Development of Neurobehavioral Deterioration Risk Prediction Model for Welder: A Proposed Study

  • Nuur Azreen Paiman Centre for Energy and Industrial Environment Studies (CEIES), Faculty of Mechanical and Manufacturing , Universiti Tun Hussein Onn Malaysia, Parit Raja, Batu Pahat, Johor, 86400
  • Azian Hariri Centre for Energy and Industrial Environment Studies (CEIES), Faculty of Mechanical and Manufacturing , Universiti Tun Hussein Onn Malaysia, Parit Raja, Batu Pahat, Johor, 86400
  • Ibrahim Masood Faculty of Mechanical and Manufacturing, Universiti Tun Hussein Onn Malaysia, Parit Raja, Batu Pahat, Johor, 86400
  • Arma Noor Universiti Putra Malaysia Health Centre, Serdang, Selangor, 43400
  • Khairul Hazdi Yusof Department of Community Health, Universiti Kebangsaan Malaysia Medical Centre, Cheras, Kuala Lumpur, 56000,
  • Samsuri Abdullah School of Ocean Engineering, Universiti Malaysia Terengganu, Kuala Terengganu, Terengganu, 21030
  • Ahmad Fu'ad Idris Centre for Energy and Industrial Environment Studies (CEIES), Faculty of Mechanical and Manufacturing , Universiti Tun Hussein Onn Malaysia, Parit Raja, Batu Pahat, Johor, 86400
  • Mohd Azizi Mohd Afandi Centre for Energy and Industrial Environment Studies (CEIES), Faculty of Mechanical and Manufacturing , Universiti Tun Hussein Onn Malaysia, Parit Raja, Batu Pahat, Johor, 86400
  • Nor Zelawati Asmuin Centre for Energy and Industrial Environment Studies (CEIES), Faculty of Mechanical and Manufacturing , Universiti Tun Hussein Onn Malaysia, Parit Raja, Batu Pahat, Johor, 86400
  • Abdul Mutalib Leman Faculty of Engineering Technology, Universiti Tun Hussein Onn Malaysia, Parit Raja, Batu Pahat, Johor, 86400
Keywords: Artificial Neural Network, Biomarker, Neurobehavioral, Prediction Model, Welding Fume Exposure

Abstract

Risk prediction model estimate the risk of emerging upcoming outcomes for individual based on several
underlying characteristics. In welding process, welders have the high risk to expose with the toxicant element which
can harm the neuropsychological of a welder. This proposed study will develop a prediction model on
neurobehavioral deterioration risk of welders. In order to get the intensity of heavy metal exposure of the welders,
airborne personal monitoring and toenail biomarker test will be carried out. Meanwhile, for the neurotoxicity
assessment, the workers will undergo the neurobehavioral core test battery and questionnaire survey to identify the
neurobehavioral score level. Detail statistical analysis between both assessment results will be carried out for
development of prediction model based on artificial neural network. After validation test, the developed artificial
neural network prediction model will be applied to another metal base industry for verification purpose. Length of
abstract can be proportional to the length of the article. Through this study, it is expected neurobehavioral risk
prediction model on detection on early symptoms of neurobehavioral deterioration will be developed This study
contribute to better understanding on the effects of heavy metals exposure, especially to central nervous systems
among welders
Published
2018-11-19
How to Cite
Paiman, N. A., Hariri, A., Masood, I., Noor, A., Yusof, K. H., Abdullah, S., Idris, A. F., Mohd Afandi, M. A., Asmuin, N. Z., & Leman, A. M. (2018). Development of Neurobehavioral Deterioration Risk Prediction Model for Welder: A Proposed Study. International Journal of Integrated Engineering, 10(5). Retrieved from https://publisher.uthm.edu.my/ojs/index.php/ijie/article/view/3040
Section
Special Issue 2018: Mechanical Engineering