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Abstract

Behavioral pattern is the characteristic ways a person acts and has been recognized as a cause of many home accidents (h-accd). This study reviewed the types and prevalence of injuries among women in domestic works and proposes a model using Artificial Neural Network (ANN) function to forecast the safety level of women in domestic duty. The study was conducted in some parts of Western Nigeria among 340 subjects (171 married and 169 unmarried) using questionnaire. SPSS was used for data analysis. The ANN function was developed in MATLAB 2015a using the subjects’ behavioral patterns and the model was used to predict safety in domestic duties (d-duties) among some women. ‘Cuts/laceration’ (40%) and ‘skin contact with hot substance’ (35.6%) were commonly reported. Carelessness (26.5%) and distraction (22.1%) were the main leading factors across the groups. Marital status and h-accd (Chi-square =4.323 and p= .038); ‘hours spent on domestic works’ and ‘the h-accd’ were both significant among other tested groups variables. With the developed ANN function, the results of the MSE was 0.33626 indicating that the function predicted the exact value. The result of the predicted h-accd (safety= -0.5445, hazards= 1.0228) in d-duties of the tested variables with the ANN function, showed a very low level of safety. The article concludes that the developed model is reliable and a recommended ergonomic tool useful in all homes, most especially where women perform most domestic works.

Author Biography

Adeyemi H.O. is a Senior Lecturer in Mechanical Engineering with research interest in Artificial Intelligence and Safety engineering.

Osifeko M.O. is a Lecturer in Computer Engineering. He is currently undergoing PhD work in the University of Pretoria.

Olanike O.A. is a Lecturer in Electrical and Electronic Engineering. She is currently undergoing her Ph.D. work.

Olatunbosun O.B., Adesina A.P. and Egbuobi U.C. are students in Mechanical Engineering department, with research interest in Artificial Intelligence and Safety Engineering.

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