Weight Training Analysis of Sportsmen with Kinect Bioinformatics for Form Improvement
This addresses the problem of form improvement for athletes and sports franchises, but it appears incremental as it applies existing Kinect technology to a specific domain.
The paper tackles the problem of analyzing athletes' weight training form by capturing motion data with a Kinect depth camera and processing joint parameters to identify imperfections. The result is a system that can provide valuable insights into workout dynamics and help improve athlete form, though no concrete performance numbers are provided.
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.