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

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

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.

The overall goal of this research is to create a clinical toolkit to predict prosthesis use and function in the community. With this toolkit, clinicians will be able best determine an individual's K-Level designation, resulting in increased prosthesis use.

Aim 1: Determine whether a participant's prosthesis use matches the assigned K-level and/or self-reported goals and, if not, determine the reason(s) using an expert panel to evaluate data from performance-related measures, participant-reported measures, and smartphone and prosthesis sensors (clinical toolbox).

Aim 2: Quantify the effects of targeted physical intervention (prosthesis repair/refit, physical rehabilitation) or psychological intervention (motivational interviewing) or both on activity levels and patient goals.

Aim 3: Identify measure(s) that sensitively predict prosthesis use to create a clinically deployable toolkit to evaluate and optimize prosthesis use in the community.

Inclusion Criteria:

• Unilateral or bilateral lower limb amputation at transtibial or transfemoral level
• Ability to wear and use a prosthesis
• Designated K-level 2 - 4, or equivalent
• Prescription of definitive prosthesis
• Veterans Affairs participants must receive care through the Veterans Affairs or related remote-site clinic
• Age: 18-89 years-to reflect the age range of eligible participants at Department of Defense and Veterans Affairs study sites, including young, combat-injured Service Members and healthy older Veterans, aged 70-80.

Exclusion Criteria:

• Co-morbidities that limit prosthesis use, independently of prosthetic function, training, or motivation, such as stroke, obesity, severe traumatic brain injury, and neuralgia, which require interventions outside the scope of this study. Suitability to participate in the study will be determined by the individual's physician.
• Unable or unwilling to learn to use the smartphone app or to allow transmission of study data
• Unable or unwilling to provide informed consent
• Residing in an area with poor cell phone coverage