This study aims to collect data to improve gait function in individuals with Diabetic Peripheral Neuropathy (DPN).

The primary goals are to evaluate:

• Biomechanical mechanisms contributing to abnormal plantar pressure and propulsion during gait in individuals with DPN
• Biofeedback-induced changes in plantar pressure, propulsion, and biomechanics during gait in individuals with DPN

The participants will be required to complete

• Questionnaires
• Clinical examination
• 3-Dimensional gait analysis on an instrumented treadmill
• Visual and auditory biofeedback on the participant's propulsion and plantar pressure metrics provided by a projector screen during walking

Over 38 million adults in the United States (~1 in 7) are living with Diabetes Mellitus (DM), of which diabetic peripheral neuropathy (DPN) is the most common complication, affecting more than 50% of individuals with DM. DPN causes both sensory and motor impairments of the foot and ankle, leading to reduced functional mobility and increased ulceration and amputation risk. Propulsion and plantar pressure are two key interrelated gait parameters contributing to walking function and ulceration risk, respectively. Real-time biofeedback is a non-invasive rehabilitation strategy with significant promise for targeting gait impairments by providing the user with quantitative information regarding a targeted performance variable.

In this study, the team will evaluate multi-joint lower extremity biomechanical responses to univariate propulsion and plantar pressure biofeedback. Secondly, the team will use identified biomechanical compensations to propulsion and plantar pressure biofeedback to develop a multi-variable, implicit, individualized visual biofeedback program to improve gait function in individuals with DPN. Insights into the biomechanical mechanisms underlying plantar pressure and propulsion in people with DPN will allow us to design more informed and effective gait rehabilitation interventions aimed at preventing deleterious outcomes such as ulceration and amputation that can be tailored to individual patient characteristics.

Inclusion Criteria:

• Able to walk 10-meters independently without an assistive device
• Sufficient cardiovascular and musculoskeletal health to walk on a treadmill for 6 minutes at a self-selected speed
• Diagnosis of diabetes mellitus
• Diagnosis of diabetic peripheral neuropathy by a physician
• Foot examination within the past 6 months documenting ambulatory status
• Physician clearance

Exclusion Criteria:

• History of amputation
• Active ulceration
• Medial column deformity
• Severe cognitive impairment (MoCA < 10)
• Severe visual impairment
• History of Charcot osteoarthropathy
• History of posterior muscle group lengthening
• History of lower extremity joint replacement
• History of lower extremity and/or foot surgery affecting walking mechanics
• Orthopaedic problems of the lower limbs or spine due to other medical conditions (not diabetes or DPN) that limit walking or cause pain during walking
• Improper footwear for walking and community ambulation
• Cardiovascular or medical condition affecting ability to walk safely
• History of unexplained dizziness or fainting in the past 2 months
• Allergy to adhesive tape or rubbing alcohol

Data on demographics, medical history, clinical evaluation, questionnaires, walking biomechanics, and plantar pressure data will be collected from individuals (N = 25) with diabetic peripheral neuropathy. Subject-level de-identified data will be preserved and shared in raw and pre-processed forms in ".csv" and ".xlsx" format. Biomechanics data will be processed and saved in ".c3d" formatted files as per standard practice in the field of biomechanics.

All data will be deposited 6 months following the completion of the study. At a minimum, the data will be made available for 3 years after the completion of the study.

Raw and pre-processed data will be archived through the National Institute of Child Health and Human Development (NICHD) Data and Specimen Hub (DASH). Processed biomechanics data will be archived through SimTK. The archived data will be assigned digital object identifiers (DOI). Both NICHD DASH and SimTK are made available through web-accessible repositories at no cost to users.