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Related Experiment Video

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Home-Based Monitor for Gait and Activity Analysis
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Maximum walking speed in multiple sclerosis assessed with visual perceptive computing.

Anuschka Grobelny1, Janina R Behrens1, Sebastian Mertens1

  • 1Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, NeuroCure Cluster of Excellence, NeuroCure Clinical Research Center, Berlin, Germany.

Plos One
|December 16, 2017
PubMed
Summary
This summary is machine-generated.

Visual perceptive computing (VPC) using the Short Maximum Speed Walk (SMSW) reliably assesses gait in people with multiple sclerosis (PwMS). This objective method, superior to the timed 25ft walk (T25FW), correlates with disability and self-perceived impairment.

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Area of Science:

  • Neurology
  • Biomedical Engineering
  • Rehabilitation Science

Background:

  • Gait impairment is common in people with multiple sclerosis (PwMS), posing challenges for accurate assessment in clinical and research settings.
  • Previous pilot studies demonstrated the feasibility of visual perceptive computing (VPC) for gait analysis in PwMS using the Short Maximum Speed Walk (SMSW) over short distances (<4 meters).

Purpose of the Study:

  • To validate the SMSW as a quick, objective, and clinically relevant measure of gait in a large cohort of PwMS.
  • To compare the equivalence of SMSW gait parameters with the traditional timed 25ft walk (T25FW).
  • To investigate the association of SMSW-derived gait parameters with clinical disability (EDSS) and self-perceived walking impairment (MSWS-12).

Main Methods:

  • 95 PwMS and 60 healthy controls (HC) underwent gait assessment using a VPC system (Microsoft Kinect) for the SMSW, including immediate retests for reliability.
  • All participants also performed the T25FW.
  • PwMS were assessed using the Expanded Disability Status Scale (EDSS) and completed the 12-item Multiple Sclerosis Walking Scale (MSWS-12).

Main Results:

  • PwMS exhibited significantly reduced average speed and increased mediolateral deviation during SMSW compared to HC (p<0.001, p=0.002).
  • Average speed was the most reliable SMSW parameter (ICC > 0.977) and showed strong correlations with T25FW speed (r > 0.747, p<0.001) in both groups.
  • SMSW average speed demonstrated significant correlations with clinical disability (EDSS, r=-0.586, p<0.001) and self-perceived walking impairment (MSWS-12, r=-0.546, p<0.001).

Conclusions:

  • VPC-based SMSW reliably detects gait disturbances in PwMS over short distances, with high accuracy for maximum gait speed.
  • The SMSW's objective nature and simple setup make it a valuable tool for assessing gait in PwMS.
  • The strong associations with clinical disability and self-reported walking impairment support the SMSW's clinical relevance, suggesting superiority over T25FW.