Development of statistical models for predicting muscle and mental activities during repetitive precision tasks

• Main Authors: Zadry, H.R., Md Dawal, Siti Zawiah, Taha, Z.
• Format: Article
• Published: Taylor & Francis 2016
• Subjects: T Technology (General); TJ Mechanical engineering and machinery
• Online Access: http://eprints.um.edu.my/18730/; https://doi.org/10.1080/10803548.2016.1150094

This study was conducted to develop muscle and mental activities on repetitive precision tasks. A laboratory experiment was used to address the objectives. Surface electromyography was used to measure muscle activities from eight upper limb muscles, while electroencephalography recorded mental activities from six channels. Fourteen university students participated in the study. The results show that muscle and mental activities increase for all tasks, indicating the occurrence of muscle and mental fatigue. A linear relationship between muscle activity, mental activity and time was found while subjects were performing the task. Thus, models were developed using those variables. The models were found valid after validation using other students’ and workers’ data. Findings from this study can contribute as a reference for future studies investigating muscle and mental activity and can be applied in industry as guidelines to manage muscle and mental fatigue, especially to manage job schedules and rotation.