针刺研究2023，Vol.48Issue(12)：1274-1281,8.DOI:10.13702/j.1000-0607.20221145
一种基于三轴姿态传感器和计算机视觉的针刺手法分类系统
An acupuncture manipulation classification system based on three-axis attitude sensor and computer vision
摘要
Abstract
Objective To explore the action characteristics of acupuncture manipulations by combining visual and sensor technique,so as to improve the identification and classification accuracy of acupuncture manipulations and to quantificate the classifiations.Methods In this paper,the time domain features of acupuncture physical parameters and dynamic gesture features in the video of acupuncture manipulations are combined together to identify and classify acupuncture techniques.The acupuncture needle manipulation processes of 2 acupuncture experts and 3 young acu-puncturists were selected as the study objects.The collected data included 4 basic manipulation techniques:lifting-thrusting reinforcing,lifting-thrusting reducing,twisting reinforcing and twisting reducing methods,all of which were performed by right-handed doctors.During acupuncture manipulation,a three-axis attitude sensor was used to acquire finger moving acceleration velocity and needle-rotating angle velocity,followed by analyzing the parameters of hand-moving velocity,amplitude,strength and angle.The mapping relationship among physical parameters and different ma-nipulating methods was formed in time domain.The computer vision technology was employed to extract the spatio-temporal features of the acupuncture manipulation video images,and a hybrid model of three-dimensional convolutional neural network(3D CNN)and long-and short-term memory(LSTM)neural network were used for the recognition and classification of dynamic gestures of hand in acupuncture manipulation videos.Then the time-domain features of physical parameters were combined with the dynamic gestures in the classification process,with the manipulation clas-sification realized.Results In performing the lift-thrusting reinforcing method,the needle insertion speed was faster and the force was larger,while the needle lifting speed was slower and the force was smaller.And in performing the lift-thrusting reducing method,the needle lifting speed was faster,the force was stronger,and the needle insertion speed was slower and the force was smaller.In the performance of twisting reinforcing,the leftward twisting force was bigger and the rotation amplitude was larger,while in performing the reducing method,the rightward twisting force was larger and the rotation amplitude was larger.When using the mean value of time of acceleration,speed,and amplitude as the basis of discrimination,the accuracy rates of lifting-thrusting reinforcing and reducing were 95.56%and 93.33%,while those of the two twisting manipulations were 95.56%and 91.11%,respectively.Compared with the classification method that only uses the sensor to obtain the manipulation information,the recognition accuracy was significantly im-proved.Conclusion The acupuncture manipulation classification system can achieve quantitative analysis of physical parameters and dynamic recognition of acupuncture techniques,providing a certain foundation for the quantification and inheritance of acupuncture techniques.关键词
针刺手法/计算机视觉/三轴姿态传感器/识别/分类Key words
Acupuncture manipulation/Computer vision/Three axis attitude sensor/Identification/Classification分类
医药卫生引用本文复制引用
朱猛,刘大明,裴建,詹逸珺,沈海月..一种基于三轴姿态传感器和计算机视觉的针刺手法分类系统[J].针刺研究,2023,48(12):1274-1281,8.基金项目
上海申康医院发展中心重大临床研究项目(No.SHDC2020CR3091B) （No.SHDC2020CR3091B）
上海市卫生健康委员会三年行动计划[No.ZY(2021-2023)-0209-10] （2021-2023）
