SHORT-TERM IMPACTS OF MOBILE TOUCH-SCREEN DEVICE USE ON MUSCULOSKELETAL DISORDERS DURING COVID-19 PANDEMIC: RISK ASSESSMENT MODELLING AND VERIFICATION

• Ali Elghomati http://orcid.org/0000-0001-7488-1507
• Orhan Korhan http://orcid.org/0000-0002-9388-8605
• Boran Sekeroglu http://orcid.org/0000-0001-7284-1173
• Kagan Dogruyol http://orcid.org/0000-0001-5782-5802

DOI:

https://doi.org/10.7166/33-2-2598

Keywords:

association rule mining approach, machine learning, educational activities, mobile touch screen, musculoskeletal disorders

Abstract

The intensive and repetitive use of touch-screens may pose significant problems, such as ergonomic pain or musculoskeletal disorders. This research aims to study the effect of using mobile touch-screen devices on the human musculoskeletal system during the COVID-19 pandemic lockdown and to develop a model for classifying the effects of musculoskeletal stress (pain and discomfort) on the performance of educational activities. The Cornell musculoskeletal discomfort questionnaire was given to 544 participants (71% males and 29% females). An Association Rule Mining approach was applied to illustrate the correlation, and multiple machine-learning models – used to predict the impact of pain and discomfort on different body regions – were applied to determine risk levels that might interfere with the ability to perform daily activities. Most musculoskeletal disorders were reported in the neck region and lower back (64.33% and 55.33% respectively), followed by upper back (44.30%) and the right shoulder (38%). Analysis of association rules showed high positive correlation between the lower back and the neck (support = 43%, confidence = 77%). Additionally, it was found that the radial basis function network has the highest accuracy in prediction (84%). The results of the radial basis function model showed that interference in educational activities can be predicted by using pain indicators in body parts resulting from touch-screen device usage.