Utilization of depth camera to ease posture-risk assessment of related sitting work

Widodo, Romy Budhi, Chandra, Kevin Christian, Oktiarso, Teguh, Chamidy, Totok and Suhartono, Suhartono (2023) Utilization of depth camera to ease posture-risk assessment of related sitting work. Journal of Engineering Science and Technology Review, 16 (3). pp. 100-108. ISSN 1791-2377

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Abstract

Sitting work posture is often used in office work. Work position failures when sitting can cause Musculoskeletal Disorders. Therefore, ergonomists are necessary for the workplace to assist workers' posture. However, these needs cannot be met due to the limited number of ergonomists and costs. So a practical and inexpensive semi-automatic application is needed. One method for assessing upper body work posture is RULA. This study aims to develop a posture assessment application for sitting work and suggest improvement. In addition, the effect of changes in room brightness, the variability of chair height, and types of office-work tasks were explored in this study to determine the accuracy level of the depth camera to measure the worker's posture. Research design uses empirical research with independent variables: room illuminance, chair height, and four types of office-work tasks. The two levels of room illuminance are 32 lux and 60 lux; the seat height consists of three levels, i.e., 40, 45, and 50cm, while four types of tasks include writing, typing, writing with a cheat sheet, and typing with a cheat sheet beside the Subject. The experiment tests the difference between the application's RULA estimation results and the ergonomist's RULA value. The experiment results showed that the proposed application successfully assessed RULA with the same results as the calculations by the ergonomist. This study makes posture assessment easier for sitting work and provides suggestions for posture improvement. In addition, automation of posture assessment using a depth camera helps provide evaluations and recommendations for improving posture while working sitting.

Item Type:	Journal Article
Keywords:	RULA; posture assessment; Kinect V2
Subjects:	08 INFORMATION AND COMPUTING SCIENCES > 0899 Other Information and Computing Sciences > 089999 Information and Computing Sciences not elsewhere classified
Divisions:	Faculty of Technology > Department of Informatics Engineering
Depositing User:	Totok Chamidy
Date Deposited:	21 Sep 2023 13:57

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