Robotic system for accelerated motor skills acquisition in sports

This technology is a robotics platform that captures user motion through various sensors and applies force to the pelvis and trunk to train users to perform physical tasks related to sporting activities.

Unmet Need: Assist-as-needed force system for sports training

Robotic-mediated movement training is an effective rehabilitation approach for motor impairments following neurological injury, including brain injury, stroke, and spinal cord injury. Since similar motor training is required for mastering skills involved in many sports, the study of movement patterns of professional athletes can also be utilized to train novices to improve their skills and mitigate injury. However, while the movements of professional athletes have been studied using high-tech motion capture systems, there has been little effort to couple this to assist-as-needed force-based training.

The Technology: Robotic assist-as-needed system for motor learning

This technology combines motion capture technology with an assist-as-needed force system to analyze and then train participants to perform physical motions related to sporting activities. It records movement patterns and internal signals from key points on the human body using a motion capture system, force plates, an electromyograph, and an electroencephalogram. Using AI/ML models trained by the motions of professional athletes, it can then guide the training of novices to perform sporting activities such as throwing a ball. Furthermore, the data gathered from the system during training is used to characterize human learning, enabling the continuous improvement of the model/platform.

This technology has been validated in human participants for activities including catching, aiming, and throwing a ball at a target.

Applications:

• Robotics-mediated training system for sports
• Robotics-mediated training system for injury mitigation
• Robotics-mediated training system for performance improvement

Advantages:

• Leverages existing robotics platform used for injury rehabilitation
• Combines motion capture and various sensors to gather internal and external data on participants
• Versatility in the application of motor skills to various sporting activities

Lead Inventor:

Sunil Agrawal, Ph.D.

Patent Information:

Patent Pending

Related Publications:

• Omofuma I, Santamaria V, Ai X, Agrawal S. “Training Postural Balance Control with Pelvic Force Field at the Boundary of Stability.” Bioengineering (Basel). 2023 Dec 6;10(12):1398.

• Bowersock CD, Pisolkar T, Omofuma I, Luna T, Khan M, Santamaria V, et al. “Robotic upright stand trainer (RobUST) and postural control in individuals with spinal cord injury.” The Journal of Spinal Cord Medicine. 2023 Nov 2;46(6):889–99.

• Luna TD, Santamaria V, Omofuma I, Khan MI, Agrawal SK. “Postural Control Strategies in Standing With Handrail Support and Active Assistance From Robotic Upright Stand Trainer (RobUST).” IEEE Transactions on Neural Systems and Rehabilitation Engineering. 2021;29:1424–31.

• Luna TD, Santamaria V, Omofumal I, Khan MI, Agrawal SK. “Control Mechanisms in Standing while Simultaneously Receiving Perturbations and Active Assistance from the Robotic Upright Stand Trainer (RobUST).” In: 2020 8th IEEE RAS/EMBS International Conference for Biomedical Robotics and Biomechatronics (BioRob) [Internet]. 2020 [cited 2026 Jan 7]. p. 396–402.

Tech Ventures Reference:

• CU25023

• Licensing Contact: Dovina Qu