Personalized Mobility Interventions Using Smart Sensor Resources for Lower-Limb Prosthesis Users (NCT03930199)

🩺 Plain-English Summary (8th-Grade Level)

The goal of this research is to analyze data from smartphone-based and wearable sensors, using advanced machine-learning and data-mining techniques, and to combine this information with performance-based measures, participant-reported measures, and structured interviews to create a clinical toolbox to (i) identify individuals who exhibit reduced prosthesis use (compared to expected usage levels based on K-level designation and/or participant goals of community mobility and social interaction), (ii) identify prosthetic/physical and psychological factors that limit prosthesis use, and (iii) determine the effect of targeted interventions to increase prosthesis use and facilitate achievement of participant goals. Objective sensor-based measurement of home and community activities will allow for the correlation of real-world function to in-clinic assessments and to monitor changes resulting from rehabilitation interventions in real time. Machine-learning and data mining techniques will be used to identify a subset of measures from this toolbox that sensitively and accurately reflect real-world function, enabling clinicians to predict and assess activity and provide effective interventions to optimize prosthesis use. The goal of this project, to improve overall performance with respect to activities of daily living and other real-world activities, thus addresses the Fiscal Year 2017 (FY17) Orthotics and Prosthetics Outcomes Research Program (OPORP) Focus Area of Orthotic or Prosthetic Device Function.

Who can join: Review the eligibility criteria below.

Location: Shirley Ryan AbilityLab — Chicago, Illinois

Age range: 18 Years to 89 Years