June 6, 2023 — Southwest Research Institute is using markerless motion capture to assess the performance and injury risk of baseball pitchers. The internally funded project utilized the SwRI-developed Engine for Automatic Biomechanical Evaluation (ENABLE™) analysis tool to create a portable, user-friendly system to improve pitchers’ accuracy and alter their mechanics to reduce injury risk.
Markerless motion capture leverages computer vision algorithms to capture 3D motion data for biomechanical analysis in research, clinical and sport science applications, without the need to attach physical body markers to a human subject.
“We’re interested in how various factors can lead to excellent performance as well as lower risk of injury,” said SwRI Research Engineer Ty Templin, who led the project.
The work began with data collected by Dr. Sakiko Oyama, associate professor of kinesiology at The University of Texas at San Antonio. Oyama used ENABLE to capture the movements of more than a dozen pitchers, collecting video data, optical motion capture and ground reaction force, which is the force exerted by the ground on the body when in contact with it.
“It was clear that we could track the pitchers’ movements, but we wanted to find out if we could identify potential changes in their mechanics that would improve performance or reduce their risk of injury,” Templin said. “We ran optimization scenarios to make subtle changes to the pitchers’ motions and mechanics to minimize shoulder torque, which was our metric for injury. We then maximized the hand velocity, which was our metric for performance.”
SwRI’s markerless biomechanics system is unique in its forward dynamics optimization capability, which allows users to examine scenarios that incorporate hypothetical changes to the subject’s movements. For example, researchers found that a straightened stride leg more efficiently transfers energy into the pitch.
“We see so many potential applications for this technology,” said Institute Engineer Dr. Dan Nicolella. “In addition to optimizing how someone moves or performs in sports to reduce the risk of injury and extend their careers, we envision more general healthcare applications. For example, it could help people learn how to change their gait patterns to minimize things like the development of osteoarthritis.”
Templin, Nicolella and their colleagues plan to investigate the various benefits the system can offer and have already begun studying the movements of basketball players.
“It’s almost impossible to say, ‘If you throw like this, you’re going to get injured,’” Templin said. “What we’ve seen is that putting certain additional stresses on the body can make you more likely to get injured, but if you change movements slightly, that likelihood can be lessened. We can’t say with certainty that injury will or won’t occur, but we’re quantifying the probability.”