IRMA-International.org: Creator of Knowledge
Information Resources Management Association
Advancing the Concepts & Practices of Information Resources Management in Modern Organizations

Computer Aided Modeling and Finite Element Analysis of Human Elbow

Computer Aided Modeling and Finite Element Analysis of Human Elbow
View Sample PDF
Author(s): Arpan Gupta (Indian Institute of Technology Mandi, India)and O.P. Singh (Indian Institute of Technology Mandi, India)
Copyright: 2017
Pages: 9
Source title: Medical Imaging: Concepts, Methodologies, Tools, and Applications
Source Author(s)/Editor(s): Information Resources Management Association (USA)
DOI: 10.4018/978-1-5225-0571-6.ch042

Purchase

View Computer Aided Modeling and Finite Element Analysis of Human Elbow on the publisher's website for pricing and purchasing information.

Abstract

Finite element modeling (FEM) plays a significant role in the design of various devices in the engineering field of automotive, aerospace, defense etc. In the recent past, FEM is assisting engineers and healthcare professional in analyzing and designing various medical devices with advanced functionality. Computer aided engineering can predict failure circumstances, which can be avoided for the health and well-being of people. In this research work, computer aided engineering analysis of human elbow is presented beginning with modeling of human elbow from medical image data, and predicting the stresses in elbow during carrying heavy loads. The analysis is performed by using finite element method. The results predict the stress level and displacement in the human bone during heavy weight lifting. Thus, it can be used to predict the safe load that a particular person can carry without bone injury. The present analysis focused on a particular model of bone for a particular individual. However, safe load can be determined for various age groups by generating more detailed model including tendons, ligaments and by using patient specific material properties.

Related Content

Sharon L. Burton. © 2024. 25 pages.
Laura Ann Jones, Ian McAndrew. © 2024. 24 pages.
Olayinka Creighton-Randall. © 2024. 14 pages.
Stacey L. Morin. © 2024. 11 pages.
N. Nagashri, L. Archana, Ramya Raghavan. © 2024. 22 pages.
Esther Gani, Foluso Ayeni, Victor Mbarika, Abdullahi I. Musa, Oneurine Ngwa. © 2024. 25 pages.
Sia Gholami, Marwan Omar. © 2024. 18 pages.
Body Bottom