Here is Henry Do (above) and Michael Pollind (above) presenting their research on the use of wearable sensors in fall risk assessment in older adults.
Here is Sharon Kim presenting her work with machine learning/deep learning algorithms and idiopathic toe-walking in adolescents. Sharon used these tools to classify toe-toe walking vs. heel-toe walking and build an accurate model.
Harbir Bhatti presents his research involving Gait Real-Time Analysis Interactive Lab (GRAIL) and fall risk assessment in elderly people. Using sensory perturbations and gait parameters analysis, Harbir creates a model assessing fall risk.
Christopher Hoang presents the research from “Gait Rehab Lab” at the Orange Research Expo for Undergraduates, Chapman University. The lab designs and fabricates the sensors and their housing, ranging from bed sore sensor applications to therapy shoes to correct idiopathic toe-walking in children. They also study the dynamic stability of older adults using slip, trip, and medial-lateral perturbations by examining gait parameters (e.g. step length, step width).