Sports Science Laboratory
VisionPose Used in AI app to Identify Pain through Pitching Motion
We used the software to better understand the relationship between pitching motion and pitching disorders in youth baseball.
Takeo Ishii, Sports Science Laboratory
Initial Business Requirements
“What causes shoulder and elbow pain when pitching?”
Many baseball coaches and players consider this question when out on the field. We have analyzed our database of over 4,000 baseball players to find the relationship between pitching motion and pitching disorders.
Using the analyzed results, we have developed a smartphone app that visually displays which of your pitching motion causes pain.
Why We Chose VisionPose
There are many algorithms that use deep learning for pose estimation, but they often require a lot of time to have learned enough to be useful. VisionPose allowed us to analyze the data from the day we purchased it, saving us the time we would have otherwise spent waiting for the algorithm to get up to speed.
The after-sales service was excellent, and we are very grateful for the fast responses to our various requests.
Implementation Results and Future Outlook
We have collected data not only on baseball, but also on many other sports, and we have a lot of athletic ability data, as well as disability data.
By using VisionPose to analyze this data, we hope to develop an application that can present each athlete with movements that both prevent injury and improve performance in various sports.
VisionPose Utilized in an AI App to Identify Pitching Mechanics That Cause Pain
We have developed a smartphone app that captures pitching motion, evaluates it through AI analysis, and points out the motion that causes pain.
App overview (in Japanese):https://www.spo-labo.com/projects/sports-p/throwing-injury-p/