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Self-Powered Multifunctional Instrumented Knee Implant

[+] Author Affiliations
Mohsen Safaei, Steven R. Anton

Tennessee Technological University, Cookeville, TN

Paper No. SMASIS2018-8078, pp. V002T06A008; 11 pages
  • ASME 2018 Conference on Smart Materials, Adaptive Structures and Intelligent Systems
  • Volume 2: Mechanics and Behavior of Active Materials; Structural Health Monitoring; Bioinspired Smart Materials and Systems; Energy Harvesting; Emerging Technologies
  • San Antonio, Texas, USA, September 10–12, 2018
  • Conference Sponsors: Aerospace Division
  • ISBN: 978-0-7918-5195-1
  • Copyright © 2018 by ASME


Computational modeling, instrumented linkages, optical technologies, MRI, and radiographic techniques have been widely used to study knee motion after total knee replacement (TKR) surgery. Information provided by these methods has helped designers to develop implants with better clinical performance and surgeons to obtain an improved understanding of the stability and mobility of the joint. Correspondingly, overall patient satisfaction with respect to the reduction in pain and recovery of normal functioning of the joint has been improving. However, about 20% of patients are still not fully satisfied with their surgical outcomes. The main obstacle in the current state-of-the-art is that a comprehensive post-operative understanding of knee balance is still unavailable, mostly due to a lack of in vivo data collected from the joint after surgery. This work presents an attempt to develop a self-powered instrumented knee implant for in vivo data acquisition. The knee sensory system in this study utilizes several embedded piezoelectric transducers in the tibial bearing of the knee replacement in order to provide sensing and energy harvesting capabilities. Through a series of analytical modeling, finite element simulation, and experimental testing, the performance of the suggested system is evaluated and a dimensionally optimized design of an instrumented TKR is achieved. More specifically, a comprehensive platform is established in order to combine the knowledge of embedded piezoelectric sensors and energy harvesters, musculoskeletal modeling of the knee joint, multiphysics finite element modeling, additive manufacturing techniques, image processing, and experimental knee loading simulation in order to achieve the experimentally validated and optimized instrumented knee implant design. The cumulative work presented in this article encompasses three main studies performed on the sensing performance of the proposed design: first, preliminary parametric studies of the effect of local dimensional and material parameters on the electromechanical behavior of the embedded sensory system; second, investigation of the ability to sense total force and center of pressure location; and third, evaluation of an enhanced system with the ability to sense compartmental forces and contact locations. Additionally, the energy harvesting capacity of the system is investigated to ensure the achievement of a fully self-powered sensory system. Results obtained from the experimental analysis of the system demonstrate the successful sensing and energy harvesting performance of the designs achieved in this study.

Copyright © 2018 by ASME



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