Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD)
Boston Children's Hospital, Boston, MA, USA
Spinal muscular atrophy (SMA) and Duchenne muscular dystrophy (DMD) are genetic disorders that often result in progressive weakness and impaired function. Our recent findings suggest that novel machine-learning (ML)-based abstraction models may map noisy signals from foot-worn sensors (namely, instrumented insoles developed by the project team) into accurate and clinically relevant spatiotemporal and kinetic gait parameters. These gait parameters derived from instrumented insoles may serve as functional biomarkers to detect changes in real world function. All participants will be observed and measured while wearing the instrumented insoles in the lab and in real-life environments.
Age
5–any
Sex
ALL
Healthy volunteers
Accepted
You may be eligible if
Genetic confirmation of disease (DMD, SMA) or healthy control
Able to walk independently at least 25 meters
Ongoing corticosteroids therapy or initiation of corticosteroid therapy in the previous 3 months for DMD
Stable dose of FDA approved SMN up-regulator therapy or in an open-label extension phase of a study treatment for at least 6 months for SMA or gene replacement at enrollment for SMA or DMD participants.
You may not be if
Use foot orthoses or assistive devices for community ambulation or a mobility device for community navigation
Use investigational medications intended for treatment of NMD within 30 days
Prior to study entry had an injury or surgery that would impact gait within the previous 3 months
Clareo Health | Establishing Walking-related Digital Biomarkers in Rare Childhood Onset Progressive Neuromuscular Disorders
