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This work aims to develop a wearable system for classifying risky ankle postures linked to injuries.

June 14, 2026Materials Horizons0 citations

Toward intelligent wearables: engineering self-powered triboelectric nanofiber sensors for the classification of risky ankle postures

AAAsma AkterKing Fahd University of Petroleum and Minerals GRGokana Mohana RaniInha University MAMd Mehedi Hasan ApuKing Fahd University of Petroleum and Minerals

Key Points

This work aims to develop a wearable system for classifying risky ankle postures linked to injuries.
Engineered triboelectric nanofibers were integrated into a wearable system.
Machine learning algorithms were applied for analyzing ankle motion classifications.
Focus on classifying inversion and eversion motions to assess risk.
The system effectively classified risky ankle postures with high accuracy.
Results indicate significant potential for preventive healthcare applications in ankle injury management.

Abstract

This work presents a wearable system combining engineered nanofibers and machine learning for ankle injury classification, enabling classification of risky motions like inversion and eversion, which is useful for preventive healthcare.

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