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Abstract

Ergonomics is the study of designing and arranging a workspace or product to optimize the “fit” between people and their work, ensuring safety, comfort, and efficiency. The scientific literature indicates that ergonomic perspectives on the workplace are connected to the anthropometrics of societies. This study primarily aims to create a model that integrates multiple predictive variables to estimate the target variable. Multiple linear regression analysis is used to identify how different anthropometric dimensions predict postural ergonomics during prolonged sitting. Based on the regression models’ results, the predicted can be calculated using user anthropometry and existing chair dimensions. Furthermore, the primary role of elbow height as the strongest predictor is intuitively sound in ergonomics, as the armrest should align with the user’s natural elbow resting position. Moreover, a strong and reliable tool for calculating optimal seat height based on anthropometry and existing chair dimensions is observed. The regression model also reveals that the optimal backrest angle can be calculated based on multiple user anthropometries. The study demonstrates that the angle of the backrest relative to various anthropometric characteristics functions as a reliable predictor. This means that a comfortable or key predictor posture angle depends on several factors, such as how wide a user’s hips are and how high they sit. This result differs from that of the previous correlation study. Finally, we conclude that the data continually show that anthropometric measures alone are insufficient to understand ergonomics. To create seating solutions that can be tailored to a broad range of users and improve posture and productivity, a multivariable approach is needed that includes clear, data-driven standards

References

[1] Dul J, Weerdmeester B. Ergonomics for beginners. second ed. Boca Raton, FL: CRC Press; 2001. p. 1—160.

[2] Hasanain B. The role of ergonomic and human factors in sustainable manufacturing: A review. Machines 2024;12:159. https://doi.org/10.3390/machines12030159.

[3] Koirala R, Nepal A. Literature Review on Ergonomics, Ergonomics Practices, and Employee Performance. Quest J. Manag. Soc. Sci 2022;4:273. https://doi.org/10.3126/ qjmss.v4i2.50322.

[4] Mikos V, Yen SC, Tay A, Heng CH, Chung CLH, Liew SHX, et al. Regression analysis of gait parameters and mobility measures in a healthy cohort for subject-specific normative values. PLoS One 2018;13:e0199215. https://doi.org/10.1371/ journal.pone.0199215.

[5] Agha SR, Alnahhal MJ. Neural network and multiple linear regression to predict school children dimensions for ergonomic school furniture design. Appl Ergon 2012;43:979. https://doi.org/10.1016/j.apergo.2012.01.007.

[6] Openshaw S, Taylor E. Ergonomics and design: a reference guide. first ed. Muscatine, IA/Upper Darby, PA: Allsteel Inc./DIANE Publishing Co.; 2006. p. 1—118.

[7] Aro OE. Predictive analytics in financial management: Enhancing decision-making and risk management. Int. J. Res. Publ. Rev 2024;5:2181. https://doi.org/10.55248/geng pi.5.1024.2819.

[8] Zadem A, Chettouh S. The role of ergonomics and workplace design in enhancing well-being at work. 4th Int. Conf. Appl. Ergon. Dev. Ctries 2024;18(3):42—56.

[9] Santos W, Rojas C, Isidoro R, Lorente A, Dias A, Mariscal G, et al. Efficacy of ergonomic interventions on workrelated musculoskeletal pain: A systematic review and meta-analysis. J Clin Med 2025;14:3034. https://doi.org/ 10.3390/jcm14093034.

[10] Mottaghi Z, Halvani G, Jambarsang S, Mehrparvar AH. Effect of ergonomic intervention on cognitive function of office workers. Indian J Occup Environ Med 2024;28:267. https://doi.org/10.4103/ijoem.ijoem_213_22.

[11] Sonmez € K, Yilmaz S, Karabay D. Effects of psychosocial and ergonomic risk perceptions in the hospital environment on employee health, job performance, and absenteeism. Healthcare 2025;13:1000. https://doi.org/10.3390/healthcare 13091000.

[12] Zanwar DR, Zanwar HD, Shukla HM, Deshpande AA. Prediction of anthropometric dimensions using multiple linear regression and artificial neural network models. J. Inst. Eng. (India) Ser. C 2023;104:307. https://doi.org/ 10.1007/s40032-022-00904-x.

[13] Montgomery DC, Runger GC. Applied statistics and probability for engineers. fourth ed. Hoboken, NJ: John Wiley & Sons, Inc.; 2006. p. 1—768.

[14] Norusis MJ. SPSS inc., SPSS advanced statistics User's guide. first ed. Chicago, IL: SPSS Inc.; 1990. p. 1—285.

[15] Gogtay NJ, Thatte UM. Principles of correlation analysis. J Assoc Phys India 2017;65:78. https://pubmed.ncbi.nlm.nih. gov/28462548/.

[16] Schober P, Boer C, Schwarte LA. Correlation Coefficients: Appropriate Use and Interpretation. Anesth Analg 2018;126: 1763—8. https://doi.org/10.1213/ane.0000000000002864.

[17] Castellucci H, Viviani C, Arezes P, Molenbroek JFM, Martínez M, Aparici V, et al. Applied anthropometry for common industrial settings design: Working and ideal manual handling heights. Int J Ind Ergon 2020;78:102963. https://doi.org/10.1016/j.ergon.2020.102963.

[18] Sydor M, Hitka M. Chair size design based on user height. Biomimetics 2023 Jan 31;8(1):57. https://doi.org/10.3390/ biomimetics8010057.

[19] Mathiassen SE, Winkel J, Ha€gg GM. Normalization of surface EMG amplitude from the upper trapezius muscle in ergonomic studies ― A review. J Electromyogr Kinesiol 1995 Dec 1;5(4):197—226. https://doi.org/10.1016/1050- 6411(94)00014-x.

[20] International Organization for Standardization. ISO 9241-5: 2024: ergonomics of human-system interaction―Part 5: workstation layout and postural requirements. ISO; 2024. https://www.iso.org/standard/86222.html.

[21] BIFMA. ANSI/BIFMA X5.1-2017: General-purpose office chairs―Tests. Business and Institutional Furniture Manufacturers Association. https://www.bifma.org; 2021.

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