Jiayao Wan, Binggan Wang, Tianai Huang, Fan Wang, Wenchao Tang
{"title":"[基于三维运动跟踪技术的手针刺手法机器学习定量评价模型研究]。","authors":"Jiayao Wan, Binggan Wang, Tianai Huang, Fan Wang, Wenchao Tang","doi":"10.13703/j.0255-2930.20241209-0002","DOIUrl":null,"url":null,"abstract":"<p><strong>Objective: </strong>To develop an objective quantitative evaluative model of manual acupuncture manipulation (MAM) using three-dimensional motion tracking technology and machine learning, so as to provide a new approach to the study on acupuncture and moxibustion education and manipulation standardization.</p><p><strong>Methods: </strong>A total of 120 undergraduate students in the major of acupuncture-moxibustion and <i>tuina</i> were recruited. The Simi Motion Ver.8.5 motion tracking system was used to collect the data of three types of MAM, balanced reinforcing and reducing by twisting, reinforcing technique by twisting and reducing technique by twisting. Eight quantitative parameters covering movement performance and stability were established. With 5 types of machine learning algorithms (logistic regression, random forest, support vector machine, K-nearest neighbor, and decision tree) adopted, the evaluative model was constructed, and the feature importance analyzed.</p><p><strong>Results: </strong>In the evaluation of different types of MAM, the support vector machine presented the best for the effects of the balanced reinforcing and reducing by twisting, and the reducing by twisting (accuracy rates were both 0.88); and the logistic regression algorithm showed the optimal performance in evaluating the reinforcing by twisting (1.00 of accuracy rate). Feature importance analysis revealed that twisting velocity was the dominant parameter for evaluating the balanced reinforcing-reducing manipulation. The reinforcing and reducing of acupuncture techniques were more dependent on the left-hand twisting parameters and comprehensive performances, respectively.</p><p><strong>Conclusion: </strong>The objective evaluative model of MAM based on three-dimensional motion tracking technology and machine learning demonstrates a reliable evaluative performance, providing a new technical approach to standardized assessment in acupuncture and moxibustion education.</p>","PeriodicalId":69903,"journal":{"name":"中国针灸","volume":"45 9","pages":"1201-1208"},"PeriodicalIF":0.0000,"publicationDate":"2025-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"[Research on machine-learning quantitative evaluative model of manual acupuncture manipulation based on three-dimensional motion tracking technology].\",\"authors\":\"Jiayao Wan, Binggan Wang, Tianai Huang, Fan Wang, Wenchao Tang\",\"doi\":\"10.13703/j.0255-2930.20241209-0002\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Objective: </strong>To develop an objective quantitative evaluative model of manual acupuncture manipulation (MAM) using three-dimensional motion tracking technology and machine learning, so as to provide a new approach to the study on acupuncture and moxibustion education and manipulation standardization.</p><p><strong>Methods: </strong>A total of 120 undergraduate students in the major of acupuncture-moxibustion and <i>tuina</i> were recruited. The Simi Motion Ver.8.5 motion tracking system was used to collect the data of three types of MAM, balanced reinforcing and reducing by twisting, reinforcing technique by twisting and reducing technique by twisting. Eight quantitative parameters covering movement performance and stability were established. With 5 types of machine learning algorithms (logistic regression, random forest, support vector machine, K-nearest neighbor, and decision tree) adopted, the evaluative model was constructed, and the feature importance analyzed.</p><p><strong>Results: </strong>In the evaluation of different types of MAM, the support vector machine presented the best for the effects of the balanced reinforcing and reducing by twisting, and the reducing by twisting (accuracy rates were both 0.88); and the logistic regression algorithm showed the optimal performance in evaluating the reinforcing by twisting (1.00 of accuracy rate). Feature importance analysis revealed that twisting velocity was the dominant parameter for evaluating the balanced reinforcing-reducing manipulation. The reinforcing and reducing of acupuncture techniques were more dependent on the left-hand twisting parameters and comprehensive performances, respectively.</p><p><strong>Conclusion: </strong>The objective evaluative model of MAM based on three-dimensional motion tracking technology and machine learning demonstrates a reliable evaluative performance, providing a new technical approach to standardized assessment in acupuncture and moxibustion education.</p>\",\"PeriodicalId\":69903,\"journal\":{\"name\":\"中国针灸\",\"volume\":\"45 9\",\"pages\":\"1201-1208\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2025-09-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"中国针灸\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.13703/j.0255-2930.20241209-0002\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"中国针灸","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.13703/j.0255-2930.20241209-0002","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
[Research on machine-learning quantitative evaluative model of manual acupuncture manipulation based on three-dimensional motion tracking technology].
Objective: To develop an objective quantitative evaluative model of manual acupuncture manipulation (MAM) using three-dimensional motion tracking technology and machine learning, so as to provide a new approach to the study on acupuncture and moxibustion education and manipulation standardization.
Methods: A total of 120 undergraduate students in the major of acupuncture-moxibustion and tuina were recruited. The Simi Motion Ver.8.5 motion tracking system was used to collect the data of three types of MAM, balanced reinforcing and reducing by twisting, reinforcing technique by twisting and reducing technique by twisting. Eight quantitative parameters covering movement performance and stability were established. With 5 types of machine learning algorithms (logistic regression, random forest, support vector machine, K-nearest neighbor, and decision tree) adopted, the evaluative model was constructed, and the feature importance analyzed.
Results: In the evaluation of different types of MAM, the support vector machine presented the best for the effects of the balanced reinforcing and reducing by twisting, and the reducing by twisting (accuracy rates were both 0.88); and the logistic regression algorithm showed the optimal performance in evaluating the reinforcing by twisting (1.00 of accuracy rate). Feature importance analysis revealed that twisting velocity was the dominant parameter for evaluating the balanced reinforcing-reducing manipulation. The reinforcing and reducing of acupuncture techniques were more dependent on the left-hand twisting parameters and comprehensive performances, respectively.
Conclusion: The objective evaluative model of MAM based on three-dimensional motion tracking technology and machine learning demonstrates a reliable evaluative performance, providing a new technical approach to standardized assessment in acupuncture and moxibustion education.
期刊介绍：
Chinese Acupuncture and Moxibustion (founded in 1981, monthly) is an authoritative academic journal of acupuncture and moxibustion under the supervision of China Association for Science and Technology and co-sponsored by Chinese Acupuncture and Moxibustion Society and Institute of Acupuncture and Moxibustion of China Academy of Traditional Chinese Medicine. It is recognised as a core journal of Chinese science and technology, a core journal of Chinese language, and is included in the core journals of China Science Citation Database, as well as being included in MEDLINE and other international well-known medical index databases. The journal adheres to the tenet of ‘improving, taking into account the popularity, colourful and realistic’, and provides valuable learning and communication opportunities for the majority of acupuncture and moxibustion clinical and scientific research workers, and plays an important role in the domestic and international publicity and promotion of acupuncture and moxibustion disciplines.
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