Deep Temporal Clustering of Pathological Gait Patterns in Post-Stroke Patients Using Joint Angle Trajectories: A Cross-Sectional Study

Deep Temporal Clustering of Pathological Gait Patterns in Post-Stroke Patients Using Joint Angle Trajectories: A Cross-Sectional Study

Rehabilitation of gait function in post-stroke hemiplegic patients is critical for improving mobility and quality of life, requiring a comprehensive understanding of individual gait patterns. Previous studies on gait analysis using unsupervised clustering often involve manual feature extraction, whi...

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Bibliographic Details
Main Authors: Gyeongmin Kim, Hyungtai Kim, Yun-Hee Kim, Seung-Jong Kim, Mun-Taek Choi
Format: Article
Language:English
Published: MDPI AG 2025-01-01
Series:Bioengineering
Subjects:
post-stroke
hemiplegia
gait patterns
kinematic data
time-series data
deep clustering
Online Access:https://www.mdpi.com/2306-5354/12/1/55
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