Innovation Hub

Predicting Connective Tissue Injury in Female Athletes and Identifying the Influence of Muscle Proteins in Determining Tissue Stiffness

Damien Callahan, Assistant Professor, Human Physiology

Females and males share identical cellular structure in muscle cells. However, subtle yet important differences in the proteins that make up these cells may explain differences in their mechanical properties, and defining the differences may account for the differences between sexes in injuries like ACL or Achilles tendon tears. By understanding the role that proteins play in (overused or stressed) muscles, we can develop more accessible and less invasive means to measure them, and ultimately develop methods to prevent tissue stress and injury – particularly in female athletes.

Targeting Oxygen Delivery in Female Athletes for Wu Tsai Human Performance Alliance

Christopher Minson, Kenneth M. and Kenda H. Singer Endowed Professor, Human Physiology

Females typically have lower levels of hemoglobin, iron, and red blood cell mass (which carries oxygen in the blood) compared to males. As oxygen delivery is a key determinant of exercise performance and health, safely raising oxygen-carrying capacity could have a large impact on performance and health. Evidence shows that we can increase red blood cell mass, by acclimating people to heat, and by their inhalation of low-levels of carbon monoxide, over time. No studies have focused these approaches on the female athlete, nor combined these approaches to determine whether they are synergistic in their impact on performance. These combined methods may have a large impact on oxygen carrying capacity and endurance performance in female athletes, and could ultimately be extrapolated more broadly to women with anemia or other low oxygen-carrying capacity.

Neural Representational Models for Reference Frame Transformation for Skilled Action

Michelle Marneweck, Assistant Professor, Human Physiology

To reach for a pen or line up for a free throw relies on extracting sensory information of the object relative to the eyes, the head, and the body and transforming that information into an actionable plan with the right movements. This project addresses how the central nervous system combines different sources of information into a coherent understanding of the body situated in the world so a person can act skillfully. A focus on female basketball players will classify how sensory information from different sources is best integrated in the brain, in order to identify ways different ways to enhance skilled physical performance, in males and females.

3D Anthropometric Scanning & Machine Learning to Understand Sex Patterned Performance Geometries of Runners

Susan Sokolowski, Professor and Director of Sports Product Design Program

This project will utilize machine learning to analyze 3D body scans of runners of different abilities from the Eugene area to understand and make predictions about sex-based performance geometries that are not possible with existing tools. The 3D scans will be combined with other data like demographics, product size preferences, experience/ ability, training, injury history, nutrition, recovery and sleep habits and analyzed to identify markers of high performance. By classifying patterns across body geometries and runners’ behaviors/experiences, this information (or these models) could eventually be used to provide person-specific interventions to improve running performance.