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Showing 4 results for Sammak Amani
Conceptual Design of An Ergonomic Desk Converter Using Anthropometric Data of Iranian Community
Arezoo Sammak Amani, Mohammad Amin Mououdi, Morteza Mahdavi, Fariba Ghaempanah,
Volume 9, Issue 3 (Iranian Journal of Ergonomics 2021)
Abstract
Background and Objectives: For many employees, students and “Behind the desk jobs”, most of the daily work is done while sitting on a chair and behind a desk. This happens while many studies are associating long-term sedentary posture with musculoskeletal and cardiovascular diseases, etc. The aim of the present research is to design a tool that helps to change the working posture of people who work at sedentary workstations from sitting to stand-sit posture.
Methods: The measurements needed to design a desk converter were extracted from the existing anthropometric data of the Iranian community between the ages of 6-19 and 20-60 for both sexes, using 4 anthropometric parameters of elbow (to floor) height sitting, eye height sitting, elbow height standing and eye height standing. These values were used to obtain the difference between the required work surface of the hand while sitting and standing (keyboard position) and the difference of the required work surface of the eye while sitting and standing (display position). Due to the adjustability of this tool, 5th percentile of women and 95th percentile of men were used to achieve the required range of changes.
Results: The desk converter constitutes two parts, 1. Top surface (meant for monitor) and 2. the keyboard tray. The difference in the height of these two surfaces was calculated 12cm. The maximum height of the desk converter (adjustable range) for both age groups was 68 cm due to changes in sitting and standing elbow height. The width and depth of the desk are set at 90 by 50 cm, and the keyboard and mouse surface, with a width equal to the desk’s and a depth of 20 cm, creates sufficient and comfortable space for users.
Conclusion: It is envisioned that by using this tool and changing the posture of individuals from an entirely sitting posture to standing and sitting alternation, a contribution to the reduction of musculoskeletal, cardiovascular, diabetes and cancer problems can be made.

Evaluation of Usability and Discomfort of Safety Footwear in Different Industries of Mazandaran Province
Morteza Mahdavi, Arezo Sammak Amani, Mohammad Amin Mououdi, Hadi Asghari,
Volume 10, Issue 2 (Iranian Journal of Ergonomics 2022)
Abstract
Objectives: Providing safety for human resources in the industry is very important. Safety shoes are one of the most common PPEs that protect the foot against potential hazards. This study aimed to evaluate the discomfort and usability of safety shoes in different industries of Mazandaran province to find gaps in the quality of design and improve the design of safety shoes.
Methods: This was a cross-sectional study and was conducted in 2021.This study included employees of 11 different industrial companies that used seven safety shoe brands. They answered two researcher-made questionnaires, LPD (discomfort and general satisfaction) and SFUQ (usability). Data analysis was performed with Spearman rank correlation coefficient while Pearson correlation coefficient, and ANOVA test were also performed.
Results: In total, 226 men with a mean age of 36.33 ± 7.4 years were included in this study. The participants reported the lowest usability for the brand G (3.3 and 3.99), and the least discomfort and the most usability index with the brand A (1.2 and 5.35). Overall, the highest satisfaction was reported for brand A and the lowest satisfaction to brand G.
Conclusion: The findings of this study showed that the main problem in comfort and usability is probably related to shoe molds because the manufacturers of safety shoes import molds from abroad that do not fit the anthropometric characteristics of Iranian users’ feet.

Evaluation of Comfort, Usability and Posture of an Ergonomic Sit-stand Desk Converter Developed Based on Anthropometric Data from an Iranian Community
Mohammad Amin Mououdi, Arezoo Sammak Amani, Mohammad Taghipour,
Volume 11, Issue 2 (Iranian Journal of Ergonomics 2023)
Abstract
Objectives: Nowadays, workers are less mobile and more sedentary due to the use of modern technologies in the workplace, and the complications resulting from static work and fixed posture have caused numerous disorders, including musculoskeletal disorders. This study was conducted to evaluate the comfort and usability of the ergonomic sit-stand desk converter with the aim of preventing disorders caused by constant sitting in workers.
Methods: 30 employees and faculty members of a university voluntarily participated in this study and provided informed consent. After the necessary explanations, subjects were provided with two researcher-created questionnaires ( Local Perceived Discomfort (LPD) and Sit-Stand Desk Converter Usability Questionnaire (SSDCUQ)), two methods of posture analysis, two methods of Workstation evaluation and general satisfaction along with 20-8-2 software and an ergonomic desk converter. After the test period, the data was analyzed using SPSS version 22 software and statistical tests such as mean, standard deviation, Spearman's rank correlation coefficient and Pearson correlation coefficient.
Results: The overall mean LPD in the different body parts was 0.48 ± 0.87, indicating that the converter functions in the range of no problem to very little discomfort. The average overall satisfaction with the function of the converter was 3.18 ± 1.08 ,which is in the medium to good range. When analysing the different sitting and standing postures, a significant correlation was also found between the different situations of using the converter (P<0.0005), which indicates an improvement in sitting and standing posture while using the converter.
Conclusion: Height-adjustable workstations are a good choice to reduce sitting time and improve posture. Despite the improvement in sitting and standing posture when using the converter, there are limitations, such as ignoring the software warnings for sitting and standing in the mechanical converter studied.

Prediction of Musculoskeletal Disorders Based on People's Demographic Information Using Artificial Intelligence Methods and the Cornell Musculoskeletal Discomfort Questionnaire
Mousa Nazari, Arezoo Sammak Amani, Mohammad Amin Mououdi, Mohammad Mahdi Alyan Nezhadi,
Volume 11, Issue 4 (Iranian Journal of Ergonomics 2024)
Abstract
Objectives: Work-related musculoskeletal Disorders (WMSDs) are the most significant challenges in both developing and developed countries, affecting the majority of individuals throughout their lives. Considering the detrimental effects of musculoskeletal disorders on the productivity and general health of employees, this research utilizes the Cornell Musculoskeletal Disorder Questionnaire (CMDQ) to develop an intelligent model for assessing and predicting the levels of musculoskeletal disorders.
Methods: In this descriptive-analytical study, 810 employees from five organizations (in four occupational categories, including administrative, technical, production, and services) completed the CMDQ voluntarily. After collecting the questionnaire and performing relevant statistical analyses, data normalization and clustering based on the K-Means method were used to determine levels of musculoskeletal disorders. Finally, the multilayer perceptron artificial neural network was trained to predict the levels of musculoskeletal disorders; moreover,  the criteria of precision, accuracy, recall, and F1-score were used to evaluate the proposed model.
Results: The performance of the proposed model in predicting the levels of musculoskeletal disorders is presented in two scenarios (use and non-use of the Synthetic Minority Oversampling Technique (SMOTE) method) based on the evaluation criteria provided. The accuracy, precision, recall, and F1-score values were 0.724, 0.709, 0.756, and 0.720, respectively. The appropriate accuracy and precision in the proposed model indicate its capability to identify the levels of musculoskeletal disorders in individuals and help healthcare professionals take necessary measures to prevent and predict them.
Conclusion: This study employs the CMDQ questionnaire and artificial intelligence to analyze musculoskeletal disorders in the workplace. The proposed model demonstrates significant accuracy and precision compared to similar studies. The results indicate that this model can be utilized to identify and predict musculoskeletal disorders in organizational employees, offering the potential to expedite the identification process and reduce costs.

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