VR Medical Simulator Using Sensor-Based Anatomy Models
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Solution Overview
Problem
Legacy medical VR/AR simulators require dedicated hardware setup, calibration, and maintenance, which is costly, time-consuming, and prone to mechanical constraints, limiting their versatility and realism in training various medical procedures.
Innovation Solution
A flexible medical simulation system using anatomy models with position and orientation sensors and calibration units that store pre-computed data, allowing for automatic adaptation to different training scenarios without the need for specialized hardware integration or calibration, enabling realistic simulation of various patient pathologies and procedures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If dedicated haptic hardware and specialized setup are used, then realism and accuracy of simulation are improved, but device complexity and cost increase
Solution Approach 1:
The patent creates a visual copy of the anatomical structure through VR/AR simulation that replicates the appearance and spatial relationships of real anatomy. This visual replica provides sufficient training value without requiring physical copies or complex haptic hardware, resolving the contradiction by achieving simulation accuracy through computational modeling rather than physical replication.
Solution Approach 2:
The patent replaces complex mechanical haptic feedback systems with visual feedback mechanisms. Instead of using physical force feedback devices that require calibration and maintenance, the system uses VR/AR visual representations to convey anatomical information and procedural guidance, eliminating the need for dedicated haptic hardware while maintaining training effectiveness.
2Measurement precision
If manual calibration by experienced physicians is performed, then alignment accuracy is improved, but time consumption and operational complexity increase
Solution Approach 1:
The system performs automatic calibration through software-based alignment algorithms that self-adjust the VR/AR visual model to match the physical anatomy model. This self-calibration process eliminates the need for manual intervention by experienced physicians, reducing setup time while maintaining alignment accuracy through computational methods.
Solution Approach 2:
The patent pre-configures the VR/AR system with anatomical data and calibration parameters before the training session begins. The system prepares the visual model and alignment settings in advance, so that when the physical anatomy model is placed on the platform, the calibration is already optimized or can be quickly auto-adjusted, minimizing the time required for alignment during actual use.
3Adaptability or versatility
If multiple dedicated simulators are deployed for different procedures, then versatility and adaptability are improved, but cost and device complexity increase
Solution Approach 1:
The patent creates a universal VR/AR simulation platform that can display different anatomical structures and procedural scenarios through software configuration. By using a single physical platform with interchangeable visual models and configurable parameters, the system can simulate multiple different medical procedures and anatomical regions, eliminating the need for multiple dedicated simulators while maintaining versatility across different training scenarios.
Data Source
AI summary
Simulation systems and methods may enable medical training. A manufacturing unit may receive data from a configuration unit indicating identification and manufacturing parameters for an anatomy model. A data processing unit may receive data from the configuration unit identifying the anatomy model, and data from a calibration unit indicating a position and/or orientation of a position and orientation sensor relative to the anatomy model. The data processing unit may also receive data from the position and orientation sensor indicating a position and/or orientation of the anatomy model. The data processing unit may generate a virtual image using the data from the position and orientation sensor, the data from the calibration unit, and the data from the configuration unit. The data processing unit may render the virtual image to a display.