Weight Training Analysis of Sportsmen with Kinect Bioinformatics for Form Improvement

TL;DR

This paper presents a Kinect-based system for analyzing athletes' weight training motions to identify imperfections and improve form, offering real-time and recorded data analysis for enhanced training outcomes.

Contribution

The study introduces a novel Kinect-based motion analysis system specifically designed for weight training, enabling detailed assessment of athletes' form and movement parameters.

Findings

System can analyze motion parameters like range of motion, speed, and balance in real time.

Recorded data allows for accurate comparison and feedback on athlete's form.

System is easy to deploy and provides valuable insights for training improvement.

Abstract

Sports franchises invest a lot in training their athletes. use of latest technology for this purpose is also very common. We propose a system of capturing motion of athletes during weight training and analyzing that data to find out any shortcomings and imperfections. Our system uses Kinect depth image to compute different parameters of athlete's selected joints. These parameters are passed through certain algorithms to process them and formulate results on their basis. Some parameters like range of motion, speed and balance can be analyzed in real time. But for comparison to be performed between motions, data is first recorded and stored and then processed for accurate results. Our results depict that this system can be easily deployed and implemented to provide a very valuable insight to dynamics of a work out and help an athlete in improving his form.