Spatial Mesh Positioning in Mixed Reality Healthcare
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Solution Overview
Problem
Conventional augmented reality healthcare systems rely on slow and expensive artificial intelligence algorithms for detecting patients and calculating their position and rotation in three dimensions, which are complex to develop and execute.
Innovation Solution
The system uses a mesh object of a patient's portion rotated in reference to two points, defined by x, y, and z coordinates, which is faster and less complex to engineer, involving a 3D source mesh object generation, orientation bar placement, and rotation calculations within a mixed reality smartglass framework.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If artificial intelligence algorithms are used to detect patients and calculate position and rotation, then measurement precision is improved, but device complexity and execution time increase
Solution Approach 1:
The patent segments the complex AI-based detection system into simpler geometric operations. Instead of using a monolithic AI algorithm, the system divides the problem into: (1) detecting key anatomical landmarks, (2) constructing a spatial mesh from these landmarks, and (3) performing separate rotation calculations around specific axes. This segmentation reduces overall system complexity while maintaining measurement precision.
Solution Approach 2:
The patent introduces a spatial mesh as an intermediary representation between raw sensor data and final position/rotation calculations. The mesh object serves as a mediator that simplifies the transformation process, allowing for more efficient computation of anatomical orientations without requiring complex AI algorithms for each calculation step.
2Measurement precision
If artificial intelligence algorithms are used to detect patients and calculate position and rotation, then measurement precision is improved, but execution speed decreases
Solution Approach 1:
The patent performs preliminary construction of the spatial mesh and identification of key anatomical landmarks before the actual position and rotation calculations are needed. By pre-processing the data to establish the mesh structure and critical reference points, the system eliminates the need for complex real-time AI computations during measurement, thereby improving execution speed while maintaining precision.
Solution Approach 2:
The patent replaces the computational 'mechanics' of AI algorithms with simpler geometric and mathematical operations. Instead of using neural networks or complex machine learning models for position and rotation calculation, the system uses straightforward vector mathematics and geometric transformations on the pre-established spatial mesh, significantly improving execution speed.
3Measurement precision
If artificial intelligence algorithms are used to detect patients and calculate position and rotation, then measurement precision is improved, but development cost increases
Solution Approach 1:
The patent replaces expensive, complex AI algorithms with simpler, more economical computational methods. The spatial mesh approach uses basic geometric operations that are computationally inexpensive and easier to implement, reducing development costs while maintaining the necessary measurement precision for medical applications.
Data Source
AI summary
Systems, methods and apparatus are provided through which a 3D source mesh object is generated by a three-dimensional-augmented-reality engine from medical data, a copy mesh object is generated by copying the 3D source mesh object, a center of the 3D source mesh object is calculated from the 3D source mesh object, an orientation bar is generated and placed orthogonally in the center of the copy mesh object, a scene mesh object a generated by scanning the room, the scene mesh object being a game object, a patient mesh object is generated by cutting the scene mesh object in reference to original dimensions of the 3D source mesh object and a patient mesh object is generated from the patient mesh object by starting from the index tip of a finger and placing the 3D source mesh object in a direction that is downward.


