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All Journal Indonesian Journal of Electrical Engineering and Computer Science
Sami Ur Rahman, Jawwad
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Predictive modelling of osteoporosis and effect of BMI on the risk of fracture in femur bone using COMSOL Multiphysics: a computational modelling approach Kamal, Aleena; Kamal, Minahil; Fatima, Mashal; Hussain, Syed Muddusir; Sami Ur Rahman, Jawwad; Selvaperumal, Sathish Kumar
Indonesian Journal of Electrical Engineering and Computer Science Vol 39, No 1: July 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v39.i1.pp89-100

Abstract

This study explores the intricate relationship between osteoporosis, body mass index (BMI), and the risk of femur fractures using computational modeling. Osteoporosis is a silent metabolic disorder that depletes bone density and structure, significantly increasing the risk of fractures, particularly in weight-bearing bones such as the femur. To analyze the impact of mechanical stress on osteoporotic bones, COMSOL Multiphysics was utilized to simulate stress distribution in a femur under varying BMI conditions, providing valuable insights into how BMI influences bone health and fracture risk. A three-dimensional (3D) femur model was designed using computer-aided design (CAD) software, with specific material properties assigned for both healthy and osteoporotic bones. Finite element analysis was conducted by applying different load conditions, representing body weight, on the femur head. The results highlighted stress distribution and deformation patterns, identifying regions most prone to fracture. The findings demonstrate that while higher BMI typically correlates with increased bone density, it also leads to greater deformation in osteoporotic bones under stress, emphasizing the complex interplay between BMI and bone strength. These insights underscore BMI’s critical role in fracture risk management. Future research should incorporate advanced fracture mechanics models and clinical data to enhance predictive accuracy and develop targeted strategies for fracture prevention in osteoporotic patients.
Integrated approach of brain segmentation using neuro fuzzy k-means Sami Ur Rahman, Jawwad; Kumar Selvaperumal, Sathish
Indonesian Journal of Electrical Engineering and Computer Science Vol 29, No 1: January 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v29.i1.pp270-276

Abstract

A proposed method using neuro-fuzzy k-means for the segmentation process of brain has been developed successfully, simulated and assessed. The proposed method has been assessed by using clinical brain images of magnetic resonance imaging (MRI) technology, to segment the three main tissues of the brain. The proposed system is able to segment the three important regions of the brain, which are white matter, grey matter and cerebrospinal fluid (CSF) more accurately, as compared to the benchmarked algorithms. Furthermore, the developed method’s misclassification rate (MR) has been significantly minimized by 88%, 27%, 88%; 82%, 71%, 84%; and 82%, 29%, 83%, as compared to k-means, fuzzy logic, and radial basis function (RBF) for white matter, grey matter and CSF, respectively. Also, from the visual interpretation, it is observed that the brain’s edges are well preserved and the tissues are clearly segmented. From these measures, the proposed integrated approach is shown to be accurate in segmenting the MRI brain tissue with reduced misclassified pixels.
Co-Authors Fatima, Mashal Hussain, Syed Muddusir Kamal, Aleena Kamal, Minahil Kumar Selvaperumal, Sathish Selvaperumal, Sathish Kumar