Session: 07-08-01: Biomedical Devices, Sensors, and Actuators I

Paper Number: 164928

Prediction of Admissible Residual Stress ARS for Medical Prostheses Using Fatigue Criteria 

Medical lower limb prostheses, are exposed to repeated mechanical stresses from daily activities, such as, walking and running. Ensuring their longevity is crucial to prevent premature failure and increase patient comfort. In this study, a fatigue life prediction model originally developed for construction materials is adapted to medical prostheses by integrating the allowable residual stress into the design process. The methodology uses finite element analysis (FEA) and fatigue criteria, including Crossland, Sines and Dang-Van models, to identify critical fatigue areas and optimize residual stress distribution through surface treatments such as shot peening and nitriding. The Materials and Methods describes the selection of prosthetic materials, including titanium alloys, cobalt-chromium, carbon fiber composites, and PEEK, which are commonly used due to their high strength-to-weight ratio and biocompatibility. A finite element model (FEM) was developed to simulate cyclic loading conditions that correspond to real-world use and allow the identification of stress concentration zones. The study integrates techniques to deal with residual stresses in order to improve fatigue resistance and mechanical stability. To evaluate the accuracy of the numerical model, validation methods such as fatigue testing, residual stress measurement by X-ray diffraction and digital image correlation were used. In addition, mechanical tests were performed under different environmental conditions to evaluate the effects of temperature and humidity on the longevity of the prosthesis. The results and discussion show that the finite element simulations reveal critical stress areas in prosthetic sockets, knee joints and foot modules. Surface treatments such as shot peening improved fatigue life by approximately 30%, while nitriding increased surface hardness, reduced wear and increased longevity. The effects of stress relaxation under cyclic loading were also investigated and confirmed the need for post-treatment stabilization procedures. The study found that the most vulnerable areas were those subjected to multiaxial load combinations, particularly at the interfaces between mechanical components and biological tissue. Experimental validation showed a strong correlation between the simulated and measured residual stress distributions, confirming the predictive accuracy of the proposed model. In addition, comparative studies on untreated and treated prosthetic materials provided insights into the failure mechanisms and the benefits of a controlled residual stress distribution. The conclusion and future work emphasizes the importance of integrating residual stress prediction into prosthetic design for improved durability. Future research will focus on patient-specific fatigue modeling, taking into account variations in body weight and activity level, and exploring biomechanical interactions between prosthetic components and human tissue. In addition, novel surface treatments and advanced material innovations tailored to individual patient needs will be investigated to further improve fatigue resistance and reliability. The potential application of adaptive load control mechanisms, such as smart materials that self-adapt under changing loads, will also be explored. This study bridges the gap between numerical fatigue prediction models and real-world prosthetic applications to ensure long-term performance, improved patient mobility and higher safety standards in the development of medical implants.

Presenting Author: Jinan CHARAFEDDINE Léonard de Vinci Pôle Universitaire, Research Center

Presenting Author Biography: Jinan Charafeddine received a Master’s degree in Biomedical Engineering and a diploma in Instrumentation and Industrial Computing from the Lebanese University, Beirut, Lebanon, in 2013. She completed a Ph.D. in Motion Science and Control of Mechatronic Systems at Paris-Saclay University, Orsay, France, in 2021. From November 2020 to August 2023, she served as a Lecturer in the Department of Mechatronics and Digital Systems of Engineering at Université Paris-Saclay and the Engineering School “Institut des Sciences et Techniques des Yvelines” (ISTY) and as a Researcher at the Laboratoire d'Ingénierie des Systèmes de Versailles (LISV). Since September 2023, she has been a Professor Researcher at Devinci Higher Education, Paris La Défense, specializing in Biomechanics and Artificial Intelligence for Medical Computer Vision

Authors:

Radouane Akrache Laboratoire d'Ingénierie des Systèmes de Versailles (LISV) - UVSQ
Jinan CHARAFEDDINE Léonard de Vinci Pôle Universitaire, Research Center
Taha Houda Prince Mohammad Bin Fahd University
Wafaa M. R. Shakir Al-Furat Al-Awsat Technical University
Halima Ghorbel LATMOS
Yasin Dhaher UT Southwestern Medical Center