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SHIMMER: A new tool for temporal gait analysis.

Karol J O'Donovan1, Barry R Greene, Denise McGrath

  • 1Leixlip, Co. Kildare, Ireland.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
|December 8, 2009
PubMed
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The SHIMMER wireless sensor platform accurately measures temporal gait parameters during walking and running. This cost-effective technology aids in ambulatory monitoring and detecting functional movement changes in the ageing population.

Area of Science:

  • Biomedical Engineering
  • Wearable Technology
  • Gerontology

Background:

  • Effective ambulatory monitoring is crucial for detecting risk factors in the ageing population.
  • Flexible wireless sensor platforms are needed for measuring biomechanical and physiological variables in functional movement.

Purpose of the Study:

  • To assess the utility of the SHIMMER wireless sensor platform for ambulatory human gait analysis.
  • To validate the SHIMMER's ability to accurately measure temporal gait parameters.

Main Methods:

  • The SHIMMER platform, equipped with a tri-axial gyroscope, was used to collect gait data.
  • Temporal gait parameters (stance, stride, swing times) were derived from SHIMMER data.
  • SHIMMER data was simultaneously compared against measurements from the CODA motion analysis system.

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Main Results:

  • Excellent agreement (ICC(2, k) > 0.85) was observed between SHIMMER and CODA systems for stance, stride, and swing times.
  • Bland and Altman analysis showed minimal mean differences for stance (0.0087s), stride (0.0044s), and swing (-0.0061s) times.
  • High correlation was found across 10 walking and 4 running trials in a healthy adult male subject.

Conclusions:

  • The SHIMMER platform demonstrates high accuracy and reliability for temporal gait analysis.
  • It is a versatile and cost-effective tool for ambulatory monitoring of functional movement.
  • This technology holds potential for early detection of age-related movement changes.