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Footfall Placement Variability and Falls in Multiple Sclerosis

Overview of attention for article published in Annals of Biomedical Engineering, November 2012
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Title
Footfall Placement Variability and Falls in Multiple Sclerosis
Published in
Annals of Biomedical Engineering, November 2012
DOI 10.1007/s10439-012-0685-2
Pubmed ID
Authors

Michael J. Socie, Brian M. Sandroff, John H. Pula, Elizabeth T. Hsiao-Wecksler, Robert W. Motl, Jacob J. Sosnoff

Abstract

Gait variability (i.e., fluctuations in walking) provides unique information about the control of movement and is associated with falls. This investigation examined the association between gait variability and falls in persons with multiple sclerosis (MS) and healthy controls. Traditional distributional metrics of gait variability (i.e., coefficient of variation (CV)) and a novel metric based on Fourier series analysis of footfall placement variability were determined for 41 individuals with MS and 20 age- and sex-matched controls. Spatiotemporal parameters of gait were collected using a 7.9 m electronic walkway that recorded individual footfalls during steady state comfortable walking. Persons with MS were divided into two groups based on fall history (non-fallers and recurrent fallers). Overall, persons with MS had greater gait variability than controls as indexed by CV and Fourier-based variability (p's < 0.05). Moreover, recurrent fallers with MS had greater Fourier-based variability than non-fallers with MS (p = 0.025), whereas there was no difference in MS groups in traditional gait variability metrics (p > 0.05). These observations highlight that footfall placement variability is related to fall status in MS. Future work determining the sensitivity of footfall placement variability to dysfunction is warranted.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 83 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 2%
Unknown 81 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 19 23%
Student > Master 15 18%
Student > Bachelor 9 11%
Researcher 8 10%
Other 5 6%
Other 13 16%
Unknown 14 17%
Readers by discipline Count As %
Medicine and Dentistry 20 24%
Engineering 16 19%
Sports and Recreations 7 8%
Nursing and Health Professions 6 7%
Neuroscience 4 5%
Other 12 14%
Unknown 18 22%