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Inverse identification of elastic modulus of dental implant-bone interfacial tissue using neural network and FEA model

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Abstract:

This study introduces an inverse procedure for identifying the elastic modulus (Young's modulus) of interfacial tissue around a dental implant using neural network (NN) and finite element analysis (FEA). An NN model is first trained using displacement responses obtained using FEA models with given interface properties. It is then used to identify the interface elastic modulus by feeding in measured displacements of a dental implant-bone structure whose interface elastic modulus is unknown. The results indicate that the identified elastic modulus is sufficiently close to the original one. The developed NN-FEA inverse procedure is concluded to be robust and efficient. It offers a new perspective and means for the study of the living-bone properties around dental implants, as it can be easily made in real-time.

Keywords: Young's modulus; dental implant; finite element analysis; interfacial tissue; inverse analysis; neural network

Document Type: Research Article

DOI: http://dx.doi.org/10.1080/17415970903063151

Affiliations: 1: Department of Restorative Dentistry, Faculty of Stomatology, Xi'an Jiao Tong University, Xi'an, P.R. China, 710004 2: Department of Restorative Dentistry, Faculty of Dentistry, National University of Singapore, 119074 Singapore 3: Department of Mechanical Engineering, Centre for Advanced Computations in Engineering Science (ACES), National University of Singapore, 119260 Singapore 4: Department of Mechanical Engineering, Centre for Advanced Computations in Engineering Science (ACES), National University of Singapore, 119260 Singapore,The Singapore-MIT Alliance (SMA), 117576 Singapore 5: Clinical Research Center, The Second Affiliated Hospital, Zhejiang University, 310000 Hangzhou, P.R. China

Publication date: December 1, 2009

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