Ongoing research efforts across the Alliance are pushing the boundaries of our understanding and optimization of human performance. This session highlighted some of those late-breaking findings and provided a preview of research to be explored through the posters and demos.

Samuel Benabou from Stanford University presented his research validating a new wearable technology that doesn’t rely on a person’s heart rate or wrist movements like typical smartwatches but instead uses leg movements. “We found that our leg kinematics device had about 40 percent less error than leading smartwatches on the market.”

Meghan Keating from Boston Children’s Hospital discussed new methods to predict female athlete menstrual status. “It’s difficult to find a specific target when using BMI or percent expected body weight in these female athletes… so we thought relative fat content might be a useful marker to determine adequate energy storage to support normal reproductive function.” Her preliminary research results show that a percent fat measurement based on Dual-Energy X-Ray Absorptiometry (DEXA) might be a good clinical tool to predict menstrual dysfunction in female athletes.

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