ABSTRACT Falls are the leading cause of fatal and non-fatal injuries in older adults (ages 65+). Injuries due to falling result in 2.8 million emergency visits annually, and 25% of falls result in very serious injuries (such as fractures or traumatic brain injury). Through this diversity supplement, Dr. Monroe Kennedy, an engineer interested in aging research, seeks to get training and mentoring in geroscience. As part of this diversity supplement, Dr. Kennedy, proposes to develop a wearable smartbelt device that can alert the wearer to risk of falling and potentially prevent falls. Combined with a robust training plan, the proposed activities will prepare Dr. Kennedy to become a leader in geriatrics research and make impactful contributions to the field of aging research. Aim 1 will be to conduct focus groups with older adults on the wearable smartbelt device, such as style and comfort. Aim 2 will test the wearable smartbelt device by collecting visual and sensor data from older adults while walking on various surfaces at slow and brisk paces. The data will be used to train the falls prevention model utilizing machine learning methods. The ultimate goal is for the model to be able to calculate fall risk by predicting potential walking trajectories of the wearer and imbalance and alert the wearer via vibrotactile response if the risk of falling is probable. By preventing falls from occurring in the first place, the proposed device has the potential to greatly increase the overall well-being, long-term health, and independence of older adults as well as costs associated with hospital visits and caregiving.