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Publication Type : Journal Article
Publisher : Journal of Medical Imaging and Health Informatics, American Scientific Publishers
Source : Journal of Medical Imaging and Health Informatics, American Scientific Publishers, Volume 10 (2020)
Keywords : IRONING WORK; MUSCULOSKELETAL DISORDER; REPETITIVE WORK; SHOULDER PAIN; sEMG
Campus : Coimbatore
School : School of Engineering
Department : Mechanical Engineering
Verified : Yes
Year : 2020
This study focused on the assessment of muscle activities related to shoulder pain among the occupational ironing workers. The activity of the shoulder muscle response was observed as maximum during the ironing activity. The fatigue property was identified using the surface electromyography (sEMG). The structural spots were chosen on the basis of statistical survey and direct observation conducted before the investigation. The muscle activities of trapezius descendens of the right hand, deltoideus medius of the right hand, deltoideus anterior of the right hand, trapezius descendens of the left hand and deltoideus medius of the left hand was recorded by using the sEMG and the muscle activities were investigated for workers involved in ironing of clothes in laundry shops. The investigation reports were collected and processed. The study reports that the musculoskeletal disorder in the shoulder portion is due to the age, repetitive work, working time and iron box weight. The maximum response was observed in the deltoideus medius of the right hand. The age factor found to be the most prevailing symptom among the ironing workers. The aged persons were found to be at high risk due to repetitive task for a prolonged time period of ironing and also the table height influences fatigue. In order to overcome this problem, the workers were suggested to take adequate rest brakes during the ironing process and adjust the table height.
Cite this Research Publication : T. Mohanraj, M, A., K., V. K. C., and Vijay, M., “Evaluation of Shoulder Pain Among the Workers Involved in Ironing Process Using Surface Electromyography”, Journal of Medical Imaging and Health Informatics, vol. 10, 1 vol., 2020.