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Home-Based Monitor for Gait and Activity Analysis
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Gait Variability to Phenotype Common Orthopedic Gait Impairments Using Wearable Sensors.

Junichi Kushioka1, Ruopeng Sun1,2, Wei Zhang3

  • 1Department of Orthopaedic Surgery, Stanford University, Stanford, CA 94305, USA.

Sensors (Basel, Switzerland)
|December 11, 2022
PubMed
Summary

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Gait variability measured by foot-mounted sensors during the 6-minute walk test can distinguish between different mobility impairment pathologies. This method shows promise for phenotyping neurogenic and joint diseases based on gait patterns.

Area of Science:

  • Biomedical Engineering
  • Clinical Biomechanics
  • Neurology

Background:

  • Mobility impairments are common in age-related diseases, affecting gait.
  • Distinguishing between different causes of mobility disorders using gait analysis is challenging.
  • Foot-mounted inertial measurement units (IMUs) offer a potential tool for detailed gait phenotyping.

Purpose of the Study:

  • To determine if gait parameters from IMUs during the 6-minute walk test (6MWT) can differentiate mobility impairments in Lumbar Spinal Stenosis (LSS) and Knee Osteoarthritis (KOA).
  • To investigate gait variability as a potential biomarker for phenotyping distinct pathologies causing mobility loss.

Main Methods:

  • Collected bilateral foot-mounted IMU data during the 6MWT from 30 participants (10 LSS, 10 KOA, 10 healthy controls).
Keywords:
gait impairmentgait variabilityknee osteoarthritislumbar spinal stenosiswearable IMU sensor

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  • Derived 11 gait parameters across pace, rhythm, asymmetry, and variability domains for each minute of the 6MWT.
  • Analyzed minute-by-minute gait parameter differences between control and disease groups, and between LSS and KOA groups.

    • Main Results:

    • Gait parameters in all four domains distinguished controls from both disease groups over the entire 6MWT.
    • No significant statistical differences were found between LSS and KOA groups initially, though stride length variability trended higher in LSS (p=0.057).
    • Stride length variability became a significant differentiator between LSS and KOA during the 3rd (p≤0.05) and 4th (p=0.06) minutes of the 6MWT.

    Conclusions:

    • Gait variability measures show potential as biomarkers for phenotyping mobility impairments from different pathologies.
    • Increased gait variability reflects a loss of gait rhythmicity, common in neurological impairments like LSS.
    • The middle portion of the 6MWT (minutes 3-4) is identified as a key window for detecting subtle gait differences between distinct mobility impairment origins.