文章摘要
王韫,陈梓馨,徐海鑫,石运隆,秦雪娇.结合主观决策和表面肌电的医生手部精细动作编码研究[J].包装工程,2024,(16):40-50.
结合主观决策和表面肌电的医生手部精细动作编码研究
Coding Method for Fine Hand Movements of Doctors Combining Subjective Judgement and sEMG Measurements
投稿时间:2024-03-12  
DOI:10.19554/j.cnki.1001-3563.2024.16.004
中文关键词: 眼科手术  手部精细动作  行为编码  表面肌电信号
英文关键词: eye surgery  fine hand movements  behavior coding  surface electromyogram signal
基金项目:国家重点研发计划(2022YFB4702904)
作者单位
王韫 北京航空航天大学 新媒体艺术与设计学院北京 100191 
陈梓馨 北京航空航天大学 机械工程与自动化学院北京 100191 
徐海鑫 北京航空航天大学 航空科学与工程学院北京 100191 
石运隆 北京航空航天大学 机械工程与自动化学院北京 100191 
秦雪娇 山东大学第二医院济南 250102 
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中文摘要:
      目的 当前在医学教育与培训领域中,对复杂精细手部操作技能的分解与掌握仍然存在显著挑战。提出一种将医生主观决策信息与表面肌电信号结合,对医生的手部精细动作进行行为编码的方法。方法 首先明确了行为编码的定义和手部精细动作特点,并梳理了肌电信号在行为编码中的应用路径。基于以上研究背景和基础,完成了进行了主观决策信息的采集与编码模型的构建,并设计和实施用户实验测量表面肌电(Surface Electromyography,sEMG)信号。通过对肌电信号数据进行节点判断与动作分段,对手部精细动作编码进行了验证。结论 手部精细动作技能相关的行为编码提供了一种结合表面肌电和主观决策的行为序列结构化方法,不仅有助于医学生对标准化手术行为的理解与学习,更为未来手术机器人的开发、训练与测试提供了实证参考。
英文摘要:
      In the field of medical education and training, there are still significant challenges in the decomposition and mastery of complex and fine hand manipulation skills. The work aims to propose a method to encode the fine movements of doctors' hands by combining the subjective judgment information with surface electromyographic signals. Firstly, the definition of behavior coding and the characteristics of hand fine movements were clarified, and the application path of EMG in behavior coding was sorted out. Based on the above research background and foundation, the acquisition of subjective judgment information and the construction of coding model were completed, and the user experiment to measure sEMG signal was designed and implemented. The fine movement coding of doctors' hands was verified through node judgment and movement segmentation of EMG data. The behavior coding related to fine hand movement skills provides a structured behavior sequence method combining surface electromyography and subjective judgment, which not only helps medical students understand and learn standardized surgical behaviors, but also provides an empirical reference for the development, training and testing of surgical robots in the future.
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