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Related Experiment Video

Updated: May 29, 2026

Lower-Limb Biomechanical Characteristics Associated with Unplanned Gait Termination Under Different Walking Speeds
05:52

Lower-Limb Biomechanical Characteristics Associated with Unplanned Gait Termination Under Different Walking Speeds

Published on: August 25, 2020

Extracting gait parameters from raw electronic walkway data.

André Dias1, Lukas Gorzelniak, Angela Döring

  • 1Norwegian Centre for Integrated Care and Telemedicine, University Hospital of North Norway, Tromsø, Norway. andre.dias@uit.no

Studies in Health Technology and Informatics
|September 7, 2011
PubMed
Summary
This summary is machine-generated.

Wearable accelerometers offer a cost-effective method for measuring spatiotemporal gait parameters. This study found ankle-mounted accelerometers to be reliable for daily life gait analysis, aiding in detecting gait impairments.

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Area of Science:

  • Biomechanics
  • Wearable technology
  • Gerontology

Background:

  • Spatiotemporal gait parameters are crucial for identifying gait impairments and related health conditions.
  • Traditional measurement methods (e.g., electronic walkways, force plates) are expensive and lab-bound.
  • Advancements in raw data accelerometers present a potentially affordable and versatile alternative for gait analysis.

Purpose of the Study:

  • To evaluate the feasibility of using raw data accelerometers for gait analysis.
  • To compare accelerometer data with established methods like GAITRite.
  • To identify optimal accelerometer placement for reliable gait parameter extraction.

Main Methods:

  • A feasibility study involving 50 participants from the KORA-Age project.
  • Utilized GAITRite systems and Actigraph GT3X accelerometers for data collection.
  • Developed and open-sourced a software package for processing GAITRite raw data.
  • Investigated accelerometer placement, focusing on the ankle.

Main Results:

  • The ankle emerged as the most promising location for accelerometer placement.
  • Accelerometer-based gait parameter extraction was found to be simple and reliable.
  • Data suggests accelerometers can effectively capture gait parameters in real-world settings.

Conclusions:

  • Raw data accelerometers are a viable, low-cost tool for gait analysis.
  • Ankle-mounted accelerometers demonstrate reliability for everyday gait monitoring.
  • This technology facilitates accessible detection of gait impairments outside laboratory settings.