Discipline: Technology and Engineering
Subcategory: Biomedical Engineering
Session: 3
Room: Exhibit Hall A
Nicole Vigon - University of Wisconsin-Milwaukee
Co-Author(s): Anahita A. Qashqai, University of Wisconsin-Milwaukee, Milwaukee, Alyssa J. Schnorenberg, University of Wisconsin-Milwaukee, Milwaukee, Donald G. Basel, Children's Hospital, Milwaukee, Brooke A Slavens, University of Wisconsin-Milwaukee, Milwaukee
Hypermobile Ehlers-Danlos Syndrome (hEDS) is an inherited connective tissue disorder that is caused by a defect in the protein collagen. This disorder affects as many as 1 in 5000 people worldwide. Symptoms include overly flexible joints that can more easily dislocate, creating joint instability, which leads to early-onset osteoarthritis. There is currently a lack of knowledge on the functional effects of these symptoms on gait in children with hEDS. This study aims to quantify temporal-spatial kinematic characteristics of gait, in an effort to define the phenotype of hEDS. Six participants with hEDS (mean age of 13.7 years old) were recruited from the Genetics Center at Children’s Hospital of Wisconsin. The subjects underwent three-dimensional motion analysis using a 15-camera Vicon T Series system with 14 retro-reflective markers. The subjects completed 8-10 trials at a self-selected, fast, and slow walking speed along a 30-ft walkway. Data was labeled, filtered, and modeled using Vicon Nexus software and the lower extremity Plug-in Gait model. Stride length, walking speed, stance duration, and cadence were calculated for multiple gait cycles per subject for each walking speed. The mean self-selected speed results for these parameters were 1.27 ± 0.156 m, 1.24 ± 0.067 m/s, 37.78 ± 1.94% and 59.46 ± 7.19 strides/min, respectively. While group means were within normal ranges for all gait parameters, inspection of patient specific metrics were found to be different from normal as reported from literature. Identification of patient specific differences between those with hEDS and healthy individuals may provide insight to determine the underlying mechanisms of pain and injury, to mitigate the risk for early-onset osteoarthritis. Quantitative gait analysis findings will provide rehabilitation engineers, therapists, and physicians with a better understanding of pathological human movement. This work will lead to improved diagnosis and rehabilitation for children and youths with hEDS.
Funder Acknowledgement(s): Supported by the Genetic Center of the Children's Hospital of Wisconsin. A special thanks to the Stimulus Package to Accelerate Research Clusters (SPARC) grant and the Senior Excellence in Research Award (SERA).
Faculty Advisor: Brooke Slavens, slavens@uwm.edu
Role: I was apart of every aspect of this component of the research project. This project is apart of a much larger ongoing project, partnered with Children's Hospital in Milwaukee. I assisted with motion capture data collection. As well as data labeling, filtering and modeling using Vicon Nexus software. Lastly I calculated using Vicon Nexus, then analyzed the temporal spatial gait data.