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Low-Cost Gait Analysis for Behavioral Phenotyping of Mouse Models of Neuromuscular Disease
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Gait pattern in patients with different multiple sclerosis phenotypes.

Irena Dujmovic1, Sasa Radovanovic2, Vanja Martinovic3

  • 1Clinic of Neurology, Clinical Centre of Serbia, Dr Subotica 6, 11129 Belgrade 102, Serbia; University of Belgrade School of Medicine, Department of Neurology, Dr Subotica 6, 11129 Belgrade 102, Serbia.

Multiple Sclerosis and Related Disorders
|April 22, 2017
PubMed
Summary

Multiple sclerosis (MS) impairs gait, with primary-progressive MS (PPMS) showing more symmetry issues than relapsing-remitting MS (RRMS) at similar disability levels. Gait disturbance in MS reflects cognitive-motor interference and is linked to disability.

Keywords:
Cognitive-motor interferenceDisabilityDisease phenotypesGait patternMultiple sclerosis

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Area of Science:

  • Neurology
  • Biomechanics
  • Rehabilitation Science

Background:

  • Gait pattern is frequently impaired in multiple sclerosis (MS).
  • Gait characteristics across different MS phenotypes remain incompletely understood.
  • Understanding gait in MS is crucial for patient management and rehabilitation.

Purpose of the Study:

  • To elucidate spatio-temporal gait pattern characteristics in relapsing-remitting (RRMS) and primary-progressive (PPMS) MS phenotypes.
  • To compare gait parameters between MS phenotypes and healthy controls (HC).
  • To investigate the influence of cognitive-motor tasks on gait in MS.

Main Methods:

  • Analysis of spatio-temporal gait parameters (cycle time, stride length, gait velocity, etc.) in RRMS (n=52), PPMS (n=18), and HC (n=40) using GAITRite walkway.
  • Subjects performed standardized walking tasks, including dual and triple motor-mental tasks.
  • Calculation of symmetry indices for key gait parameters.

Main Results:

  • MS patients exhibited longer cycle time and double support time, shorter stride length, and lower gait velocity compared to HC.
  • Dual and triple tasks significantly impacted walking performance in both MS patients and HC.
  • While PPMS patients differed from RRMS patients, gait performance was similar at matched disability levels (EDSS 3.0-5.0), except for more impaired CT and ST symmetry in PPMS.
  • EDSS score correlated significantly with CT, DST, SL, and GV.

Conclusions:

  • Gait pattern disturbance in MS patients is phenotype-dependent and influenced by disability.
  • Cognitive-motor interference significantly impacts gait in multiple sclerosis.
  • Gait analysis provides valuable insights into the functional deficits associated with different MS phenotypes.