Action Primitive Classification of Sewing Operations toward Training Unskilled Workers

In this study, we proposed a system for measuring hand posture and fingertip force for training unskilled workers who sew with sewing machines. Furthermore, we classified sewing behaviors by constructing deep learning models using time-series color image data, hand posture, and fingertip force as inputs. Our experiments demonstrated that the classification model based on color images is the highest accuracy. Meanwhile, using the fingertip force-based model can not only classify sewing actions but can also extract the operator’s motion data in detail.