Researchers in the Wu Tsai Human Performance Alliance are integrating the technology into training footwear to provide a data-driven approach to improving athletic performance
Shear forces — unaligned forces pushing one part of the body in one direction, and another part of the body in the opposite direction — can lead to injuries and other problems for athletes. Shear sensors can provide measurements that may be a useful feedback mechanism for improving performance among athletes. A collaborative group of researchers at the University of Oregon’s Phil and Penny Knight Campus for Accelerating Scientific Impact, Bowerman Sports Science Center, and Sport Product Design Program teamed up under the Wu Tsai Human Performance Alliance at Oregon to develop an innovative new wearable sensor for measuring shear forces.
The new technology, an optical-based sensor, which measures shear strain based on the relative change in light of different wavelengths reflected from a surface of unique color pattern, is the subject of a new paper appearing in the March 2022 edition of the journal Sensors and Actuators.
“Wearable shear force sensors can provide real-time quantitative feedback to athletes and coaches,” said Michael McGeehan, the lead author on the paper and a postdoctoral scholar in the Knight Campus. “Integrating these sensors into training footwear could provide a data-driven approach to improve athletic performance.”
Importantly, McGeehan says, the new sensing technique presented in the paper allows determination of directionality of shear measurements, overcoming a major limitation of other optical-based shear sensors. These properties — along with its small size, low-cost, and scalable design — support the use of this sensor and sensing paradigm for a variety of biomedical and robotics applications.
Contributing authors on the paper included Michael Hahn, an associate professor in the Department of Human Physiology and the director of the Bowerman Sports Science Center; Salil Karipott, a postdoctoral scholar in the Knight Campus; Keat Ghee Ong, a professor in the Knight Campus; and Maryam Shuaib, an undergraduate researcher and research assistant in the Ong Lab.
This work was supported by the Wu Tsai Human Performance Alliance and the Joe and Clara Tsai Foundation.