Ping Pong Motion Recognition based on Smart Watch

Abstract

Smart watches have become one of the most representative devices in wearable devices because of their unique advantages such as integration, portability, reliability, stability, universality and low environmental dependence. At present, it is mainly used for the monitoring of health indicators such as human heart rate. Whole-body inertial sensing devices cannot meet the actual needs of the general public for virtual sports because of high prices and inconvenient wear. In this paper, a single piece smart watch is used to study the recognition of the most common actions in table tennis which is a kind of fast-moving sport and has many fans through an improved convolution neural network model. The final experimental results show that the recognition accuracy reaches 95.46%, which can basically meet the needs of amateurs' motionSports.