Development of machine learning models for gait-based classification of incomplete spinal cord injuries and cauda equina syndrome

Development of machine learning models for gait-based classification of incomplete spinal cord injuries and cauda equina syndrome

Abstract Incomplete tetraplegia, incomplete paraplegia, and cauda equina syndrome are major neurological disorders that significantly reduce patients’ quality of life, primarily due to impaired motor function and gait instability. Although conventional neurological assessments and imaging techniques...

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Bibliographic Details
Main Authors: Seul Gi Park, Sae Byeol Mun, Young Jae Kim, Kwang Gi Kim
Format: Article
Language:English
Published: Nature Portfolio 2025-06-01
Series:Scientific Reports
Subjects:
Cauda equina syndrome
Gait analysis
Incomplete paraplegia
Incomplete tetraplegia
Machine learning
Motion capture
Online Access:https://doi.org/10.1038/s41598-025-04065-6
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https://doi.org/10.1038/s41598-025-04065-6

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