General Incorporated Association
“Sports Science Laboratory”
VisionPose Utilized in an AI app to Identify Pitching Motion That Causes Pain
Utilizing the software to derive the relationship between pitching motion and pitching disorders in youth baseball
Takeo Ishii, General Incorporated Association “Sports Science Laboratory”
Initial Business Requirements
“What kind of pitching mechanics causes shoulder and elbow pain?”
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 analysis results, we have developed a smartphone app that visually displays which of your pitching motion causes pain.
Why We Choose VisionPose
There are many algorithms that use deep learning for pose estimation, but they often require a lot of time to build the environment. VisionPose allowed us to analyze the data from the day we purchased it, saving us the time we woud have spent on building the environment.
The after-sales service was excellent, and we are very grateful for the prompt response 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 by 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/