Engineering for athletes to exceed their limits

MIT 3-Sigma Sports aims to solve the biggest engineering problems across sports. The program connecting students and faculty with alumni and industry partners who work together to improve athletic performance by using engineering to enhance endurance, speed, accuracy, and agility in sports.

Graduate students and former varsity athletes Sarah Fay and Jacob Rothman have both found ways to bridge their personal passions with their academic pursuits. Fay, who played squash and field hockey as an undergraduate at MIT, is working to identify the optimal weight for squash rackets by modeling the swing of a racket based on a person’s height and weight. Rothman, who played on MIT’s baseball team as an undergraduate, is co-founder of Perch, a company that uses 3-D cameras to assess the velocity of a weightlifter’s movements and provide instant feedback on how to improve form and minimize the risk of injury.

Professor Sang-Gook Kim and his students have designed an energy-harvesting shoe to convert each stride into power. Air bladders embedded in the sole of the shoe convert the foot’s impact into airflow along the runner’s gait. Both the outflow and inflow from the airbladders are directed at a dual-microturbine enclosure, which generates electricity that can be used to power the runner’s device of choice.

The results produce 90 milliwatts of power for walking at 3 mph and a staggering 900 milliwatts when jumping. This means that six hours of walking can generate enough power to charge an iPhone battery by 50 percent. “You can do a lot with that power,” Kim says. “Joggers won’t get lost and can get help quickly in emergencies.”

The next step for Kim will be working with a top manufacturer on designing a shoe that can incorporate this energy-harvesting technology.

There are competing energy harvesting shoes in development. The University of Wisconsin and instepnano have a system for fully charging an iPhone from 4 hours of walking.

Engineering and Emmy Awards rarely go hand-in-hand — unless you’re Principal Research Scientist Brian Anthony, who won an Emmy for his work on Swing Vision for CBS prior to coming back to MIT. Swing Vision uses two cameras, one recording 2,000 frames per second and the other recording 12,500 frames per second. The slower video is used by on-air commentators to analyze a golfer’s swing, while the fast video is used to gather stats about the velocity, launch angle, and backspin of the club and ball for each of their shots.

Anthony is now using his background in video instrumentation to develop event detection and similarity algorithms that can be used for manufacturing process control, medical diagnostics, and sports. Videos of a gold-standard athletic move — the perfect plié or right hook, for example — are compared to a new video of the move. “By comparing the two videos, you can make decisions based on the time-space path that one video follows after another,” he explains.

The algorithm then provides guided instructions for how the subject can best emulate the gold standard.

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