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Related Experiment Video

Updated: Oct 16, 2025

Clinical-oriented Three-dimensional Gait Analysis Method for Evaluating Gait Disorder
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Remote Gait Type Classification System Using Markerless 2D Video.

Pedro Albuquerque1, João Pedro Machado2, Tanmay Tulsidas Verlekar3

  • 1Instituto de Telecomunicações, Instituto Superior Técnico, Universidade de Lisboa, Av. Rovisco Pais 1, 1049-001 Lisboa, Portugal.

Diagnostics (Basel, Switzerland)
|October 23, 2021
PubMed
Summary

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This study introduces the GAIT-IT dataset for gait analysis and a new AI system that efficiently detects gait pathologies. The system, integrated into a web app, aids remote healthcare by classifying walking patterns.

Area of Science:

  • Biomedical Engineering
  • Computer Vision
  • Artificial Intelligence

Background:

  • Pathological gaits affect human mobility and health.
  • Gait analysis aids in diagnosing conditions and assessing recovery.
  • Vision-based systems offer potential for remote, unconstrained gait analysis.

Purpose of the Study:

  • To introduce the GAIT-IT dataset, a novel resource for pathological gait analysis.
  • To develop an efficient, vision-based automatic gait analysis system.
  • To integrate the system into a user-friendly web application for remote healthcare.

Main Methods:

  • Collected GAIT-IT dataset from 21 subjects simulating five gait types at two severity levels.
  • Trained a novel deep learning model for automatic gait analysis.
Keywords:
assisted livinggait classificationpathology identificationremote diagnosisweb application

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  • Developed a prototype web application for remote gait classification and pathology association.

    • Main Results:

    • The GAIT-IT dataset is larger and more controlled than existing datasets.
    • The novel system significantly reduces computational requirements (parameters, memory, time) compared to state-of-the-art.
    • Classification accuracy is comparable to existing methods.

    Conclusions:

    • The GAIT-IT dataset and developed system advance vision-based pathological gait analysis.
    • The system's efficiency and web integration support remote healthcare applications.
    • The user-friendly interface facilitates use by both professionals and laypersons for gait assessment.