目的 通过自组织特征映射神经网络(SOM)分析由德国Simi Motion 3D三维运动图像解析系统导出的教师提插手法参数,获取手法分类及特征.方法 研究选择30名针灸教师,取一侧"曲池穴"作为施术穴位,记录提插平补平泻、补法、泻法的运动视频.视频经由Simi Motion 3D三维运动图像解析系统分析,得出拇指指尖跟踪标记点位原始运动参数,通过SOM分析教师手法分类参数.结果 针刺手法参数呈非正态分布,离散度较大;平补平泻与补法可分为4类,泻法可分为5类,各分类的特征集中程度一般.结论 针刺手法参数总体上表现为非正态分布的多样性特征,为典型"人为控制曲线",表现出神经网络分类集中度较低的特点,其分类主要根据曲线外形及周期长短进行,且与手法难易程度相关.该技术可应用于各类手法的量化分析与技术传承研究,并能为针灸规范化与标准化提供参考.%Objective To obtain the classification and characteristics of acupuncture manipulations by analyzing teacher's lifting-thrusting manipulation parameters derived from Germany-made Simi Motion 3D image analysis system using self-organizing feature map neural network (SOM). Method Thirty acupuncture teachers were selected for the study. Unilateral Quchi (LI11) was used as a point for acupuncture. A motion video of lifting-thrusting even reinforcing-reducing, reinforcing and reducing manipulations was made. The video was analyzed using Simi Motion 3D image analysis system to obtain original motion parameters at thumb tip tracking mark point. Teacher's manipulation classification parameters were analyzed using SOM. Result Acupuncture manipulation parameters showed nonnormal distribution with larger dispersion. Even reinforcing-reducing and reinforcing manipulations could be classified into four types and reducing manipulation, into five types. The characteristics of every type showed general concentration degree. Conclusion Acupuncture manipulation parameters overall showed the diversity characteristics of nonnormal distribution and are typical "artificial control curve". They have the characteristic of lower concentration degree of neural network classification. Their classification is mainly based on curve shape and cycle length and related to the degree of difficulty of manipulation. This technique can be applied to the quantitative analysis of various manipulationsand the study of technical inheritance and provide reference for the standardization of acupuncture manipulation.
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