AI Acupuncture Point Mapping for Individual Body Variation
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Solution Overview
Problem
Conventional methods for displaying acupuncture points on the human body fail to account for individual variations in height and weight, making it difficult for experts to accurately locate these points on patients.
Innovation Solution
A method using an artificial intelligence deep-learning model to convert joint point location vectors to fit the subject's body, calculate acupuncture point locations through vector calculations, and display them in augmented reality on a real-time image.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional three-dimensional models are used to display acupuncture points, then the display method is simple, but the accuracy of locating acupuncture points varies with individual body size
Solution Approach 1:
The system dynamically adapts the acupuncture point locations by converting joint point location vectors from a standardized model to match the actual subject's body size. The joint points are detected in real-time from the subject image, and the acupuncture point positions are calculated dynamically based on the detected joint positions and the subject's individual dimensions, ensuring accuracy across different body sizes.
Solution Approach 2:
The system changes the scale parameter of the joint points by converting them from the standardized three-dimensional model's coordinate system to the actual subject's coordinate system. This parameter transformation allows the acupuncture point locations to be accurately mapped regardless of the subject's height, weight, or body proportions.
2Adaptability or versatility
If standardized acupuncture point locations are used, then the method is easy to implement, but it cannot adapt to individual variations in height and weight
Solution Approach 1:
The system uses joint points as intermediary elements to bridge the standardized acupuncture point model and the individual subject's body. By detecting joint points (elbow, wrist, finger joints) in the subject image and using them as reference markers, the system calculates acupuncture point positions that adapt to individual body variations while maintaining the systematic approach of standardized locations.
Solution Approach 2:
The system transitions from a two-dimensional standardized map to a three-dimensional adaptive model by incorporating depth information and spatial relationships of joint points. The joint point location vectors provide three-dimensional positioning that accounts for individual body geometry, enabling accurate acupuncture point localization across varying body sizes and shapes.
3Productivity
If manual marking of acupuncture points is performed, then equipment requirements are minimal, but the time and skill required increase significantly
Solution Approach 1:
The system performs automatic detection and calculation of acupuncture point positions without requiring manual marking by experts. The joint points are automatically detected from the subject image using image processing algorithms, and the acupuncture point locations are computed automatically based on the detected joint positions, eliminating the need for time-consuming manual identification while maintaining high accuracy.
Solution Approach 2:
The system replaces the manual mechanical process of expert identification and marking with an automated computer vision and calculation system. Image processing algorithms detect joint points, and mathematical calculations determine acupuncture point positions, substituting human expertise and manual operations with automated computational methods that increase speed and consistency.
Data Source
AI summary
The present disclosure relates to a method of displaying locations of acupuncture points in the human body using artificial intelligence and may provide a method of displaying locations of acupuncture points in the human body, which may convert the sizes of the joint points from an artificial intelligence deep-learning model (e.g., MediaPipe, etc.) to fit the subject body, calculate locations of acupuncture points on the hands, feet, face, body, etc. through vector calculation of the joint points, and display the same in real-time image on the subject body in augmented reality.