The system changes the selection criterion from simply choosing the first available candidate location to selecting locations based on minimized distance parameters between successive stages. By introducing and optimizing the distance parameter, the system achieves more reliable treatment outcomes while maintaining computational efficiency through algorithmic optimization.
Data Source
AI summary
The disclosed computer-implemented method for selecting locations of mandibular relocation features (MRFs) on oral appliances may include determining candidate locations for placing an MRF on a first oral appliance for a first stage of mandibular relocation (MR) treatment and determining candidate locations for placing an MRF on a second oral appliance for a second stage. The method may include selecting from the candidate locations for the first stage and the second stage based on decreasing a distance between the selected pair of candidate locations. The method may further include processing multiple MRFs in parallel. The method may also include increasing a number of initial candidate locations. Locations for intermediate stages may be selected based on interpolating between the first and second stages or based on decreasing a distance between the selected pair if the interpolation fails. The intermediate stages may be processed using a binary search or a linear search.