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Related Experiment Video

Updated: Dec 29, 2025

Clinical Assessment of Spatiotemporal Gait Parameters in Patients and Older Adults
08:56

Clinical Assessment of Spatiotemporal Gait Parameters in Patients and Older Adults

Published on: November 7, 2014

14.2K

Spatio-temporal gait variables predicted incident disability.

Takehiko Doi1, Sho Nakakubo2, Kota Tsutsumimoto2

  • 1Department of Preventive Gerontology, Center for Gerontology and Social Science, National Center for Geriatrics and Gerontology, 7-430, Morioka, Obu, Aichi, 474-8511, Japan. take-d@ncgg.go.jp.

Journal of Neuroengineering and Rehabilitation
|February 1, 2020
PubMed
Summary
This summary is machine-generated.

Gait analysis in older adults can predict future disability. Specific measures like gait speed and stride length are key indicators for assessing risk and preventing dependency.

Keywords:
FrailtyMobilityPhysical functionSarcopenia

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Last Updated: Dec 29, 2025

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Area of Science:

  • Gerontology
  • Biomedical Engineering
  • Public Health

Background:

  • Assessing disability risk in older adults is crucial for developing effective prevention and intervention strategies.
  • This study aimed to investigate the relationship between spatio-temporal gait characteristics and the onset of disability in an elderly population.

Purpose of the Study:

  • To examine the association between spatio-temporal gait variables and incident disability among older adults.
  • To determine if quantitative gait analysis can serve as a tool for predicting future disability in this demographic.

Main Methods:

  • A prospective community-based study involving 4121 older adults (≥ 65 years).
  • Baseline measurements included gait speed, cadence, stride length, and stride length variability using an electronic gait measuring device.
  • Disability was tracked through long-term care insurance records over a mean follow-up of 49.6 months.

Main Results:

  • A total of 425 participants developed incident disability during the follow-up period.
  • Low function in gait speed (HR 2.06), stride length (HR 2.17), cadence (HR 1.49), and stride length variability (HR 1.46) significantly predicted disability.
  • A cumulative relationship was observed between the number of low-functioning gait variables and subsequent disability (p < .001).

Conclusions:

  • Spatio-temporal gait variables possess significant predictive value for incident disability in older adults.
  • Quantitative and multifaceted gait analysis offers a valuable approach for assessing disability risk.
  • These findings support the integration of gait analysis into routine health assessments for elderly individuals to proactively manage disability.