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SANE (Easy Gait Analysis System): Towards an AI-Assisted Automatic Gait-Analysis.

Dario Sipari1, Betsy D M Chaparro-Rico2, Daniele Cafolla2

  • 1Department of Control and Computer Engineering, Mechatronic Engineering, Politecnico di Torino, 10129 Torino, Italy.

International Journal of Environmental Research and Public Health
|August 26, 2022
PubMed
Summary

This study introduces an AI-powered, markerless motion analysis system for real-time gait assessment. This automated approach offers a low-cost, accurate solution for diagnosing motor impairments and enhancing sports performance.

Keywords:
artificial intelligenceautomated gait analysishuman biomechanicsmarkerlessmotion tracking

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Area of Science:

  • Biomechanics
  • Artificial Intelligence
  • Medical Technology

Background:

  • Human gait is influenced by neurological, orthopedic, and pathological factors, making gait analysis crucial for diagnostics and performance evaluation.
  • Current gait analysis technologies face challenges in balancing cost, accuracy, speed, and convenience.
  • There is a need for accessible, low-cost solutions to support individuals with motor impairments.

Purpose of the Study:

  • To develop a novel, automated approach for motion characterization using artificial intelligence.
  • To enable real-time, non-invasive, and markerless gait analysis.
  • To provide a cost-effective solution for improving the quality of life for individuals with motor impairments.

Main Methods:

  • An artificial intelligence-based system was developed for automated motion characterization.
  • The system performs real-time, markerless analysis of the gait cycle.
  • Gait metrics were compared between the proposed system and traditional motion tracking methods.

Main Results:

  • The novel automated procedure enables rapid diagnosis and reduces human error in gait analysis.
  • The AI-driven system demonstrated effectiveness in real-time gait analysis.
  • Comparison with existing systems validated the proposed methodology's accuracy.

Conclusions:

  • The proposed AI-powered, markerless gait analysis system offers a promising advancement in the field.
  • This technology has the potential to improve diagnosis, treatment assessment, and performance enhancement.
  • The system provides a low-cost, convenient, and accurate solution for diverse gait analysis applications.