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Machine Learning Feature Extraction from High-Dimensional Gait Kinematics

Affective Science

Gait Analysis & Emotional State Inference

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Affective Science › Gait Analysis & Emotional State Inference

Machine Learning Feature Extraction from High-Dimensional Gait Kinematics

This research applies deep learning architectures and dimensionality reduction techniques to identify latent features within complex multivariate gait data that predict emotional state classification. The contribution establishes data-driven feature hierarchies that illuminate previously unknown emotional-motor relationships.

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📚 Academic: Thesis & PPT assistance included🧪 Tech: Master the protocols hands-on📝 Research > 3 months: Publication co-authorship in a Scopus-indexed journal

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