The results of this study provided more information about correlated factors of grip and pinch strengths. The regression equations developed in this research are applicable to clinical treatment and ergonomics programs.

Cognitive demand and mental workload assessment are essential for the optimal interaction of human-machine systems. The aim of this study was to investigate the cognitive demands and mental workload as well as the relationship between them among the mining control room operators.This cross-sectional study was performed on 63 control room operators of a large mining plant located in Iran. Cognitive demands and mental workload were assessed using cognitive task analysis (CTA) and NASA Task Load Index (NASA-TLX), respectively and the analysis was performed using SPSS version 21. Independent samples Ttest, Mann-Whitney U test and multivariate linear regression were used for data analysis.Twelve cognitive demands were extracted after observing the tasks and conducting semi-structured interviews with the control room staff. The mean scores of total cognitive demands and MWL were 6.60 and 72.89, respectively, and these two indicators showed a positive and significant correlation (r ¼ 0.286; P ¼ 0.023). The participants' demographic characteristics such as age, education, and work experience did not affect mental workload, but the two cognitive demands (memory and defect detection) affected MWL.High cognitive demands and mental workload indicate poor interaction between humans and machines. Due to the effect of memory load and defect detection on mental workload, it is recommended to assign cognitive tasks based on memory and defect detection to the machine to reduce the mental workload and improve humanmachine interaction.

BACKGROUND: Outdoor workers are exposed to heat caused by atmospheric conditions and solar radiation. More specifically, those working in palm groves are more in danger of heat stresses since they harvest their crops in hot seasons. OBJECTIVE: This study was aimed at investigating heat stresses and strains in date harvesting workers in groves around Jiroft, Southeastern Iran. METHODS: This study was a descriptive-analytical one of cross-sectional type. In this study, three environmental indices including Wet Bulb Globe Temperature index (WBGT), Environmental Stress Index (ESI) and Discomfort Index (DI), the physiological strain index (PSI) as well as perceptual strain index (PeSI) were analyzed to investigate stresses and strains in workers. For this purpose, 59 date harvesting workers (36 men and 23 women) in palm groves in Jiroft were analyzed. With accordance to date harvesting season, data collection was carried out from August to September, 2017. RESULTS: In this research, the means of environmental indices including WBGT, ESI and DI were 32.77 • C, 30.39 • C and 33.22 • C, respectively and they all revealed direct and significant correlation. Moreover, Time-Weighted Average for Wet Bulb Globe Temperature index (WBGT.TWA) was significantly different from Threshold Limit Values for Wet Bulb Globe Temperature index (WBGT.TLV). The scores of the PSI and PeSI were 2.28 and 6.61, respectively. CONCLUSION: The results of this study indicated that date picking workers were exposed to heat stress more than the reference value of WBGT recommended by American Conference of Governmental Industrial Hygienists (ACGIH). In addition, workers suffered a low degree of physiological strain and a moderate degree of perceptual strain caused by heat stress in palm groves in Jiroft.

Background: Human error is the most important cause of occupational and non-occupational accidents. Because, it seems necessary to identify, predict and analyze human errors, and also offer appropriate control strategies to reduce errors which cause adverse consequences, the present study was carried out with the aim of identifying human errors while operating meat grinder and offer suggestions in order to reduce human errors in this human-machine system. Materials and Methods: This is a descriptive study. In this ergonomic study the "Task Analysis for Error Identification (TAFEI)" technique was used in order to identify human errors while operating a meat grinder machine. According to this technique, firstly, tasks of human side of the interaction were described by Hierarchical Task Analysis (HTA) and then the State-Space Diagrams (SSDs) were drawn. Finally, after forming the TAFEI diagrams, the transition matrix table was prepared in order to identify human errors. Results: After completing all the steps of TAFEI technique, the transition matrix table was formed. Results showed 49 illegal transition states; therefore, 49 human errors were identified and described while operating the meat grinder machine. Conclusion: The results of this study showed how and under which conditions may meat grinder users do error in the human-machine interaction. In this regard, possible human errors resulting from non-ergonomic design of Iranian meat grinder machine were identified.