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Related Experiment Video

Updated: May 28, 2025

Visualizing Motion Patterns in Acupuncture Manipulation

Visualizing Motion Patterns in Acupuncture Manipulation

Published on: July 16, 2016

Exploring the potential of acupuncture practice education using artificial intelligence.

Kyeong Han Kim^1,2,3, Hyein Jeong⁴, Gyeong Seo Lee⁵

¹Department of Preventive Medicine, School of Korean Medicine, Woosuk University, Wanju, Korea.

Integrative Medicine Research

|February 13, 2025

Summary

Generative artificial intelligence (AI) shows promise for acupuncture education. AI tools can improve acupoint selection and manipulation techniques, enhancing traditional medicine training.

Keywords:

Acupuncture Artificial intelligence Education

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Last Updated: May 28, 2025

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Published on: July 16, 2016

Author Spotlight: Development of a Standardized Acupuncture Tool Inspired by Advanced Techniques for Improved Safety and Precision

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Three-Dimensional Finger Motion Tracking during Needling: A Solution for the Kinematic Analysis of Acupuncture Manipulation

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Published on: October 28, 2021

Area of Science:

Medical Education
Artificial Intelligence
Traditional Medicine

Background:

Generative artificial intelligence (AI) is increasingly utilized across medical fields, including education, clinical practice, and research.
The integration of AI in medical education offers new avenues for enhancing learning experiences and outcomes.

Purpose of the Study:

To review the potential applications of AI models in acupuncture practice education.
To identify current research trends and future possibilities for AI in traditional medicine training.

Main Methods:

A literature search was conducted to identify recent and relevant findings on AI in acupuncture education.
The review focused on AI applications in specific areas like acupoint selection and acupuncture manipulation.

Main Results:

Active research is underway on utilizing AI for acupuncture education.
AI-powered educational tools are being developed within the broader field of traditional medicine.
AI demonstrates potential in improving acupoint selection and acupuncture manipulation training.

Conclusions:

AI-driven educational tools hold significant potential to improve the effectiveness and efficiency of acupuncture education.
Further development and research in AI for traditional medicine education are warranted.