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Research on Acupuncture Technique Recognition Technology Based on Deep Learning Algorithms

Published: 05 April 2024 Publication History

Abstract

Combining deep learning-based methods and key posture sensor data can improve the accuracy of automatically identifying basic acupuncture techniques. This study aims to propose a novel deep learning-based method to identify the time characteristics of the physical parameters of acupuncture techniques, including twisting-supplementing (TS), twisting-draining (TD), level-supplementing level-draining (LSLD), lifting-inserting-supplementing (LIS), and lifting-inserting-draining (LID) methods. During the acupuncture process, six-axis posture sensors collect parameters such as lifting and inserting speed, twisting frequency, and angular rotation rate, and analyze the mapping relationship between physical parameters and different techniques. By using multi-dimensional signal control decision algorithms, the performance of our method is enhanced, addressing the issue of poor recognition based on single-dimensional signals. Experimental results demonstrate that our method achieves high accuracy in identifying five techniques. Our proposed method can effectively identify acupuncture techniques, making it useful for the evaluation and teaching of acupuncture techniques, facilitating the inheritance of traditional Chinese acupuncture techniques.

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      ISAIMS '23: Proceedings of the 2023 4th International Symposium on Artificial Intelligence for Medicine Science
      October 2023
      1394 pages
      ISBN:9798400708138
      DOI:10.1145/3644116
      Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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      Published: 05 April 2024

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