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Related Experiment Video

Updated: Jan 10, 2026

Substantiating Appropriate Motion Capture Techniques for the Assessment of Nordic Walking Gait and Posture in Older Adults
09:37

Substantiating Appropriate Motion Capture Techniques for the Assessment of Nordic Walking Gait and Posture in Older Adults

Published on: May 12, 2016

9.1K

Using 3D skeleton tracking for gait analysis in older adults compared to a kinect-based mobility analysis system.

Kathrin Raeder1, Nicole Strutz2,3,4, Simone Kuntz1

  • 1Geriatrics Research Group, Charité - Universitätsmedizin Berlin (corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin), Berlin, Germany.

BMC Geriatrics
|November 26, 2025
PubMed
Summary

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Smartphone camera apps show good agreement with advanced systems for measuring older adults' gait parameters, aiding fall risk assessment. This technology can help identify mobility issues and reduce fall risks in seniors.

Area of Science:

  • Gerontology
  • Biomedical Engineering
  • Rehabilitation Technology

Background:

  • Falls are a significant concern for older adults, who often underestimate their fall risk.
  • Mobility and fall risk assessment tools are crucial for early detection and intervention.
  • Smartphone camera applications offer a potential solution for accessible fall risk assessment.

Purpose of the Study:

  • To compare the agreement between a smartphone camera-based application (SCA) with 3D skeleton tracking and the Microsoft Kinect System (MKS) for mobility analysis.
  • To evaluate the reliability of SCA in measuring spatiotemporal gait parameters in older adults.

Main Methods:

  • A cross-sectional study design was employed.
  • 186 datasets from 31 older adults were collected.
Keywords:
AppGait parameterMovementNew algorithmOlder adultsSmartphone

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Last Updated: Jan 10, 2026

Substantiating Appropriate Motion Capture Techniques for the Assessment of Nordic Walking Gait and Posture in Older Adults
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  • Gait analysis was performed using both SCA and MKS across two gait modes: comfort and fast.

    • Main Results:

    • For comfort mode gait, Intraclass Correlation Coefficient (ICC) values ranged from 0.74 for gait speed to 0.85 for cadence.
    • For fast mode gait, ICC values ranged from 0.66 for gait speed to 0.81 for cadence.
    • Both systems demonstrated good agreement (ICC > 0.75) for most spatiotemporal gait parameters, except for gait speed.

    Conclusions:

    • The smartphone camera application (SCA) shows good agreement with the MKS for measuring spatiotemporal gait parameters in older adults.
    • SCA has potential as a reliable and practical tool for clinical gait analysis.
    • This technology can aid in identifying fall risks and improving mobility assessments in the geriatric population.