Researchers in the Center for Orthopaedic and Biomechanics Research are helping collect data about the characteristics in children who have been diagnosed with Autism Spectrum Disorder.
Ron Pfeiffer, associate dean of the College of Health Sciences and executive director for the center, and Jeff Eggleston, research associate for the center, are participating in a funded research project led by Janet Dufek, a faculty member in the Department of Kinesiology and Nutrition Sciences at the University of Nevada, Las Vegas.
The team is collecting pilot data to investigate the variability in gait characteristics in children who have been diagnosed with Autism Spectrum Disorder compared to healthy age- and gender-matched children. Three dimensional (3D) motion capture along with ground-reaction force technology is being used to collect participants’ kinematic (measures of linear and angular motion) and kinetic (measures of mass and force) to characterize the gait patterns of these children.
The findings of this study will aid in establishing a common description of gait characteristics in children with Autism Spectrum Disorder. Since the study is collecting pilot data, the findings also will guide avenues for future research, such as intervention treatment plans and therapeutic modalities, and potentially increase the dichotomy of the diagnosis of Autism Spectrum Disorder. This study also is including individuals described as toe-walkers, who previously have been omitted from Autism Spectrum Disorder gait studies.
There is growing interest in learning more about the characteristics of Autism Spectrum Disorder. The research team hopes to determine if children diagnosed with the disorder exhibit a greater amount of variability in gait characteristics than children not diagnosed with Autism Spectrum Disorder and to determine if toe-walking children with the disorder exhibit markedly different gait characteristics than age- and gender-matched healthy children.
Research reported in this article was supported by the Mountain West Clinical Translational Research-Infrastructure Network under a grant from National Institute of General Medical Sciences of the National Institutes of Health under Award Number 1U54GM104944. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.