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Updated: Sep 4, 2025

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

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

Published on: March 4, 2018

Data augmentation for depression detection using skeleton-based gait information.

Jingjing Yang¹, Haifeng Lu¹, Chengming Li²

¹School of information Science and Engineering, Lanzhou University, Lanzhou, China.

Medical & Biological Engineering & Computing

|July 13, 2022

Summary

This summary is machine-generated.

This study introduces skeleton data augmentation to improve depression screening using gait analysis. Effective augmentation techniques significantly boost depression detection accuracy, offering a promising non-contact early detection method.

Keywords:

Data augmentation Depression recognition Gait Skeleton

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Area of Science:

Biomedical Engineering
Computer Science
Psychiatry

Background:

Depression incidence is rising globally, posing challenges for large-scale screening.
Gait analysis offers a non-contact, low-cost method for early depression detection.
Current gait analysis for depression lacks sufficient effective sample data.

Purpose of the Study:

To propose and evaluate skeleton data augmentation techniques for depression risk assessment.
To enhance the effectiveness of gait analysis in early depression screening.
To identify optimal augmentation strategies for human skeleton data.

Main Methods:

Developed five skeleton data augmentation techniques.
Applied augmentation to depression and emotion datasets.
Classified augmentation methods into non-noise and noise types based on mutual information and classification accuracy.

Main Results:

Augmented datasets retaining raw skeleton data properties improved detection model performance.
Rotation augmentation achieved 92.15% depression detection accuracy.
Channel mask augmentation achieved 91.34% depression detection accuracy.

Conclusions:

Skeleton data augmentation is effective for improving depression detection accuracy.
Specific augmentation strategies like rotation and channel masking are highly effective.
Enhanced gait analysis using augmented data shows promise for non-contact, early depression screening.