Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Video

Updated: Apr 21, 2026

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

14.5K

Inertial sensor-based stride parameter calculation from gait sequences in geriatric patients.

Alexander Rampp, Jens Barth, Samuel Schülein

    IEEE Transactions on Bio-Medical Engineering
    |November 13, 2014
    PubMed
    Summary
    This summary is machine-generated.

    Related Concept Videos

    You might also read

    Related Articles

    Articles linked to this work by shared authors, journal, and citation graph.

    Sort by
    Same author

    Engagement with the national electronic health records by people with Parkinson's disease.

    Frontiers in aging neuroscience·2026
    Same author

    The future digital outpatient clinic for movement disorders: from technological innovation to ethical and systemic implementation-a position paper.

    Journal of neural transmission (Vienna, Austria : 1996)·2026
    Same author

    Value in App Store Data and User Reviews: Quality Assessment of Parkinson's and Alzheimer's Disease Apps.

    Studies in health technology and informatics·2026
    Same author

    Sensor-Derived Parameters from Standardized Walking Tasks Can Support the Identification of Patients with Parkinson's Disease at Risk of Gait Deterioration.

    Bioengineering (Basel, Switzerland)·2026
    Same author

    Moving beyond the hospital: in-depth characterization of daily-life mobility in patients with atypical Parkinsonian disorders.

    NPJ Parkinson's disease·2026
    Same author

    Data-driven clinical decision support tool for diagnosing mild cognitive impairment in Parkinson's disease.

    NPJ Parkinson's disease·2026
    Same journal

    Fast Prospective Motion Correction for MRI Based on Electromagnetic Induction Coils with Low Footprint and In-place Calibration.

    IEEE transactions on bio-medical engineering·2026
    Same journal

    Digital Twin Modeling of MR Gradient Coils for Accurate Gradient Safety Evaluation of Implantable Medical Devices.

    IEEE transactions on bio-medical engineering·2026
    Same journal

    A Method for Improving Human Joint Moment Estimation during Lower Limb Rehabilitation Training Based on sEMG Signals.

    IEEE transactions on bio-medical engineering·2026
    Same journal

    Assessment of skin stiffness in systemic sclerosis using optical coherence elastography: A comparative study with histology and clinical parameters.

    IEEE transactions on bio-medical engineering·2026
    Same journal

    Modeling Dyadic Interdependence in Endocrine Functioning: A Multilevel Machine Learning Study of Adults with Cancer and Their Caregivers.

    IEEE transactions on bio-medical engineering·2026
    Same journal

    A Kalman Filter-Based Framework for Granger Causality Assessment: Application in Tracking Maternal-Fetal Heart Rate Coupling.

    IEEE transactions on bio-medical engineering·2026
    See all related articles

    A new mobile gait analysis system using inertial sensors accurately measures walking parameters in elderly individuals. This system offers a reliable method for diagnosing gait impairments and monitoring long-term mobility.

    Area of Science:

    • Biomedical Engineering
    • Gerontology
    • Rehabilitation Science

    Background:

    • Gait impairments are common in the elderly, necessitating objective analysis for diagnosis and management.
    • Current gait analysis methods may lack practicality for widespread clinical use or long-term monitoring.
    • Mobile systems are needed for accessible, quantitative gait assessments.

    Purpose of the Study:

    • To present a novel method for computing clinically relevant temporal and spatial gait parameters using a shoe-mounted inertial sensor system.
    • To validate the accuracy and reliability of this mobile gait analysis system against a gold standard (GAITRite).
    • To assess the system's performance in elderly individuals, including those using walking aids.

    Main Methods:

    • Ankle-mounted accelerometers and gyroscopes were used to capture gait data.

    More Related Videos

    Home-Based Monitor for Gait and Activity Analysis
    07:24

    Home-Based Monitor for Gait and Activity Analysis

    Published on: August 8, 2019

    7.5K
    Clinical-oriented Three-dimensional Gait Analysis Method for Evaluating Gait Disorder
    06:54

    Clinical-oriented Three-dimensional Gait Analysis Method for Evaluating Gait Disorder

    Published on: March 4, 2018

    15.0K

    Related Experiment Videos

    Last Updated: Apr 21, 2026

    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

    14.5K
    Home-Based Monitor for Gait and Activity Analysis
    07:24

    Home-Based Monitor for Gait and Activity Analysis

    Published on: August 8, 2019

    7.5K
    Clinical-oriented Three-dimensional Gait Analysis Method for Evaluating Gait Disorder
    06:54

    Clinical-oriented Three-dimensional Gait Analysis Method for Evaluating Gait Disorder

    Published on: March 4, 2018

    15.0K
  • Temporal gait events were detected through signal feature analysis.
  • Stride length was calculated via double integration of gravity-compensated accelerometer data, with sensor drift correction.
  • Validation involved 101 elderly participants (mean age 82.1 years) performing walking tests with and without a wheeled walker, comparing results with GAITRite.

    • Main Results:

    • The inertial sensor system demonstrated high correlations with GAITRite for stride length (0.93) and stride time (0.95).
    • The absolute error for stride length was 6.26 cm during normal walking.
    • The system accurately captured increased stride length when using a wheeled walker, unlike the GAITRite system which was interfered with by the walker.

    Conclusions:

    • The developed inertial sensor-based algorithm provides a clinically relevant and accurate method for gait parameter calculation.
    • This mobile system is suitable for both diagnostic workup and long-term monitoring of gait in the elderly population.
    • The system's robustness to walking aids offers an advantage over traditional systems.