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Clinical-oriented Three-dimensional Gait Analysis Method for Evaluating Gait Disorder
Published on: March 4, 2018
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A perceptual map for gait symmetry quantification and pathology detection
Antoine Moevus1, Max Mignotte2, Jacques A de Guise3
1Département d'Informatique & Recherche Opérationnelle (DIRO), Faculté des Arts et des Sciences, Université de Montréal, Montréal, QC, H3C 3J7, Canada. a.moevus@gmail.com.
Biomedical Engineering Online
|October 30, 2015
Summary
This study introduces an affordable, marker-less gait analysis system using a depth sensor to visualize and quantify gait asymmetry. The system provides clinicians with a fast, perceptual tool for diagnosing various conditions and monitoring recovery.
Area of Science:
- Biomechanics
- Medical Imaging
- Clinical Diagnostics
Background:
- Gait is a complex process involving neurological, articular, and musculoskeletal systems.
- Gait analysis is crucial for diagnosing diverse conditions, including neurological, muscular, and orthopedic diseases.
- Current methods may lack ease of use or affordability for daily clinical application.
Purpose of the Study:
- To develop a novel, inexpensive, and user-friendly method for visualizing gait asymmetry.
- To enable quick clinical assessment of body parts exhibiting asymmetric movement during gait.
- To provide a perceptual display of gait characteristics for enhanced diagnostic capabilities.
Main Methods:
- Utilizing a consumer-grade depth sensor (Kinect) for marker-less motion capture.
- Applying multi-dimensional scaling with a temporally shift-invariant distance for visualization.
- Developing a quantifiable index to measure local and global gait asymmetry.
Main Results:
- The proposed index for gait asymmetry is statistically significant.
- The system offers an inexpensive, marker-less, and non-invasive approach to gait analysis.
- The developed tool is readable, flexible, and easy to set up for clinicians.
Conclusions:
- The system provides a perceptual color map for a quick overview of gait asymmetry.
- It can be valuable for monitoring disease progression and recovery post-surgery.
- The technology holds potential for diagnosing pathologies where gait asymmetry is a key symptom.
