Development of neurobehavioral deterioration risk prediction model for welder: a proposed study

• Main Authors: Paiman, Nuur Azreen, Hariri, Azian, Masood, Ibrahim, Noor, Arma, Yusof, Khairul Hazdi, Abdullah, Samsuri, Idris, Ahmad Fu’ad, Mohd Afandi, Mohd Azizi, Asmuin, Nor Zelawati, Leman, Abdul Mutalib
• Format: Article
• Language: English
• Published: Penerbit UTHM 2018
• Subjects: T Technology (General); TK Electrical engineering. Electronics Nuclear engineering
• Online Access: http://eprints.uthm.edu.my/5960/1/AJ%202018%20%28673%29.pdf; http://eprints.uthm.edu.my/5960/; https://doi.org/10.30880/ijie.2018.10.05.018

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.