A Hybrid AI-Biomechanics Digital Twin to Predict Skin Damage in Prosthetic Sockets

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SPIRE - Sciences Po Institutional REpository
Published
2026-02-05
Primary Topic
Advanced Sensor and Energy Harvesting Materials
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article
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article

A Hybrid AI-Biomechanics Digital Twin to Predict Skin Damage in Prosthetic Sockets

Taha Houda, Halima Ghorbel, Wafaa M. R. Shakir, Radouane Akrache et al.
SPIRE - Sciences Po Institutional REpository
Advanced Sensor and Energy Harvesting Materials
article

A Hybrid AI-Biomechanics Digital Twin to Predict Skin Damage in Prosthetic Sockets

Taha Houda, Halima Ghorbel, Wafaa M. R. Shakir, Radouane Akrache, Yasin Dhaher, Jinan Charafeddine
article en

Abstract

No abstract available for this paper.
SPIRE - Sciences Po Institutional REpository
Prince Mohammad bin Fahd University (SA), Atmosphere Systems and Services (FR), Pôle Léonard de Vinci (FR), Vinci (France) (FR), Ecole Supérieure d'Ingénieurs Léonard de Vinci (FR), Laboratoire atmosphères, milieux, observations spatiales (FR), Al-Furat Al-Awsat Technical University (IQ), Laboratoire d'Ingénierie des Systèmes de Versailles (FR), The University of Texas Southwestern Medical Center (US)
Openalex Percentile: Top 22%
Advanced Sensor and Energy Harvesting Materials
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