A training analysis system for table tennis players

Abstract

The invention discloses a table tennis player training analysis system. It includes an attitude sensing module, a vibration sensing module, a main control module, and a host computer; the vibration sensing module includes multiple vibration sensors, and multiple vibration sensors are set on the table tennis table and monitor the vibration intensity respectively; the attitude sensing module , which is used to monitor the posture data of the player’s arm when hitting the ball; the main control module calculates according to the setting positions of multiple vibration sensors and the data obtained by the respective monitoring of the vibration sensors, so as to obtain the falling position of the table tennis ball on both sides of the table every time the ball is hit. point position coordinates; and process and integrate the landing position coordinates of the table tennis ball and the posture data of the arm each time; the host computer includes an algorithm module, which aggregates and classifies the processed and integrated data to obtain the training classification results, and The training analysis is given according to the training classification results. The invention can accurately and automatically obtain the drop point position of the table tennis ball, and can analyze the training of athletes.

Description

technical field [0001] The invention relates to the field of sports training analysis, in particular to a table tennis player training analysis system. Background technique [0002] The current commonly used methods of table tennis training monitoring are mainly divided into two types: one is human eye recognition, that is, the referee directly judges the result of the game during the game. The disadvantage of this method is that it is prone to misjudgment. High and controversial dribbles are difficult to judge directly; the other is a computer vision analysis system, which is a real-time playback system commonly used in international competitions today. This system avoids misjudgments during the judgment process, but the disadvantage is that the real-time It will delay the game process and affect the performance of athletes. At the same time, the current table tennis training methods usually give training suggestions through artificial observation of the training process, ...

AI Technical Summary

Problems solved by technology

At the same time, improve the problem of low data accuracy in the current table tennis intelligent training system, improve the accuracy of measurement and real-time data collection, and analyze the common methods and deficiencies of players

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