Personalized Mobility Interventions Using Smart Sensor Resources for Lower-Limb Prosthesis Users

We propose to use a combination of smartphone-based sensors, next-generation flexible adhesive sensors, patient-reported outcome measures, focus groups, surveys, machine-learning, and data mining techniques to (i) identify and analyze factors that contribute to low prosthesis use and (ii) monitor the effect of targeted interventions to increase prosthesis use and improve overall performance with respect to activities of daily living and other real-world activities. Dr. Masha Kocherginsky is the Biostatistician on this study, and will be responsible for statistical analyses of the data. She will advise on data collection and data quality control, perform statistical analysis, interpret the results and participate in manuscript preparation.