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Artificial Intelligence Aided Training in Ping Pong Sport Education

机译：乒乓球运动教育中的人工智能辅助训练

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摘要

Recently, artificial intelligence has made huge strides in sports analysis. This paper attempts to focus this technology into table tennis with a real-time machine learning system that enables individual ping pong players to have independent training. This system enables table tennis players to maintain the benefits of training with a coach, without the physical presence of one. This, of course, also helps to practice social distancing under present situations. Our system uses a SensorTile development hardware and embedded workbench software to collect real time sensor data, using a variety of MEMS sensors such as accelerometers, gyroscopes, and magnetometers. Therefore, the mounted SensorTile system can detect the motion and orientation of the table tennis racket. We used machine learning (ML) methods to perform real-time table tennis stroke classification producing accurate classification results. Using this proposed machine learning system, players now have an effective training machine that is able to tell them if their strokes are accurate. This also reduces private coaching time in an attempt to limit unnecessary exposure, while still allowing players to receive feedback to improve their game.
机译：最近，人工智能在运动分析领域取得了长足的进步。本文试图通过一种实时机器学习系统将这项技术集中到乒乓球上，该系统可以使单个乒乓球运动员接受独立训练。该系统使乒乓球运动员在没有教练的情况下仍能保持与教练一起训练的好处。当然，这也有助于在当前情况下实践社会疏离。我们的系统使用SensorTile开发硬件和嵌入式工作台软件，通过各种MEMS传感器（如加速度计，陀螺仪和磁力计）收集实时传感器数据。因此，已安装的SensorTile系统可以检测乒乓球拍的运动和方向。我们使用机器学习（ML）方法执行实时乒乓球击球分类，从而产生准确的分类结果。使用这种建议的机器学习系统，玩家现在可以使用一种有效的训练机，该机器可以告诉他们他们的击打是否准确。这也减少了私人教练的时间，以试图限制不必要的接触，同时仍允许玩家接收反馈以改善他们的比赛。

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