One in every three adults over 65 years-of-age will fall each year. According to the Centers for Disease Control and Prevention, approximately 2.8 million falls amongst the elderly resulted in over 800,000 hospitalizations and more than 21,000 fatalities. Predicting which elderly individuals are at highest risk for future falls is a matter of significant public health interest. Here, we will develop biomarkers of fall-risk using a newly developed (MoBI) system that allows for real-time measurement of brain electrical activity while participants walk in a virtual environment with simultaneously acquired quantitative gait markers using an infrared motion capture system.